This critique is leaning really hard on their interpretation of "dying". They take the literal company is going to fail type of dying where as I have always taken it the same way he has presented it in his "rot-economy" context. They can remain financially "successful", but more and more people hate their products, their products are getting worse, their products are "dying". Google Search is still a good example, the old Google search is "dead" if you like, a know many people, including myself who no longer use it. More people hate and getting off Facebook. More people are jumping from Windows to macOS or Linux.
These tech giants need AI to continue to grow, and that growth at the moment seems to be coming from just two AI companies who are burning a record about of investments. OpenAI has raised nearly $200B, that is more money than Australia's tax revenue.. and they are getting further from being profitable as Chinese models are getting better and much cheaper.
The article linked seems right, but you have to take these morbid analogies in a very specific way, and assume that the only way to measure these companies is revenue/profits/money rather than their products.
I wish people would hold actual professional media economists to the same standards, along with journalists who just repeat press releases without actually challenging statements. His main argument has been the numbers don't make sense, and can't see how this won't end badly for a lot of people.
If many people hated their products, they wouldn't use them. If they didn't use them they would not be financially successful. Google is not dying just because you personally have a feeling the results are worse than before and there is no definition of dying that would be consistent with Google's current state. If Google were to die they would die the way Yahoo did, because a competitor was demonstrably better than them and everyone switched off. There is no realistic evidence that this might occur in the near future.
If I have a billion trillion dollars but 20% of the population hates me, but I get to live in a giant solid gold mansion with an army of servants keeping the 20% away from me, have I really failed?
Still a failure because it is propped up by an inflated US dollar. Those trillions would mean nothing when the US economy collapses due to a cumulative effect of massive national debt, unending wars and inflation.
At least if you have the population by your side, you wouldn't have "guns, gold, potassium iodide, antibiotics, batteries, water, gas masks from the Israeli Defense Force, and a big patch of land in Big Sur I can fly to" [1]
They are all willing to risk everything to see if their bet on achieving "singularity" fructifies. I don't see us getting anywhere close (at least with the current tech).
One thing I’m observing in these comments is a willingness of folks to project their own predictions onto Ed’s statements when validating their plausibility. Eg. “I think he’s wrong about the timing but I do expect AI companies to go to zero.”
You can do that, but then you’re no longer discussing his predictions. You’re discussing your predictions, and your own positioning.
Those differ from Dan’s essay, which engages with the literal text of Ed’s numerous predictions during 2024 and 2025 which are demonstrably invalidated by their measurable outcomes.
On the flip side, I also see many people taking this thread as an opportunity to shit on Zitron as a person, and not "discussing his prediction". Incompetent/ blow hard/ dishonest are ones I remember off the top of my head.
AI by itself, is surprisingly polarized; Ed Zitron even more so.
Incompetent and dishonest are characteristics that follow from this professional work, adequately describing an individual who continues to make poor predictions, analyses and false statements refuted by past events.
- a list of predictions that are entirely wrong, from A-to-Z, and are not even resembling what ends up happening
- a list of predictions that are wrong, but where the underlying points are in fact interesting and have some predictive value, and it's just the "last step" that is wrong
For example, one person might say "oh it's raining in Dallas therefore I should buy some TI stock". And we'll say for sake of argument that they say that even though it's nice and sunny in Dallas at the moment.
Another person says "Oh its raining a lot in Idaho and that is going to increase potato yields and therefore I will buy McDonalds stocks cuz fries will be cheaper". In this hypothetical it turns out McDonalds buys all their potatoes from ... Kansas or something instead (and it's a specific kind of potato in a completely separate market)... but Idaho potato yields _did in fact go up_.
An even more straightforward point: the iphone 3GS comes out in 2010, people are very hyped, someone looks at how RIM _still_ hasn't gotten its shit together and declares "RIM isn't going to to be able to stay profitable 18 months from now, they're gonna have their lunch eaten".
Turns out that RIM still made a healthy profit in 2010. and 2011. And 2012. 2013 was their first loss in a while... and then it wasn't until 2014 that they really got kicked in the face.
The prediction was early, overestimated how long of a tail RIM would experience, but how wrong was it? Was the prediction of some utility?
I'm saying this... it would be helpful if _some_ more AI companies flamed out. In some sense he does himself no favors by focusing on the corps with the biggest war chest instead of the various AI companies that spend a bunch to go nowhere fast and then have just disappeared.
Why is Zitron’s repute evaluated entirely on the basis of failed predictions? Predictions are incredibly hard. AI enthusiasts and thought leaders have made so many demonstrably incorrect predictions it’s hard to keep track. Based on this metric, Altman and Amodei should never be taken seriously again.
Have you ever listened to Zitron speak? He's not exactly the type to hedge his predictions behind careful language about how hard predictions are. He makes every one of these predictions with absolute confidence and conviction.
And we're used to insulting and making fun of the prominent members of those circles too, see: "Scam Altman", the large variety of jokes about Musk's timelines, comments about Dario waking up in a cold sweat whenever a powerful new open weight model drops, the "AGI achieved" meme etc.
Being thorough and accurate might make you a lot of money in the stock market, but it's not a good way to get any media presence, because that demands being in front of people quite often, and basically nobody can be insightful and well researched in all topics of the day. Once you become a pundit, whether on politics or tech, and rely on eyeballs to feed you, you are going to be throwing stinkers. And at that point, you might as well just align with an audience and not care too much about whether you are predicting anything accurately.
We have people telling us the next recession being imminent all the time. Others told us that NFTs were key to the future of art. That's the pundit way. If you want accuracy, you become like Charlie Munger, have maybe 2, 3 really good insights througout your career, and hope do to well using the insights yourself, not by being a pundit
This is exactly right. Now, that does mean something about Zitron: he’s a pundit, not an expert or a forecasting genius. You could point to any number of analogous booster types. Twitter/X somehow loves pushing these people onto my recommended feed. I remember reading breathless threads about how o3 was going to single-handedly end white collar work. There are just more of that sort of person, so none of them in particular gets the same amount of attention as Zitron, who seems to be the only person willing to go on the record against AI. Maybe his overall worldview is sound, and maybe it isn’t. But he’s not really making confident, specific predictions about the future.
Which leads me to a criticism of the piece: several assertions are described as “Wrong,” with no explanation or citation, which are not obviously wrong to my mind. For example, the assertion that “DeepSeek has commoditized the [LLM]” is at least debatable. It is a prospect that the major labs seem to have at least considered.
In my experience, people who make fun of AI's ability to eliminate white-collar work are exactly the same people who are white-knuckling it, hoping they can make another $300k next year to buy that Rivian.
People who don't need a salary look at the situation more objectively and, in general, can see that a lot of white-collar work is in peril.
The flip side of that is that at least half of all white-collar work was already useless before AI. If it hasn't already been eliminated, there's no reason to assume a-priori that AI can eliminate it.
I think that is tied to the general trend that people see themselves as far less replaceable than others. And I’m not sure that people who don’t need a salary are exactly objective about it - unless you mean people who live off the state or something, those are people who need their capital reserves to continue to appreciate in order to sustain their lifestyles, and are thus relying on the destruction of white collar work to justify the valuations of the technology companies which are underpinning the strength of the markets. It’s like saying in the 19th century that only the propertied classes should be allowed to make decisions about labor policy, because the laborers themselves have their judgment clouded by their position.
But I take your point, and I only brought up the o3 example to emphasize that people on both sides of the booster/doubter debate can be prisoners of the moment. There are boosters eternally convinced that the utopia (or armageddon, for the doomer-inclined) is either already here or imminent, and there are doubters eternally convinced that we have reached the peak. One of them will eventually be right, but neither has been yet. You can’t fault one of them for calling their shot if you’re not willing to see it happening on the other side.
They haven’t allowed a recession to happen since ~2009 when they massively inflated their way out of the worst of the last one. Learned to have the cake and eat it too.
The only problem is after a few rounds of this the currency becomes worthless, and we’re well on our way. Inflation is a major component of those numbers rising.
And that's when we pay off the national debt for pennies on the worthless dollar. The pro move would be to stop lending the US money, but that's not going to happen.
The US doesn't require that you lend it money, it possesses the global reserve currency. It'll take it from you via currency debasement. That's a world problem whether the world likes it or not. There is still no viable (realistic) alternative, and that includes the Euro, Yen, Yuan, gold, Bitcoin.
There are no lenders outside or inside of the US for $20 trillion in new debt over the next decade. Monetization is the only path. If you mean lend the US money in regards to holding or using USD (while it's being debased as it is now), then sure.
And if the world tries to shake off the USD, well, Iran & Venezuela (oil transactions assist USD dominance) would like a word. I'm not suggesting defending the USD reserve position via military action is moral, I'm suggesting it's certain to occur.
> First, the favorable impact of the artificial intelligence investment boom on economic activity and earnings will likely diminish significantly in 2027. That’s because what’s relevant for growth is how much investment is increasing, not its level. The increase in investment in 2026 will almost certainly be the peak. There aren’t sufficient resources — construction workers, electrical generation capacity, or chip manufacturing capacity - to increase investment by the same magnitude in 2027. Nor are the dominant hyperscalers likely to have the free cash flow and balance sheet capacity to sustain a bigger increase in investment in 2027 compared with 2026.
> Second, as the growth of investment spending slows, the growth in earnings of hyperscaler suppliers will falter, profit expectations will diminish and price-earnings ratios will shrink. The “picks and shovels” providers will suffer a double whammy - slower demand growth and profit margin compression. On the way up, higher demand leads to wider profit margins that sustain equity market valuations. On the way down, the outlook for earnings deteriorates quickly as the shortfall of demand relative to expectations is exacerbated by a collapse in profit margins.
> Third, as the investment cycle matures, the focus will shift to the returns that the hyperscalers are expected to earn on their massive investments. I suspect it will be difficult for the AI hyperscalers to generate sufficient revenue ($2 trillion or more per year) to generate the returns needed to justify an AI capital base that is likely to reach $5 trillion.
(I'd encourage you to read the entire piece, it was written by Bill Dudley, a former president of the Federal Reserve Bank of New York, and is too much to quote in its entirety)
Yet with all what? AI stock pushing indexes high and US stock market being cheap because dollar lost 30% of volume in last few years so the whole world is trying to profit from short ride? Record low unemployment because gas and groceries are so expensive most people work 2 or 3 jobs just not to end up homeless? Democrats are going to retake because ballroom and gold arch does not affect gas or grocery price. They will retake because Republicans proved they are extremely soft on corruption. Not only they allow POTUS & Fam. steal billions from taxpayers, they are not stopping it and some even profit themselves. Dems will retake because we have a dangerous version of plutocracy mixed with socialism, where one person on the top (POTUS) unilaterally decides that US Government will take a free chunk out of Intel, or that 20 billion of taxpayers money will go to help Argentina or Brazil or Japan. That's why.
I mean I wish you a lot of fun playing this discussion game online, but I kinda fail to see the point of it.
Someone could now of course say "hey, but are your sure that these are really the metrics we should be looking at?", which could then be countered with a "well of course! This is how one measures a recession, no?"
And that could go on forever, achieving absolutely nothing.
I feel like I've been in a recession economy since the day I entered the workforce 14 years ago. The movement of the stock market has had no effect on my reality. It's like two different universes inhabited by two different sets of people.
IMO, all the narratives we were exposed to around privilege before and after COVID were a cover up of this fact that we have a two-class system which is explicitly creating this condition. The issue is at the system design level and goes far beyond "technology putting people out of a job". The privilege narrative was classic communist-style "accuse your enemy of what you're doing yourself." It was literally the privileged few preemptively accusing the unprivileged masses of being unfairly privileged in order to take control that narrative before it was used on them.
> We have people telling us the next recession being imminent all the time. Others told us that NFTs were key to the future of art.
That's quite the conflation, and a very subtle way to tie a claim that's still unresolved to one that is to try and make the first one seem wrong with no evidence. Recessions are almost guaranteed in our system, they're a part of a cycle. Unless you think that the Great Recession was the last one in history, saying the next one is 'imminent' would be correct for any other viewpoint. We just don't know when it'll officially start.
...get any media presence, because that demands being in front of people quite often, and basically nobody can be insightful and well researched in all topics of the day
What? Zitron is getting a lot of media attention by repeating the same takes hundreds of times. He's not a general pundit.
> For any of his posts that I read, while there are numbers thrown around, the numbers don't actually connect to a coherent argument. In many cases, as we saw above, the numbers don't even really support his argument (such as an MAU decline in Facebook causing Meta financial problems which would then cause Meta to spuriously insert AI in places it doesn't belong). I suspect he's relying on people's eyes glazing over when they see numbers and just not thinking about what the numbers mean.
A frustrating thing about Ed Zitron is that he sometimes breaks news - gets hold of leaked numbers that nobody else has, for example - but he then wraps those numbers in his own extremely biased commentary. This makes it much harder to evaluate how credible the new information is.
Yes, and his post about the exact same data was noticeably more confusing and less illuminating than theirs because he was primarily concerned to point to whatever the biggest number was and go "Ooh, big number!"
There was a major material difference between the FT and Ed's post: FT explicitly noted that OpenAI has $billions in cash on hand (which is relevant if you are analyzing data about solvency), while Ed's post obfuscated that data point.
As someone else mentioned, ignore Ed’s personality and look solely at the balance sheets and capital analysis. Regardless of delivery, the math doesn’t math.
It's wild to me how much Ed is criticized while pathological liars like Musk and Altman are glossed over.
(Disclosure: I pay for Zitron's publication for the capital figures and exclusives he gets his hands on, I do not pay attention to his interviews, we are fact finding, if he wants to perform, I am not bothered, I've seen the performers on the other side, just keep the facts coming for ground truth)
> For example, when Timothy B. Lee looked at a spreadsheet that Zitron used to create a projection of Anthropic's revenue, he found, "He doesn't count February 1-10, counts March 1-10 twice, counts August 21-October 21 as one month instead of two, and doesn't count October 21-November 1. [another commenter notes that his spreadsheet also contains February 30] ... Ed claims he tried to compute Anthropic's revenue for 2025 and came up with $3.6 billion, suggesting some funny business [but the numbers work out once you fix the errors]"
As someone with a bit of understanding of accounts and finance I don't think Ed's analysis is very good. He's not someone who would pass a finance exam.
I posted here a while ago when his bubble prediction lapsed and plenty of his fans were here. Telling me how I was wrong and the Q2 reports weren't complete yet because it was still early July and blah blah
Criticized as being poor human beings, or as being poor executives?
Because the former, as P.T. Barnum pointed out, is just free advertising. And I see far more of that than the latter. Now, if and when their various empires collapse there will be no shortage of people pointing back and saying "all the signs were there", but in my everyday life (obviously just a single point of anecdata), it feels like I see a lot more coverage of them as "bad people" than as "bad at what they claim to be experts on".
HN has a fairly complex user footprint, it's not everyone of course and I do not mean to paint too broadly, but there is a strong contingent of those pro in a cluster.
Would you like a list of pro Musk and Altman users based on their comment and submission history? I'm unsure if that violates the site guidelines, and I prefer not to have my subthreads detached or stern reprimands by mods (it makes me feel bothersome in a host's home).
I certainly believe there are some Musk and Altman glazers on this site. There are also certainly Ed Zitron glazers.
The point is not a few users you can point out, it wouldn't prove anything. The point is that you claimed that Musk and Altman are "Pathological liars like Musk and Altman are glossed over". I would say that requires at least sentiment analysis that an extremely high percentage(90+%) of hackernews users match that description. And that is simply not what I observe when I use this site. My feeling is that sentiment for Musk and Altman are neutral at best.
The bubble you’re talking about exists, it is SF and the rest of the tech industry. It’s literally where the AI leaders are located, where they overhype each others
I am a realist, I understand the cult of personality, etc. Just like I wouldn't spend a moment trying to talk a Catholic out of their faith. I have no feelings on the topic, this can only last so long based on capital trajectories.
For me, HN ist rather some kind of counterweight/counterbubble where not everybody is insanely critical and cynical about Elon Musk and Sam Altman. :-)
FWIW I think you spend too long on this site. I'm not trying to be mean but I see you much too often here having strong opinions thinly sourced and think that perhaps your time would be better spent elsewhere. I, too, spend more time than is healthy for myself on this site but think I spend a fraction of what you do.
I realize we've both been in this community for a long time but I think one of the things I find about participating in Reddit and HN communities over time is that, I stop both being able to separate the truth of a matter from the argument itself and I stop being able to conceptualize the people in the thread as people and not mouthpieces for argument. There's a special toxicity that arises on these sites, where the argument becomes the main issue at hand and I see a conversation as a large conflict between world views. I may be projecting my own feelings here, but think it's worth contemplating these hot button issues elsewhere and responding in a lower temperature forum more conducive to actual discourse.
The concern is noted and appreciated. I am here (as you mention, likely too much) to learn, to grow, to share, and to be curious. I don't take this place too seriously, and I hope you don't either, it's not meant to be serious. Take value from what you can, discard that which you cannot. I have enough, and so have more free time than most. I am a scholar first now.
> and think that perhaps your time would be better spent elsewhere
Open to ideas, propose where. I have...looked extensively for work with meaning and am coming up short. Mods have my email if you want to reach out. I am always open to being proven wrong and/or updating my priors. What needs to be built that is also worth building? I am always happy to contribute my time, energy, and resources to meaningful causes and work. I have done my best to be interesting to people who can provide opportunity, and yet find opportunity in the scope of meaningful work in short supply.
> Open to ideas, propose where. I have...looked extensively for work with meaning and am coming up short.
FWIW I've decided to view sites like HN and Reddit as "intellectual junk food." There's a feeling that one is engaging in intellectual betterment by using these sites, but in practice none of the outcomes valued in intellectual output fall out of reading and posting a lot on these sites. I can't tell you what you should work on; every human who wishes to be creative struggles with this problem.
Ultimately very few problems can be solved by talking endlessly about them, whether that's online or in real life. I suggest just trying to actually make solutions to problems if you want to use your time that way. Talking with others can be a great way to get energized about solving problems, but doesn't take the place of actually solving them.
I'm not financially literate enough to trust my own analysis of the numbers. Ideally I'd like commentary from someone like Bloomberg's Matt Levine, a genuine expert in financial matters who is also extremely good at explaining them in terms non-finance-professionals like me can understand.
I didn’t even see the OP comment as a criticism of his analyses, just that he likes to do this rhetorical trick of dropping in numbers that are, at best, tangential to his point to prop up the argument’s credibility. Sometimes he does this in the middle of a real financial analysis which is even more maddening and confusing.
Fair, if you’re looking for reliable financial commentary Matt Levine is indeed the goat. Zitron is more like an old school blogger, with a very aggressive and corrosive style. My approach for internal documents leaked by Zitron is just to wait to see if Bloomberg picks up on the info or not.
No, you can't. The numbers are genuinely confusing, and Zitron actively works to make them more confusing rather than explaining what they mean because he needs them to sound as bad as possible. He also buries the numbers in thousands of words of prose!
The problem is that some numbers genuinely require a critical eye. If a source tells you that the OpenAI CFO told employees July ARR exceeded the Q2 total, there are a number of serious questions to be raised on how these numbers were calculated and what the point of such a confusing comparison is supposed to be. (I think the answer has to be that ChatGPT wrote the CFO’s script, no human financial expert would think to compare an annualized figure to the sum of three specific months.) But it’s hard to analyze the facts appropriately when they’re relayed by a guy who tells you that it’s all a giant scam and infers the worst possible answer to all the questions.
You're broadly right but I think you're dead wrong about the CFO statement — I think "July revenue alone exceeded all of Q2" is an extremely normal thing to say when revenue is going up at an insane rate. For example, if it was not true that June revenue exceeded March-May revenue, the point would be to show how their revenue growth has accelerated.
She, and we do not have the direct quote. It's a paraphrase, and the report can't seem to decide whether they're talking about revenue or growth. If she was talking about growth, "the ARR growth in July exceeded the ARR growth of Q2" is perfectly coherent.
"July revenue alone exceeded all of Q2" would be a very normal thing to say, but you're skipping over some of the words. Unless revenue is sharply dropping, annualized recurring revenue in any month will exceed the revenue incurred in any quarter, because it's an annualized figure.
I think the most likely explanation is that the CFO misspoke and intended to say something more like your quote, or perhaps she spoke correctly and was misquoted. But without audited financial statements, all we have is speculation, and there have definitely been times in the past when executives of major companies made intentionally misleading statements about their revenue. (In fact, this thread began with a question about why you can't just look at the numbers, and here the answer is that nobody has reported the actual revenue numbers this comparison is based on.)
I didn't say I hate it. I've never seen any reason to doubt that Ed Zitron is a great guy who's working hard to tell the truth as he understands it.
My point is that any discussion of how a large, complex company is doing requires making judgment calls about which numbers are more or less reliable, do or don't matter, etc. This is especially so when it's a private company that has not yet any kind of meaningful disclosures. So if you don't think Ed Zitron's judgment is sound, there's no good way to adjust his commentary for that and "just look at the numbers", because the numbers have been filtered by his judgment even if they all came from accurate underlying sources.
> Given how fast these companies are growing (in terms of revenue and profit), it doesn't seem that AI is, as Zitron implied, some kind of desperation move they're reaching for because "they don't know how to grow" and are all out of ideas
Growth isn't a valid rebuttal, unless we can also sus out how much of that growth is tied up in circular financing of AI projects. We have a pretty good idea how much of Nvidia's valuation is tied up in the AI craze, it's a bit harder to tell with the megascalers....
The predictions were predictions of revenue. Circular financing of AI projects does not create revenue for OpenAI, Anthropic, Meta, or Google. Only Nvidia benefits from it.
Predicting revenue growth will stall and it does not was wrong.
A startup raises $50 million from OpenAI and Anthropic to finance API calls to OpenAI and Anthropic that they are using at a loss who in turn spend that money on compute with Microsoft and Google who in turn invest in Anthropic and OpenAI who then invest the startup using the startup’s revenue to value it… the cycle repeats.
There are multi-billion dollar valued startups invested in by OpenAI and Anthropic with hundreds of millions in ARR that are spending 90% of their revenue with Anthropic and OpenAI.
Situational Awareness, the fund that recently imploded, invested tens of billions into AI companies using their holdings in Anthropic to help finance the investments…
This could all work out fine in the long term, we’re all just speculating at this point, but the circular financing is absolutely making it to revenue because capital invested into startups is used to fund growth which is achieved by subsidizing costs incurred with OpenAI and Anthropic.
The vast majority of startups are not funded by OpenAI or Anthropic. They are not a significant source of venture capital. Meanwhile, OpenAI is pulling in $40B+ per year and Anthropic $65B+ per year.
You are mixing up valuations with liquid cash and you're also making sweeping statements about how those startups are spending their cash. A majority of a raise is not spent on AI compute.
Situational Awareness blew up because they used leverage to invest, and leverage is a great way to blow up any fund even if they were directionally correct about AI.
You’re applying pre-AI investing to a post-AI world. Yes, a decade ago, a startup raised money and spent 90% of it on people. The people built software which had incredible margins. Build it and then print money for ever more. That’s not the case any more, these startups no longer have incredible margins, they’re not collecting $100/m per user and banking $99 of it. They’re collecting $1000 and sending $999 of it to Anthropic and OpenAI.
Revenue numbers are vastly inflated compared to pre-AI but these startups aren’t keeping the money. Profits are worse than ever before. Startups with 30 employees that reach $100m ARR in 6 months are not banking $90m or $80m or… they’re just passing that money straight through to OpenAI and Anthropic.
If startups aren’t just funnelling all their funds raised straight through to OpenAI and Anthropic, where is this combined $100bn in revenue coming from? Who is paying for it? My spend on software certainly hasn’t gone up in a post-AI world. My company is spending less on software now.
OpenAI have stopped being so reckless with their cash investments which is why they appear to have slowed down but they’re still investing millions in huge numbers of startups through token allowances. They invest $2 million in every YC startup (or did a few months ago). There’s an entire market of reselling these tokens!
Can you provide any examples of any of the megascalers publishing any detailed financials that touch on their AI spend or revenue or profit? The only one I’m aware of that comes close is Microsoft and they have still buried it in barely related line items which still leave us making assumptions.
There’s speculation on both sides and certainly Zitron is on the extreme end of the anti-AI side with the most cynical speculation but it is indisputable that none of the megascalers are open about their AI financials. Hence, we are all speculating endlessly. If only there were published financials then the speculation could end!
The obfuscation of financials doesn’t necessarily mean something bad is happening, it could be a competitive advantage for Google to be secretive about how cost effective their TPUs are or for Microsoft to hide how much revenue uplift they’ve experienced by adding AI to 365.
They don't publish their AI spending, revenue, and profit - but they do tend to break out other non-AI segments of their companies which can demonstrate that at least part of their growth isn't relevant to AI.
> They don't publish their AI spending, revenue, and profit - but they do tend to break out other non-AI segments of their companies which can demonstrate that at least part of their growth isn't relevant to AI.
So the previous statement that "As public companies, the megascalers publish pretty detailed financial reports" is incorrect and irrelevant to the question that was asked.
I'll expand the section of the article that it quotes:
> Although this wouldn't be in the spirit of Zitron's statement, one could argue that Meta is actually dying, it just hasn't died yet. However, the reasoning in Zitron's argument is incorrect here—the Meta, Google, and Microsoft ecosystems are not dying. Given how fast these companies are growing (in terms of revenue and profit), it doesn't seem that AI is, as Zitron implied, some kind of desperation move they're reaching for because "they don't know how to grow" and are all out of ideas.
So the argument here is that Ed says those companies are dying, but Dan Luu points out that their economic figures show that they are not.
The counter-argument is "Growth isn't a valid rebuttal, unless we can also sus out how much of that growth is tied up in circular financing of AI projects"
My point is that the public reports of these companies, while not helping us unwind the circular financing, do at least show us that their non-AI businesses are growing at a healthy pace. Which supports Dan's argument that these companies are not dying.
Financial reports alone don’t paint the whole picture when it comes to valuations. For example, theoretically amazon has committed to invest 25 billion in anthropic, and anthropic has committed to spend 100 billion on aws compute. As far as we can tell, no real money has actually changed hands in either direction, but both valuations are being buoyed by their prospective investments…
Because of accounting tricks, quarterly financials don't accurately reflect the size of this fiery money pit.
The datacenter build-outs are all majority (>50% ownership) financed by other companies, with a shell company owned by the hyperscaler as a minority owner. The data center then grants the hyperscaler an exclusive leasing agreement, and because the shell company is a minority owner, legally, it's not their debt.
The only reason this has worked is because there's such a long delay taking delivery on GPUs. When these capital allocators start paying for GPUs in data centers which haven't yet broken ground, then we'll see a very visceral market reaction. Some of that has already happened, but there's enough momentum that it can be absorbed and dismissed as an anomaly. But with governments unexpectedly passing moratoriums on data centers everywhere, it's only a matter of time before there's no data center to offload those GPUs to. That's when the music stops.
I believe that was Zitron's central thesis and why he started reporting on this. It mirrors the mortgage-backed securities situation that led to the 2008 GFC, except with even fewer guard rails to prevent financial calamity.
Investors are very savvy and keenly aware of what's going to happen. There's just zero incentive to pull the fire alarm and risk being blamed for crashing the market. If you're wondering why everyone's running toward the exits instead of treating these tech companies as 10+ year investments, you have your answer.
Over the past few years, I had helped Ed with some difficult nuances around the obscure technical aspects of serving LLMs (e.g. benchmarks and model caching); he has also shouted myself and Simon Willison out positively multiple times. I stopped assisting him because he repeatedly misused said advice to the most cynical interpretation ("how can this be interpreted to make AI boosters sound crazy?) and often made it misleading at best. Nowadays I suspect he views me as one of those crazy AI boosters.
Not challenging him was a mistake in hindsight, and I own it. Going forward I will no longer be helping writers/journalists with a clear anti-AI bias.
He made a blog post, literally last month, and it said that AIs have no use outside of coding.
It just shows he's done zero research on the things he talks about all day. Radiologists are using them, ad firms, artists, translators, law firms, auditors... It's hard to think of a white collar firm not using them.
This reads slightly weird and more like a pledge of alignment than a statement from the heart.
But apart from that, I guess that's always the learning? Journalists (or people labeling themselves as such) often have their own story they want to tell, and usually do so by building it out of little blocks of reality stacked together to form the desired picture.
I would predict a similarly frustrating experience being equally probable even without the "clear anti-AI bias" attribute set.
That's an unfair characterization of tech journalists in general. When BuzzFeed News was around, I worked closely with them on technical aspects and projects to ensure that everything was correct and accurate, and there were very receptive to it; it was not a "directionally correct" thing, the journalists wanted to avoid any unintentional. That was also one of the reasons I was open-minded to helping Ed even though we ideologically disagree: the truth is what's important.
BuzzFeed News incidentally was how I first came across Ed on Twitter from his tech PR work about 9 years ago, back when he was writing guest editorials on Gizmodo about Person of Interest (which is very very funny in hindsight). It's from the heart that I'm a bit bummed out that things turned out this way.
Upon further thought, I realized this should be counted as a correct prediction for Zitron! Zitron did indeed “keep writing this stuff until…proven wrong”. Zitron’s prediction says nothing about what happens after being proven wrong.
> In terms of the style of reasoning, of the futurists reviewed, he's probably closest to Kurzweil, in that he uses numbers to give a kind of aura of credibility, but if you know something about the topic he's discussing or look at the numbers, the reasoning falls apart.
In one of his posts a few months ago, he went on a weird tangent about the CEO of ServiceNow talking about sales planning and whether his teams are "on plan" or not. For people who haven't spent time in or around sales, this is an extremely common shorthand for quota tracking.
Ed's rant about how impossibly weird and inhuman the framing was revealed how little he knows, and cares to know, about the mechanics of the businesses he claims to profile. Yes, something like "on plan" is jargon, but a shred of reasonable journalistic curiosity (a Google search) would explain what it means and how it's a normal statement for a career-sales CEO.
>Ed's rant about how impossibly weird and inhuman the framing was revealed how little he knows, and cares to know, about the mechanics of the businesses he claims to profile. Yes, something like "on plan" is jargon, but a shred of reasonable journalistic curiosity (a Google search) would explain what it means and how it's a normal statement for a career-sales CEO.
This is precisely the sort of feedback an LLM could provide him before he hits the publish button, funny enough.
Big shout out to Zitron. Everyone knows how to monetize good predictions (stock market, etc), but he might be one of the few who successfully monetized bad predictions, making him a step ahead of the rest of us.
P1. AI is useful powerful and (P1a) will continue to get more useful and powerful at the same rapid pace it's been improving
2. AI companies are very profitable, and (P2a) will be wildly profitable (eg $30T TAM) in the next few years
These are completely separate. But in practice people seem to be either proAI (both true) or anti AI (both false). P1 is clearly true and I find it hard to take anybody seriously who says otherwise. P1a... Who knows, gotta hit a wall sometime. P2 I'm way more uncertain about (especially P2a) but it seems like people like Zitron reason backwards from hating AI.
In my mind the most obvious scenario where AI gets used a lot but AI companies (exlc. NVIDIA / chip makers) aren't worth much is the hardware becomes capable of running the current state-of-the-art models locally, cheaply, and those models are basically "good enough" for 90% of tasks.
Currently they don’t seem to be. At least OpenAI is haemorrhaging money left and right. Thing is, the compute for all this is far more expensive than anyone is willing or able to pay.
I’m not really convinced by any of this, in fact it seems most of the predictions were pretty correct and that Meta and Alphabet are having big issues is a shared opinion by multiple observers and pretty much every employee they have.
If they were doing so well why the layoffs? Why the tightening both in salaries and perks and work life balance? Why so many choices disrupting morale for their employees?
Help me understand where Meta and Alphabet's issues are. They seem to be doing quite well on paper -- nothing anomalous in terms of profitability or scaling recently. Layoffs are to be expected when AI can increase productivity.
The problem with judging Alphabet and Meta on aggregate performance is that their advertising businesses print so much money that they can invest everything in a boondoggle and coast when it blows up. Zuckerberg burned $100,000,000,000 on the metaverse and it didn’t make a dent.
That said, Alphabet and Meta are borrowing against their future advertising profits to fund their AI boondoggles. If the advertising businesses keep growing then they’re somewhat insulated from their own missteps but the reliability of the advertising business depends on companies having money to spend on advertising.
The metaverse was mostly self-contained and the failure had zero consequence for the broader economy. AI on the other hand, every major fund is investing everything into AI companies. Every advertiser is using subsidized AI tools to generate hyper specific adverts. If this all goes south, who knows how advertising spend will be impacted.
Google specifically are backstopping billions in data centre build out costs. They’ve committed to spending, like, all of their cash to data centres. If the market gets nervous and funding disappears, Google are deep in the hole.
Anthropic “invested” $50bn in data centers to be built by Fluidstack who raised a billion dollars from Situational Awareness who used their Anthropic ownership to raise money to fund these investments. Google are backstopping much of the Fluidstack build out, i.e: if Fluidstack goes out of business then Google is on the hook for $10bn+ in costs. And Google’s Anthropic investment makes up like $100bn on the balance sheet. So, Anthropic fails to live up to expectations and fails to pay Fluidstack who can’t pay their suppliers which puts Google on the hook to hand over tens of billions in cash while at the same time their biggest investment is going down the pan.
The top line numbers don’t really do justice to the scale of the risk. You need to look at the long term commitments they’re making.
He didnt mention EZs claims about lack of data center construction compared to projected growth and valuation. I wonder if that was substanciated, since it overlaps with the bubble portrait of the "coming" wall of due service contracts hitting in 2027.
I don’t really care of anyone’s predictions, whether that of Altman or Zitron. I can make a prediction that sun will collapse into itself and stop shining. I would probably be right as long as I don’t give any too strict timeframe to ky prediction. In terms of Zitron, his style is that of a British tabloid columnist. It’s rather refreshing when most tech journalism is just selling gadgets, stock or whatever without questioning at all what either Musk, Altman, Amodei or whoever says. It aggravates many people because, well, it is suppose to.
Regardless of whether you love LLM’s as technology, the financial realities of Anthropic and especially OpenAI really does not look good. They have a massive expenditure that they need to keep going in order to make profits, which at least in terms of OpenAI are horrendously behind. Zitron published these numbers together with Financial Times, so you gotta give him that at least. Meanwhile the CEO’s talk all kind of nonsense and give their own predictions to get more investors money to fund what might or might not be the biggest bubble in the history of finance. I certainly do not hope this happens, since the consequences would be horrific. But there is likely to be a some sort of correction in horizon, since the models will plateau and they will run out of money at some point.
Let me finish with my own prediction. I think a lot of people are going to lose a lot of money some time next couple of years.
If we sample from Zitron’s claims, a lot of them are wrong. Probably most of them.
I think his contribution to the discourse is the bigger picture. These companies are going into potentially economy-wrecking debt over a speculative future that looks much foggier than the last two previous technological booms.
I've come to see Ed Zitron's dramatic predictions as reminiscent of a trend I noticed on YouTube a while back;
Whenever you'd look up anything pertaining to China's future, you'd inevitably find your screen plastered wall to wall with thumbnails of a photoshopped Xi Jinping, tears streaming down his face, next to large impact font text reading "CHINA WILL COLLAPSE IN X DAYS", with X varying from 1 to 30. Much like Ed Zitron's predictions, these events obviously never occur.
I find it ironic, that one of the most memorable articles Dan Luu has written imo is about how futurists faked 'exponential scaling' about semiconductors, and we ran out of the 'good kind' of scaling, Dennard scaling a while ago, and people interested in maintaining the narrative have been making up marketing numbers, which are believable to outsiders, but not to those who know:
Yet, in this case, he takes the marketing numbers at face value, not being an expert in AI financing, while those who know more, can spot the sleight of hand, just like he can when it comes to semiconductors.
I don't think Zitron is wrong, exactly. He's just early. There are a lot of analysts who have faced the same criticism over the past 10-15 years. IMO the issue is that they fail to understand the staggering size and scope of the government fiscal + monetary interventions across those years. Essentially, the government has jammed all the risk into the future to repeatedly rescue near-term results.
I think something similar is happening with e.g. Amodei's predictions of mass unemployment due to AI. It won't happen in the immediate term, because deficit spending removes the economic incentive for firms to pare down their workforces.
All that said, I don't think these people are "wrong," per se. They're just early. When the sh*t hits the fan on all this, it's going to be a big problem. And, for example, companies whose primary business is collecting money for Internet ads will come face to face with the reality of how low value their products are. I have some insight into this, as I work for such a firm, and I know the true extent of the bot traffic out there.
- "artificial intelligence has three quarters to prove itself before the apocalypse comes" — Mar 2024
- "If OpenAI doesn’t either reduce their $8.5bn operating costs to $1bn or less and raise at least $5bn in the next year, they will die." — Jul 2024 2025 costs: $34B
- Generative AI “isn’t getting much more efficient” (Jul 2024 ). OpenAI’s frontier-model API price fell from $30/$60 per million input/output tokens for GPT-4 to $4/$20 for GPT-5.6 Sol, alongside major capability gains.
- “I would be shocked if [Musk’s] wealth doesn’t return to something more like he had in 2019 or 2020” (Dec 2022 ). Musk is now worth approximately $873 billion , several times his wealth when Zitron wrote this.
The actual quote and topic is far different than you’ve portrayed it. Here’s the actual quote: “ yet the company says that it expects to make $11.6 billion in 2025 and *$100 billion by 2029*, a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud.” from https://www.wheresyoured.at/oai-business/
He goes on to specifically discuss how unrealistic $100B by 2029 is given that OAI is structurally unprofitable.
The fact that you’re skewing your misinterpretation of what he said so much shows your own bias I’m afraid.
I think it's fair to call his specific predictions "early." I'm saying his timelines are too short. Like almost all bearish market commentators, he doesn't understand the scope of the government stimulus. This is a systemic problem in market commentary. But, don't kid yourself. If the US stops massive deficit spending, a lot of what Zitron's saying moves forward on the timeline.
It's not government stimulus driving this. It's that when you start with a "successful" company, the financial consequences of bad decisions or bad leadership can take a long time to have a negative effect, if at all, because financial success has a momentum to it.
I left Microsoft during the windows 8 cycle in large part because I could tell nobody knew what the hell they were doing, which is an objectively true statement about the time and place. My dad happened to buy Microsoft stock at that same time and did very well with it.
That's the paradoxical problem that I think all big tech has. Poor decisions by incompetent people, met with inexplicable financial success.
A prediction definitionally includes an outcome, and it _can_ include a timeline. (if you’re serious about your forecasting, then you generally include a timeline; forecasting is non-actionable if it does not include a timeline).
You might choose a different timeline for Ed’s outcomes. Okay: those are now your predictions, not his.
Zitron has done us the favor of including timelines with his predictions, so that Dan can invalidate almost all of them.
Would you say the 2012 apocalypse doomsayers were correct but just "early"? After all the sun exploding in a billion years will ultimately prove them correct.
The US can safely reduce its deficit spending by $1 trillion and absolutely nothing big will happen.
The US typically adds that much annual GDP every 16-24 months at this point. The notion that somehow the gigantic ~$31 trillion economy will fall apart if the outsized deficits don't continue, is very absurd.
The exact same things were said of the Bush deficits. The US economy was supposedly dead in 2009-2010. Here in 2026 the economy is 50% larger inflation adjusted and it has left most of Europe in the dust. The housing bubble contagion was much worse than anything we're sitting on now with AI spend.
Why do I say $1 trillion instead of $2 trillion? There are plausible scenarios where increased taxes bring down the deficits (the Dems will take the House + Senate + Presidency, we'll see how much taxes go up), there's no plausible scenario where the deficits go away completely.
> OpenAI’s frontier-model API price fell from $30/$60 per million input/output tokens for GPT-4 to $4/$20 for GPT-5.6 Sol, alongside major capability gains.
on this specific point: tokens aren't fungible between models right? Like the argument Zitron makes is that improvements in output are due to, glibly, using more tokens to get there. We see people turn on new models and instantly use up all their tokens.
Like the actual measure is more something like "for this specific task, did it cost less now to do it than it did 3 years ago with these AI pipelines" right? The token pricing isn't actually relevant in that discussion.
If you're saying that OpenAI forecast something and you're saying it's validation that the numbers match the forecast, I don't think you're really paying attention to the problems (with annualised run rate bullshit when these are proper companies who could be publishing proper numbers), with unclear financials that are designed to look good, etc.
The whole point of making predictions is timing. I can tell you the US dollar will continue to devalue (a 100% accurate prediction). But it's a worthless statement unless I can tell you when and how much.
"I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be."
This was said in February 2024. This is months before GPT-4o released. GPT 4.5 was released a year later.
I don't know anyone holding on to models of GPT 4.5 caliber, yet know 4o.
ChatGPT 4o and 4.5 score 8 and 14 points on Artificial Analysis benchmarks. [1]
For perspective, Qwen 3.6 27B, which can be ran on single GPU setups, scores 3-5x that on modern benchmarks.
I don't know why anyone would even make a claim like that in the first place. It's like saying "Computers are never going to get faster". I feel like we could run out of sand and still have faster machines over time. Just a silly thing to say.
> I don't think Zitron is wrong, exactly. He's just early.
By that metric, so was Nostradamus. The apocalypse is coming for sure, we're just quibbling about the timeline.
Realistically, timing is everything. You don't need to get it precisely right, but you also don't get a pass if you, for example, keep predicting an imminent recession through a decade of unprecedented growth.
After looking at Nvidia's orderbook, it's a reasonable conclusion that nothing bad will happen for at least another year. In which case Ed Zitron is off by at least a year.
But there are enough signs of trouble that could happen soon: Oracle debt is junk. OpenAI might not be on a viable trajectory to IPO. One or both of those could collapse the lower quality data center companies. Zitron is probably overconfident about a crash in the short term. Probably.
> After looking at Nvidia's orderbook, it's a reasonable conclusion that nothing bad will happen for at least another year. In which case Ed Zitron is off by at least a year.
Zitron is fairly clear that nothing is going to happen for a year or so — he says himself that he thinks there's another round of funding possible for both OpenAI and Anthropic.
Right, but you know the thing. The market can stay irrational longer than you can stay solvent. Predicting the medium future is hardest.
Markets don't just pre-plan their behaviour three years earlier and act it out lock-step. Other circumstances can change. By now, the world's financial press has covered some of the scariest aspects of this, and the situation has evolved.
There are other moves (the OpenAI/Blackrock AI debt securitization idea for one) that could delay it even further.
Zitron, I get the impression, has moved on to talking about the horsemen of the bubble apocalypse — talking about banner events that would need to happen for his predictions to be true. This is safer ground for a forecaster, because every forecast affects the future.
His shorter term predictions have not all failed by any means: he described Oracle's woes before the ratings agency downgraded them specifically because of OpenAI.
But most of his predictions will be irrelevant if the insane securitization plan happens. Because it will stop being about an AI bubble then; the worst risk will be the collapse of the entire US economy. It will need a different kind of analyst.
Me, I don't really care either way. I'm not on the cloud AI hype train, I don't work for a YC company, I'm not an American taxpayer so I will not be directly on the hook, and as Americans like to point out, the UK economy is behind on the whole AI thing so (unlike Ireland, which the USA will 100% leave to fail) we are ironically insulated. Maybe a couple of small British investment banks will fail and a pension fund or two will default.
For the most part we'll just watch the flames.
I do enjoy watching a Brit — albeit an ex-pat — upset a bunch of po-faced AI evangelists. It’s like “Itanic” all over again.
I think he is directionally correct. My own impression is that the bubble will burst at the worst time, and so my assessment is that, given the way this is entangled with the functioning of the USA as an economic power and with the future of the US political hard right, it will therefore darkly but poetically burst sometime around Labor Day 2028, which is the worst possible time.
I agree he is directionally correct, or at least is a vessel to raise important points and valid criticisms.
But predictions need to be specific and falsifable. If not, its just rag-chewing over a beer (luv that shit, but i aint predicting on taco tuesday). If they arent falsifable, then its not a prediction.
I think a lot of the HN comments generally can be described as one camp which cares about and enforces the rigor of predictions and trying to direct limited ear-time to voices which tend to get predictions right, vs the other camp that puts more weight towards directional accuracy.
Why would one ever predict anything at all if it was always falsifiable? Do you mean like eventually falsifiable? Like, I don't know about you, but I tend to go ahead and do any falsifying of something first if possible, before I resort to predicting.
Can you give an example of what a good/proper prediction might be, even in a hypothetical universe, in this schema? Does one "predict" when they play blackjack? Or is there a different concept for that kind of thing?
Falsifiable means able to be correct or incorrect. So if i said that my stepmom was kinda whelp, that wouldnt be falsifable, because like what does that even mean. But if I said my stepmom is going to be on her third marriage by the end of the decade, that is, because in 2030 someone can yell at me either way.
This is a spectrum of course: a prediction that OAI will collapse is probably right as _eventually_ all companies come to an end, but under that interpretation, the prediction is useless. It's more signal / useful / falsifable to say OAI is going to collapse around/at <year> due to <thesis>.
Anyway thats my two cents. Its fine to outline forces and trends, but when you make predictions there are useful (better, falsifiable) and useless.
I honestly don’t understand why you care so much about the “rigor of predictions”. Short-term predictions are almost always at least somewhat inaccurate, no matter who’s doing the predicting. Directional accuracy strikes me as far more important.
Take a look at the thread below yours, but basically if the prediction has to be wishy-washy or just interpreted as 'direction', theres way more noise and way less signal. Why not just state the underlying trend/forces instead? Why lean into the online culture of predictions and do it badly.
Bad (form) prediction: OAI is gonna be wobbly in a bit
Good (form) prediction (could be totally wrong): OAI as we know it today is going to collapse due to running out of money around/at 20xx.
And sure we can be pedantic about detail, but the litmus test is: is the prediction useful if you had a crystal ball and you could know if it was true/false a priori?
Who cares about predictions to this extent? They’re practically always incorrect or flawed in some way, and most people understand and accept that. No need to be so neurotic about it.
That’s the crux of it!! You don’t have to agree but people do care, and I think (ignoring the obvious partisans) that’s the two dominant camps of commenters on this thread.
One pony’s trash is another pony’s treasure, so I guess here one persons pedanticism is another persons hobby.
Oracle fits in Nvidia's pocket at this point: $67b sales, $22b op income.
Vs of course Nvidia: $302b sales, $197b op income.
Oracle was never as big of a deal as that brief market cap run implied. The herd pushed it up for no reason.
The comparison to Apple, Microsoft, Google and Amazon are pretty similar. Oracle fits in their pockets too. Who cares if their debt is junk. Ellison has nearly wrecked that ship on numerous occasions over the decades. He went on an elaborate acquisition binge in the previous epoch, buying his way to the next stage (preventing Oracle from being market-eliminated, or acquired), and that was an incredible mess that took a long time to sort. He's doing the same move now, trying to spend to stay on the board as the world rapidly changes under his feet.
Non-rhetorical answer to your rhetorical question, but:
The near future of the political right wing of the USA is dependent on the Ellisons staying afloat to create an impervious right-wing media sphere that would survive the end of Fox.
The Paramount-Skydance/Warner merger is now delayed until 2027. Trump/the GOP needs that merger to go ahead, but if Larry's debt position worsens it really might not.
So you can expect the executive branch to push for the USA to backstop Oracle's debt in some way, whether directly or indirectly (taking some sort of stake in OpenAI to allow it to guarantee Oracle gets most of its money, for example — anything to get the credit rating back up).
It will be the first stage of this becoming a problem for the American taxpayer.
You can make that claim for the general case that genAI capabilities will plateau or fishy financing in the sector will cause trouble at some point, but not for the specific talking heads that haven't constrained themselves to that sort of "broad future trajectory" prediction.
FTA:
> Note that I didn't attempt to catalogue statements that are nonsensical or were simply factually incorrect statements at the time, such as his December 2024 claim that “Generative AI's products have effectively been trapped in amber for over a year.” January 2026 claim that "[models are] basically the same as they were a year ago. They have the same efficacy". Zitron has not only made forward-looking statements that AI capabilities will not improve, he's also consistently made backwards-looking statements that capabilities have not improved which, while obviously false at the time, seem to play well to his base (along with his other false statements). If you connect all his statements together, it's implied that AI had the same capabilities in January 2026 as they did in December 2023 (and if you connect later statements, it's actually implied that capabilities in August 2026 are the same as in December 2023, though to be fair to Zitron he frequently contradicts himself and has also admitted to limited improvement at times).
Yes. I was specifically referring to Zitron's circular-financing complaints. I can't defend his separate claims that AI just isn't that useful. If he were involved in the tech industry, he'd know how preposterous those claims are.
What predictions would you say he is not wrong, but just early about?
If his issue is that he is accurate on something shady going on with the finances of AI companies but the effects are mitigated due to government intervention, he should say.
Your explanation gives him more credit than I think he deserves. He has been unambiguously incorrect many times over the past years in the time scales over which he makes predictions.
In general, claiming that a prediction is just early in an unfalsifiable claim. It allows no admission of being incorrect whether you are correct or incorrect in a given moment. If you are right, then good, you've made a correct claim. If you're wrong, just claim there are clandestine corrective forces keeping the disaster you are predicting at bay. Either way you make it out clean and still have some sense of legitimacy.
Not sure about being early when it comes to points about models reaching the peak of their capability. Honestly, I don't understand how he's qualified (in terms of knowledge) to make such claims.
Being wrong about when a financial bubble will burst is different than being wrong that there is a financial bubble. That's the question, because if AI is driving a bubble, then it will burst at some point.
"Early" works for an open-ended bubble thesis. It does not rescue dated claims that already failed.
Google's 500 million Gemini-user goal had an end-of-2025 deadline. Zitron called it so unrealistic that Sundar Pichai should be fired. Google reported more than 650 million monthly users by October.
"AI had already peaked" is also a claim about the state of the technology at that time. Agent and coding benchmarks moved sharply after it. The fact that every technology eventually peaks does not make a past claim that it already peaked correct.
The bubble may still burst. That would validate the bubble thesis. It would not retroactively fix the prediction record.
btw Zitron has the only fan base that has come after me with doxxing and death threats so far. Truly misery loves company!
Some numbers have a lot of squish to them. Gemini can't be called a failure. But Copilot is a flop and yet Microsoft can probably show you similar numbers to what Gemini has.
But we’re talking about Gemini, which is one of Dan’s point: the surface area is so large that any prediction is almost laughable. Zitron’s prediction here is laughable in fact because he claims both (1) Pichai is jamming AI everywhere and (2) the 500M number is impossible. Those statements are immediately contradictory to anyone who understands the scale of Google’s products.
> The bubble may still burst. That would validate the bubble thesis. It would not retroactively fix the prediction record.
If it does not burst it will be because specific efforts have been taken to deflate it in the face of concerns like those he is raising.
The bubble may not burst for example if the securitization of AI debt really happens. Then when it happens it won't be an "AI bubble" that bursts, it will be a full-on collapse of the US economy. Like when 2008 happened it wasn't really about mortgages anymore.
Macrofinance expert Nathan Tankus has an excellent post on why the financing situation around the AI boom is just not big enough to mess up the financial system.
I agree that the specific amounts invested in AI aren't enough to cause a calamity directly.
The problem is you have the vise of a stock-market decline on one side (something basically everyone thinks is impossible), and AI-induced unemployment on the other side (something a lot of commentators, including Zitron sometimes, seem to think won't happen). Those two things in tandem would be worse than 2009 by a multiple. I doubt the US government will be able to bail it out.
I recall a time when Google was struggling to monetize ads and then something changed and they started becoming profitable. The narrative was about improved targeting.
I think it might have helped a little but I never fully bought this argument. I don't think I've ever bought a product which was advertised to me online and I was using some of these platforms for years. I'm probably a liability to them; using up compute but not clicking on ads or buying anything.
Also when I ran social media ads many years back, I never got any users out of it. It literally seemed like mostly bot traffic back then; I can't imagine how bad the situation would be now with LLMs.
Did you read the post? The author cited very clearly a plethora of very specific predictions made by Zitron that were verifiably and factually wrong. False. Incorrect. Not “early”.
I've been doubting him myself (his recent articles just hedge on data centers more than anything else) but then I want to ask, are there any valid critics of AI? Not a "code is bad but it'll get better" but actual criticism in the nature of the financing, politics, etc. I think separating AI as a tool and it's capabilities and AI as product that needs to make a profit is helpful, however most people are really hedging in one camp or the other in their takes.
Cal Newport has been interesting on the topic. But it’s also possible to read Zitron and skip his personal opinions and just follow the discussion of financing, that’s what I personally do. I don’t understand why anyone would take the commentary of an internet pundit as a set of predictions to evaluate as gospel
I enjoy Newport myself, he's probably the most level-headed take I've come across. Everyone else has some agenda (or product) they're trying to get at and very much ruins the messaging (ex the agent 'civilization' piece is extremely overblown especially since..that's how multi agent systems coordinate already. Nothing happened that is unprecedented and isn't how the system is designed to work.
To shamelessly shill a passion project: A friend of mine and I try to be skeptical-but-reasonable on our podcast https://kairos.fm/muckraikers/ we aggregate papers and reporting and try to contextualize it with our own (hopefully useful) perspectives and takes
> however most people are really hedging in one camp or the other in their takes.
As with most things, most people are somewhere in the middle, as the silent majority. You only see the comments of the strongly aligned, which are also the most emotionally motivated to comment.
The data center growth questions he raised have been where I found him interesting. I could never find any other articles to corroborate his predictions though. My question is when will the AI bubble burst?
I didn't know he'd had a long history of mispredicting AI quality and growth of companies like Microsoft and Google.
>I think separating AI as a tool and it's capabilities and AI as product that needs to make a profit is helpful, however most people are really hedging in one camp or the other in their takes.
There are a myriad of people out there who have brought up genuine issues that AI presents, or preexisting issues that AI is exacerbating.
This series of articles is perhaps the best long form critique of AI as both a technology and an industry I've encountered [1].
Water usage, sure. But emissions has plenty of reasonable concern.
There are the various xAI data centers have/are running using mobile gas turbines.
In general, the extreme amount of power is going to put pressure on the grids. I hope this leads to the world doubling down on renewables to offset it all, but is that going to happen? Hell, the US actively paid [0] to stop a turbine project.
Water usage may be a drop in the bucket nationally, but they tend to put datacenters in areas without much water (often because evaporative cooling is less expensive in arid regions) and the effects to those local water supplies can be extreme.
These companies subsidizing green energy expansion, because it's now the cheapest power to expand.
These companies are going to help "correct" the widespread problem with utility monopolies, in the US. Datacenters are deploying their own power generation, partly because power cost no longer aligns with power generation costs. This mismatch is motivating research into local nuclear power generation [1] (which is almost certainly an effort to force the monopolies, rather than actually deploy).
> These companies subsidizing green energy expansion, because it's now the cheapest power to expand.
Unless you consider natural gass green energy, it's quite the opposite for the moment. This is because the AI build-out is about speed, not cost-effectiveness. That is why xai's Colossus I & II were illegally running gas turbines, and Google recanted its pledge for data center renewables targets.
This point is about power generation companies accommodating the new power demand. It's true that the power companies are keeping coal and gas peaker plants running, that they planned to retire. But, actual additions are all green [1].
And, step functions are inefficient, always, so "for the moment" isn't so unreasonable. Dataceners are something like 100 million tonnes of CO2 per year, where cars are 1,800! So, this isn't some world ending emissions, within this moment. Everything is trending green. Why? Because it's cheaper (thank you China).
Xai using gas turbines is closer to my second point of side-stepping monopolies (improperly in that case), but is also just one example. See previous link for very long term, and all the datacenters using green energy, mid term.
Everyone will do what's cheapest. Luckily, China has made that solar power. We just need to get the monopolies off their asses, and put some of their record profits into actual power expansion. Lucky for them, everyone blames the data centers for all of this. Where I am, the single power company has already raised rates so much, in preparation for electric, that it's more expensive to fast charge an electric car at noon than to buy gas, with a planned 10% increase over the next few years. So, they're dodging criticism too!
Here's what I find invalid about environment angle.
I fundamentally don't think it is wrong to increase emissions as long as you consider the tradeoffs and externalities. Every single action you do in life has externalities - if you start opposing all of them then what really is your point? You just hate people doing stuff.
If you think emissions are so harmful, try putting a number to it. I implore you to do the exercise and convince yourself or me or others and suggest that the pros don't outweigh the cons. I'm half predicting that the conversation will end in dubious claims about tail risks and world itself collapsing (I hope you don't do that).
I don't think AI is uniquely harmful for the environment given the value it provides. Hell, it can even contribute to accelerating renewable resources and increasing efficiencies overall. There's way more to lose by slowing down AI because of emission control than to gain by reducing emissions.
> There's way more to lose by slowing down AI because of emission control than to gain by reducing emissions.
If AI works out as proponents would make you believe, then either you'll see masses of people out of a job - for which society is unprepared. Or you'll see a big, society-wide productivity boost. Read: consuming non-renewable resources on this planet even faster (not just energy).
Society as a whole would benefit if rollout would slow down. Give us time to reflect on those 2nd-order effects & how to address them. But instead we have the opposite: a crazy race with big AI labs trying to out-spend & out-do the other guy, ignoring externalities everywhere.
You are making claims for why you think the emissions are worth it but I don't see how this makes concerns about emissions invalid. Even water usage, while blown out of proportion, can be a rational concern if you have a fossil fuel power station.
You can just flip this around and ask why is slowing down AI to control emissions harmful? What numbers that don't make tail risk claims are you providing for this?
wait, please stick to the argument. Why is increasing emissions bad while considering tradeoffs?
>You can just flip this around and ask why is slowing down AI to control emissions harmful? What numbers that don't make tail risk claims are you providing for this?
Slowing down reduces the value it provides to humans, that's clear to me and you I hope.
>Why is increasing emissions bad while considering tradeoffs?
Because climate change stands to be the biggest market failure in history. You need to show that the rapid scale out of data centers is going to reasonably offset the current trajectory we're on.
I think the three valid criticisms you listed are valid, but there are other quite a few other IMO-valid criticisms of AI. Here are a few as I see them:
- AI centralizes power in the hands of capital, rendering those who can afford compute hardware vastly more capable than those who cannot and thus increasing social stratification
- AI is generally trained on the creative output of humanity without those who train it giving back proportionally (copyright "rules for thee, not for me")
- AI breaks social processes built around the idea that TRYING something is inherently a cost in time or effort, such as filing a legal claim or sending someone a threatening letter. We haven't made the social changes to punish or charge people for using every appeal/option/application, so this makes asymmetric-effort tasks like applying for a job really bad in the interim
- AI use makes it harder to develop the ability to critically think for yourself, especially among those who most need to develop that ability
- AI produces large amounts of mid-tier content, making it harder to discover exceptional human-created creative content produced after AI started to exist
- AI leads to distrust in remote communication, increasing cynicism and breaking social bonds generally. This is NOT your point about "AI spreads misinformation" - no matter whether it's true or not that AI can be used to produce misinformation, having people doubt each other is a harm
- AI demand crunches hardware and time availability for other adjacent markets, such as computer gaming, construction, 3D graphics production, etc. This harms both hobbies and professions in those fields having to cope with rising prices and lower availability of materials
- Everyone is using the same or similar AI, leading to a homogenization of culture and process across humanity. This is perhaps a mixed blessing, because humans are capricious, but less variety can be viewed as a harm
I will also say I personally hate seeing "job loss" said to mean "wealth loss" or "people starving". The goal of life isn't to have a job, it's to be well and happy. If you can be well and happy without a job, great, so it's really painful to me how people don't even see those things are not the same.
> - AI centralizes power in the hands of capital, rendering those who can afford compute hardware vastly more capable than those who cannot and thus increasing social stratification
Looks to me like I can run Claude Code without being able to afford my own datacenter.
> - AI produces large amounts of mid-tier content, making it harder to discover exceptional human-created creative content produced after AI started to exist
That it does, but I think the real social evil is bad recommender systems. eg YouTube is basically on a mission to drive me insane because it literally only recommends me a) reviews of espresso machines b) video essays by autistic people about Mario 64 c) PBS scienceslop about how quantum physics is super mysterious. None of these are even what I watch, but they're also not what I want to watch.
> Looks to me like I can run Claude Code without being able to afford my own datacenter.
Until Anthropic bans you from using their data centers, at which point you cannot run Claude Code at all. Welcome to being a have-not (at least in a world where only genAI-assisted coding is acceptable).
Whether Claude is or is not available via AWS Bedrock is entirely decided by Anthropic, not by you and not by Amazon. And you can't buy the data sets (the REAL power...) from any AI company.
Those are two very different things, and the former should be a serious concern. If AI does indeed become a double-digit percentage of electricity usage as the AI labs themselves predict, then it becomes a significant contributor to emissions, full stop.
Basically, all criticism of issues that affect real people is invalid per you.
> environmental like emissions and water usage
There is real crisis with warming this year, yes the plan to consume staggering anounts of energy and make environment worst in the process is valid criticism.
> AI is useless and it will take the economy with it because it is a bubble
If it turns out to be true, a lot of innocent people get hurt. Valid.
> AI spreads misinformation and causes societal damage
As valid as criticism of facebook was valid the whole time. And yes, facebook made world into worst place.
> AI is trained on copyright (are we really on this side of the debate ?!)
100% valid.
> safety critics who think AI can take over the world
Not valid, that is bullshit. If you think the word is wrong suggest polite word that says the same.
I found this in two minutes via a search engine, but the star blogger Dan Luu apparently cannot handle that. I'm not a regular Zitron reader, but incidentally this blog post that came up in the search is several levels above Luu's post.
> Although Zitron's past predictions have generally been wrong, maybe he'll be right about something in the future. Perhaps some of these companies will have valuations decline for some reason. But, even if there's some kind of massive AI crash and OpenAI and Anthropic go to zero, in terms of the societal impact, if on top of that, some other event occurs that prevents further progress in models beyond whatever AI labs have internally right now, that's still going to result in a fair amount of change. Which companies are successful will change who gets rich, but particular companies failing won't stop changes that fall out of current or next generation model capabilities from happening; it just moves around who benefits the most.
> If Zitron ends up being right about some company or other collapsing, that's pretty uninteresting to me compared to how capabilities have developed and will develop, where he's been wrong to date. It also happens that he's been wrong about the financial predictions he's made to date, but that doesn't really interest me, though I included a number of financial predictions for completeness.
Not sure how you can "get the big picture right" while having many egregiously wrong predictions.
So your guru Luu preemptively excludes evidence and you follow him? I'm not going to fact check all purported refutations from that blowhard Luu either.
You made a poor characterization of the content of the post and were rebutted with direct quotes. It happens, thats okay! Its not an attack on your character. There's no need to feel defensive!
Agree. Even Zitron's predictions about AI peaking are arguably correct if you step outside the silicon valley bubble. People I know who don't work in tech who use AI at work are doing the same stuff they were a couple years ago: they use it to summarize emails, generate an occasional slide deck, and mostly just send workslop to their coworkers.
And for personal use, I can count on a single hand people I know who pay for an AI subscription, and of those people nobody pays for more than the $20/month plan. And they all just use it as search or maybe to vibecode some one-off party game they use once and then throw away.
I don't know a single person who has done something like run Openclaw or leaves coding agents running on their laptop open all day.
I don't like Ed, but it seems that Luu spends far more attention documenting failed predictions than checking other predictions that might have been correct.
Telling me that quite a few of Zitron's predictions turned out to be accurate, while many others were completely off base, means he's throwing darts on a dartboard. Why should I listen to him?
I'm sure I can make a lot of accurate predictions. It doesn't mean I'm worth listening to, if people can't distinguish the accurate from the inaccurate in the moment.
Reminds me of a tactic I've seen often amongst both critics and shills on fads. An OpenClaw fanatic on Youtube comes to mind. He makes opposing claims in different videos. One of them has to turn out to be true, and he trumpets his successes ("Look, I predicted this!"). Only a few notice he also predicted the opposite.
Just look at the other thread about Zitron and his Enron comparisons.
What predictions have Ed made that were correct? And how do they weigh against the incorrect ones, in terms of both quantity and quality?
That's relevant because if you make a thousand predictions, a few of them might turn out to be true. That doesn't mean you're good at making accurate predictions.
Side-bar: I once hired Ed for PR for my startup. He was very difficult to work with, not even willing to share how he pitched our startup to publications because he considered the pitch his IP. So it was hard to know what was resonating or not.
I share this less to take a shot at Ed but more so that you all know to ask this if you ever hire a PR person.
This kind of back and forth reminds me of the Dot Com bubble circa 1999. There were endless articles saying that the internet was a new golden era for mankind and that the hyperbolic company valuations were justified; the detractors cried bullocks.
I use AI every day as I assume everyone else on Hacker News does. Will the S&P 500 drop 20%? I have no idea. If you know, please let me know so I can adjust by 401K.
Looking at the refutations of Zitrons predictions in TFA, it boils down to two categories:
1. Zitron claims model capability has peaked
2. Zitron claims AI lab growth (user and revenue) has stalled.
In the first case, TFA refutes by claiming 'wrong' repeatedly, which does not convince me of anything. If anything, Zitron is probably right in this regard, since the majority of progress in recent LLM tech has been setting up of guardrails to cajole the models using 'agents'.
In the second case, numbers are given showing growth, directly refuting Zitron. However, I'm giving Zitron the benefit of the doubt, given the old saying - market can remain irrational far longer than you can remain solvent. As long as people can be convinced that the sky is falling, rational predictions rarely pan out.
What’s particularly bad about Zitron is his financial analysis. Some people have the idea in their heads that “yeah, Zitron is wrong about a lot of things, but his economic data and analysis is tight.” That couldn’t be further from the truth.
The entire AI industry, especially the vested interests, are often full of shit, sure, but the sheer amount of misunderstanding that has surrounded the economy and its relation to AI has been mind boggling. There is much bologna being accepted as reasonable or even standard by HN comment sections.
I was skeptical of LLMs making it to where we have them today, but the test results are evident, empirical, and hold up to hard scrutiny. I remain quite skeptical of a singularity event, GAI, and anything beyond what we've seen LLMs output today. It will get faster, cheaper, but not much smarter without another breakthrough. They will not be able to save the planet from their own pollution and overconsumption.
Danluu claims Ray Kurzweil's predictions are wrong. I asked
> list 50 predictions by Ray Kurzweil that he made before 2005, the date he made the prediction, and whether to not his prediction was correct. If it was correct, give some proof.
Of the 50 that were listed, 43 were correct, 7 incorrect.
Cannot take profits of these companies seriously when they have been laying off employees by the droves the past couple of years. Obviously profits will increase when workforce expenses have reduced. I'll only take it seriously after a couple more years and see how the company has held up with massively reduced workforce (powered by AI™). Another point would be to see how these incumbents get challenged by new startups and if incumbents can survive this phase.
I would be interested in seeing a similar list of predictions from Altman, Amodei, etc with annotations about how many have come true. Ed Zitron is a blow hard and frequently overstates things to the point where it is hard to take seriously, but so are the AI industry leaders.
I have heard multiple breathless press releases warning that the end of white collar work is "just 6 months away" and that people not using the latest Mythos/Fable/Whatever model will be hopelessly left behind.
Dan Luu's piece talks about this! He gives the example of Ray Kurzweil, who is similarly catastrophically wrong about everything, just in the opposite direction as Zitron. Luu's point isn't that anti-AI analysis is bad; it's that Zitron is bad. Zitron is bad in this analysis no matter what Altman says. It could be the case that Altman is also bad.
I'm convinced all of Kurzweil's predictions through the years can be simplified as (and originate from) "whatever least-implausible dream scenario allows a man of Ray Kurzweil's exact age and health to barely avoid the hitherto-universal icy grip of mortality."
Tangentially related in terms of "old stuff from other things I read", this 2006 critique [0] by Derek Lowe:
> Later in Kurzweil's article, he says:
> > "So what does the future hold? By 2019, we will largely overcome the major diseases that kill 95 percent of us in the developed world, and we will be dramatically slowing and reversing the dozen or so processes that underlie aging."
> [...] I really do expect to put cancer, heart disease, the major infections, and the degenerative disorders in their place. But do I expect to do it by 20-flipping-19?
It's hard to be optimistic when it's been those 13 years plus another 7 and somehow measles is back again, although I admit that's one isn't a pure technology-problem.
But that's kinda the point, there's no such thing as "a pure technology-problem". I think that's the fundamental - and obvious - thing that these folks seem to constantly miss.
Reading through them, Luu's grades seem fair and accurate to me. Best defense of Kurzweil I can give is that if you give a grace period of a decade and scope them down substantially (to maybe a subset of well-off Americans in coastal cities), he looks much better, though still under 50%.
One of Kurzweil's close-but-no-cigar failed predictions was "neural nets and genetic algorithms," killed off by the conjunction and being a couple years too early (2009 for increasing interest, and 2019 for wide use).
Fair, sure. But it seems to be underselling how reasonable Kurzweil is.
We've got things like 2009 - "Computers can recognize their owner's face from a picture or video. No." And ok, sure, but that has happened by 2026 and we have more than 2000 years of recorded history of people making predictions.
I don't think that situation reflects at all badly on Kurzweil except that he doesn't explicitly say he has a 15 year error bar. Which, yes, technically inaccurate, but it seems quite likely nobody would be talking about him if he spent that much time exploring the minor caveats.
And hitting him for the "and genetic algorithms" is verging on pedantry. Ok so genetic algorithms aren't a civilisation-level success that appears to be reshaping the fate of the species in the same way neural nets are. He was right that learning systems were going to be huge and he was off on a detail.
The list in the appendix is pretty telling: Yes, the moments are off by a lot, but many of the predictions describe reality well.
I'd say that 7% accuracy is on the low side and 86% on the high side. Looking through the list I'd put it more at 50-60% personally. For me that still means that I'd much rather hear about what he has to say about the potential future than most other people.
If you grade what was linked by whether it is "approximately achievable today", and not some less interesting metric like being predicted for the correct year or if it was outcompeted by some other thing, he's closer to 70-90% depending on how close you're willing to grade.
It's very easy to say 'person X made a highly specific testable prediction, while respectable people said nothing like it would ever happen, and it only 90% happened, so person X was a fool unlike all the respectable people', but it's a trap. In reality Kurzweil was directionally correct about most things, overspecified the details, and had optimistic timelines in the way that everyone has optimistic timelines about everything.
Altman and Zitron are like pro wrestlers. Their speech acts aren't for truth, they're for some spectacular effect on your feelings and your imagination that keeps you coming back for more.
I encourage anyone interested in this to read On Bullshit by Harry Frankfurt, the best popular philosophy work in a long time.
Ed Zitrons wild claims might be for entertainment value, but Altman’s are for his own valuation. He’s bringing in hundreds of billions of dollars off those claims.
Without reference to either person, I think this is essentially a misunderstanding of Frankfurt’s analysis: On Bullshit is about expressing sentiments without caring about their truth value, i.e. the concept of a “bull session.”
Both Altman and Zitron are the opposite of Frankfurt’s bullshitter, because they both appear to evince genuine care for the truth value of their position.
(Frankfurt is very subtle about this, in that he distinguishes the kind of performative lying you’re suggesting as distinct in moral and rhetorical content from bullshitting. The liar wants you to believe a specific thing; the bullshitter wants to regale you.)
Bullshitting is where you don't care about whether what you say is true. Your goal is to influence a certain way of thinking or feeling, and you just say stuff that you think will cause that in other people. Appearing to care about truth is not opposed to that, it's part of it.
I don’t think these mental states are in evidence for either of them. I think they’re both credibly earnest in their views.
(Frankfurt’s characterization of the bullshitter rests on not just the truth value being absent, but also on the bullshitter’s misrepresentation of what he’s “up to.” I don’t feel that either Zitron or Altman is misrepresenting what they’re getting up to.)
I mean, the point of Frankfurt’s bullshitter is that we know they’re bullshitting (or more expansively, Frankfurt gives us a set of criteria to test them against). We know they don’t care about the truth value of their statement, only that they are misrepresenting themselves because of a hidden “enterprise.” But there’s no such unknown enterprise in either’s case, and neither appears to be misrepresenting themselves (to my point about appearing earnest). Maybe that latter part is itself deception, but without the former they would fall into Frankfurt’s classification of a “liar” instead.
(I have to admit a bias when it comes to Frankfurt: I don’t think On Bullshit is that convincing. In particular, I think Frankfurt doesn’t do a good job of motivating the connection between bull sessions and bullshit in his strong sense, and many of his examples - like the Pascal/Wittgenstein one - don’t demonstrate misrepresentation either.)
> Both Altman and Zitron are the opposite of Frankfurt’s bullshitter, because they both appear to evince genuine care for the truth value of their position.
I can't really judge Zitron, but when it comes to Altman, I have absolutely no idea how you arrived at that assessment. In my view, he's clearly dishonest. I’ll remind you of his attempt to use government intervention to erect barriers to market entry for his competitors. Or his claims about AGI being just around the corner—claims that haven’t come true so far and were clearly aimed at investors. I’ve never heard a single statement from this man that struck me as honest.
I think it’s appropriate in this day that people have to really shout and lament on and on about their thing just to get a few people to listen and/or consider parts of their argument. Nobody listens if you’re just casually proselytizing your grift.
Kurzweil made one big claim — Singularity around 2045. Everyone at the time thought it was a total joke and hundreds of years off, if even possible. Now, that is seen as a laughably long timeline.
The rest is noise, I don't care what minor predictions he was wrong about, he called the big trend back when nobody else could make a trendline.
The fact that you know Ed Zitron's name means that, regardless of his predictions being consistently wrong (which they are), his strategy for manipulating human attention has been correct.
The question is whether he sincerely believes his own predictions or if he cynically is aware that you can create a career for yourself being a guy who says bombastic clickbait-worthy things people emotionally want to be true, instead of measured assessments of reality.
Problem is, you wouldn't know Ed Zitron's name if every piece he wrote basically said "AI might be a bit overhyped short term but will have lasting economic impacts." Booooorrrring.
The reverse is also true. OpenAI and Anthropic aren't going to get much media attention if they don't make silly claims like "all white collar jobs gone in 2 years."
And no, this isn't a new problem due to "the algorithm." Media has always been like this. Zitron is just another Peter Schiff with younger skin. The problem is human nature in general.
Hence why AI isn't going to kill media. We don't actually want sober, rational assessments of all available information from hyper-intelligent LLMs. This is unsatisfying. We want emotional validation, drama, adversarial identity and spectacle. Truth is rarely what we are seeking.
> his strategy for manipulating human attention has been correct.
"Correct" is not the word you're looking for here. More like "very effective". His strategy for manipulating human attention is very effective, but the correctness of his strategy isn't relevant here, so I'm not sure why you're bringing that up.
> Ed Zitron is a blow hard and frequently overstates things to the point where it is hard to take seriously, but so are the AI industry leaders.
Except that the AI industry leaders actually have skin in the game/are in the trenches and competing in the market. Ed Zitron wants you to subscribe to a newsletter so that you can read doom and gloom and...?
If you invested based on his advice, you'd have missed huge gains and/or lost money.
And I say this as a person who thinks most of the "AI industry leaders" are ethically questionable, at best, and ethically bankrupt, at worst, and that the stock market should be approached with caution due to valuations.
> multiple breathless press releases warning that the end of white collar work is "just 6 months away"
I'd like to see an example of this.
I think Altman and Amodei have been quite sober with their actual predictions. They've said things like "models can now do white collar work" but haven't yet said it is the end of white collar work.
The closest actual quote to this was in In March 2025, Anthropic CEO Dario Amodei told a Council on Foreign Relations audience that AI would be writing 90 percent of code in three to six months, and essentially all of it within twelve months.
I think that he underestimated how long it takes for technology to get uptake but in terms of capabilities he was perhaps 6 months out. I'd say that Fable class models are definitely capable of writing essentially all software, and that was released June 2026.
> In a remarkable interview with Y Combinator in November 2024, Sam Altman, CEO of OpenAI, shared a vision that could redefine the technological landscape as we know it. Altman confidently revealed that OpenAI has a clear roadmap for achieving AGI by 2025.
What specifically was he wrong about in either of those? I.e, something that can be falsified.
> Altman claimed that AGI could be achieved in 2025 during an interview for Y Combinator, declaring that it is now simply an engineering problem. He said things were moving faster than expected and that the path to AGI was "basically clear."
"AGI" isn't a useful term because - as noted in the article you linked - people disagree about what it means. Also his actual claim here seems to have been that the path to AGI was "basically clear."
Whoa, be careful, I think those goalposts just broke the speed of sound.
> Altman claimed that AGI could be achieved in 2025 during an interview for Y Combinator, declaring that it is now simply an engineering problem. He said things were moving faster than expected and that the path to AGI was "basically clear."
He was wrong that AGI was "now simply an engineering problem".
He was wrong that the path to AGI was "basically clear".
And if you want to play definition games and start waving your hands around and accept the claim "oh well actually we don't really know how to define AGI now", then he was wrong to claim that the path to AGI was "basically clear"!
Even if you play that game, it's still simple: either he was wrong about the path being clear, or he was wrong about the destination being clearly definable. That's still being wrong.
> He was wrong that AGI was "now simply an engineering problem".
> He was wrong that the path to AGI was "basically clear".
Why do you say that?
For context, Jensen Huang says:
> "For many tasks, we could say that we’ve already achieved AGI... I think of all of those milestones…they’re kind of senseless at this point.[1]
Even if you disagree with that, Altman's statement seems more about the idea that "more data + more compute + transformer based neural networks" will get us to something called AGI.
I think that statement is true. I guess you don't.
> if you want to play definition games and start waving your hands around and accept the claim "oh well actually we don't really know how to define AGI now", then he was wrong to claim that the path to AGI was "basically clear"!
No - because I think his and Jenson's definition means we have achieved AGI.
So it goes back to my point: this isn't falsifiable.
>> "For many tasks, we could say that we’ve already achieved AGI... I think of all of those milestones…they’re kind of senseless at this point.[1]
This statement is nonsense. It's Artificial General Intelligence that was promised. Not Artificial Some Things Intelligence.
> Even if you disagree with that, Altman's statement seems more about the idea that "more data + more compute + transformer based neural networks" will get us to something called AGI.
His statement was wrong. I don't care what other ideas you want to read into it, he was incorrect about AGI arriving in 2025. That's all there is to it. Twist it into a knot and smear butter on it if you want, wrong is wrong.
> No - because I think his and Jenson's definition means we have achieved AGI
Yeah they can twist definitions all they want. I don't really care. We have seen that LLMs and transformers have not delivered AGI, and they certainly didn't deliver it in 2025.
> His statement was wrong. I don't care what other ideas you want to read into it, he was incorrect about AGI arriving in 2025.
No
Sam Altman never claimed we'd get AGI in 2025. That is Tom's Hardware incorrect headline.
Altman's quote is:
"I felt like we actually know what to do like I think from here to building an AGI will still take a huge amount of work there are some known unknowns but I think we basically know what to go what to go do and it'll take a while it'll be hard but that's tremendously exciting I also think on the product side there's more to figure out but roughly we know what to shoot at and what we want to optimize for that's a really exciting time.."
All in all, it's clearly the AI skeptics that have egg on their faces. Sam Altman is very flawed and you could make a strong argument for why that's why he blew an enormous lead to Anthropic. Dario's predictions in general haven't been that far off. The general public is becoming increasingly aware of AI as a big deal (and something about 60% hates). Our jobs, regardless of where on the adoption curve we are, have undeniably changed a lot.
Zitron and a whole lot of people on HN were trying to claim this was a nothingburger or at least no more important than the invention of IDEs up until Dec 2025, and then all of a sudden everyone quietly shifted what the "reasonable" opinion was. If I were those people, I'd spend more time taking a look at what was wrong with my priors than look outward.
Note that no one ever quotes the end of Dario's line, either, where he said programmers would still be needed in that 12 months. People think the prediction was more extreme than it really was because all the clips didn't include the latter part.
> .... and in 12 months, we might be in a world where the ai is writing essentially all of the code. But the programmer still needs to specify what are the conditions of what you're doing; What is the overall app you're trying to make; What is the overall design decision; How we collaborate with other code that has been written; How do we have some common sense with whether this is a secure design or an insecure design. So as long as there are these small pieces that a programmer has to do, then I think human productivity will actually be enhanced
I think one important distinction is at least they have some humility to admit they were wrong. I think Ed Zitron has rarely, if ever acknowledged he was wrong.
I see this so much. "This shouldn't work, therefore it won't work." It's like the world is imagined to run on a moral causal framework rather than uncaring quantum mechanics.
I have watched many of his screeds; I think he undercuts his thesis with excess bile.
His core observation is that the unit economics of openAI and anthropic don't actually yield enough profit to pay off the huge debts that these two companies have incurred, and that as a result all the debt they've taken on will have to be written off which will trigger "the hyperscalers" to themselves suffer huge losses (likely wounding google and microsoft and destroying oracle).
He is rather more negative about the utility of LLMs than lots of other people (myself included); but his overall view of
1. they're not completely trustworthy
2. they're really expensive to train
3. it isn't obvious that anyone's willing to pay the full freight for the resulting product
4. lots of large orgs "that should know better" have gone far down the LLM "AI" road because they're looking for "the next big thing" when they should be pivoting to "mature, stable" companies instead of "hypergrowth" companies.
5. there's lots of debt and obligations and no obvious way for all of it to be paid off from revenues from openai / anthropic.
seems pretty reasonable. There seem to have been lots of bets placed on the hope that this stuff will continue scaling as it has in the past, if it is given more compute and data, and that bet is one that has yet to have demonstrated itself as correct.
Elsewhere, people have pointed out that many of the "FAANG" companies have shed lots of people and driven lots of profits, largely on the back of internal use of LLM tools. That doesn't necessarily contradict the skepticism that anthropic and openAI will succeed, and given all their obligations, if they fail it'll be a big mess.
But again, big Z doesn't do himself any favors when he rants about "failsons" or whatever.
Seems to me it's a reasonable position that runs face first into the irrational market.
Like they're digging a gigantic hole and Ed's up the top saying if you keep digging the hole will collapse (+ a whole lot of unnecessary swearing), and then a bunch of people jump into the hole to brace it and say "nuh uh, see we can keep digging" but really it's just postponing the inevitable and increasing the number of people who will be destroyed when it all crashes down
Interesting; he is clearly saying that they were ("as a field") "confident and wrong" to believe that "the economy would have been completely upended" by the appearance of a model as strong as GPT4. What seems to be missing, from your point of view, to consider it an admission of being wrong?
Altman has admitted that some things are taking longer than he expected, and has walked one or two things back (usually to keep people from throwing bombs at his house, but still...)
Zitron continues to boast of a predictive record entirely unblemished by accuracy.
Man, as a former extreme skeptic, I watched a video from Eric Schmidt in early 2025 where he said that by the end of the year nobody would be coding, and that one was dead frickin on.
> now there have been numerous projects posted on HN that are AI coded.
Yes, all of which are toy projects and get criticized every time they are posted. On actual serious projects, not someones pet home project, I've only seen "vibe coding" used in very low risk places like small UI components. And even then they are generally heavily tweaked after the fact.
My anecdotal personal experience seem to agree with the general sentiment I see here on HN. Some people or companies do it, but with generally heavy criticism.
It is all very unevenly distributed. SaaS and general web is basically on auto mode.
A lot of infra is vibe coded nowadays too.
Even prototypes are contributing to the speed of software development. Many people vibe code throwaway dashboards around the main platform which gives a lot of insights.
Everyone who started using claude clode when it came out in early 2025, knew it was coming (not quite yet). That felt more like reporting than prophesying.
You may be living in a bubble. There are tons of developers still coding by hand, and many industries that don't trust machine generated code in general.
Have you considered that they do trust their code review processes, and that they don't trust the generated code because it doesn't pass their process?
> they don't trust the generated code because it doesn't pass their process
That's not a credible scenario. Developers can either make changes by hand, or by asking an LLM, which is the common process when there is a downstream failure. Humans dont metaphorically throw their hands up and say "well the tool doesn't meet our expectations at every scale so we're not going to use it". Granted, most developers scale back how much they rely on it based on experience (good and bad).
That's very much a credible scenario. I think I use code from SO in a single digit of occasions. But I use it a lot more for giving me insight like a keyword for doing a proper web search. Or the name of a flag for a cli command, or the general shape of an algorithm or what to check in a troubleshooting session.
I won't generalize, but it's very rare for me to need code as most of my diffs are either boilerplate (generated with a tool or copied from docs or samples) or core logic that is mostly the translation of some design that I've already spent hours or days on. My core issue has always been incomplete specs from Product or incomplete docs for some tool/sdk/library (alleviated by having access to the source code).
Generated code is just not that useful, especially when designing the core architecture of a new project. And later it's not that useful either as the specs (why and how) is more valuable than any code (what).
> many industries that don't trust machine generated code in general.
Which ones? Why wouldn’t careful human code review and extensive test coverage suffice? I work in one of the most conservative and highly regulated industries in the country. My company and every single one of my peer companies I have knowledge of has transitioned to almost exclusively 100% LLM-generated code (with plenty of human review).
I don’t live on a coast and I have a large and broad social network. I don’t know anyone who still mostly codes by hand except the small amount needed to preserve some aspect of their skills. I’m sorry to say that if I did I’d consider them foolish. Even a very restrictive workflow where you used an LLM to specify granular edits you intend to make is vastly faster than doing it by hand. And the level of test coverage and depth you can achieve now is simply life-changing.
It’s much more likely that you are not a professional, or you are the one in a bubble.
>Why wouldn’t careful human code review and extensive test coverage suffice?
I have come to understand that LLM generated code, even when carefully reviewed, ends up being hard to review as time progress.
This is because when you are coding yourselves, you get a first hand sense of the complexity creeping in. Then you refactor some stuff to keep complexity in check. LLMs does not "feel" such friction, and will happily keep adding on complexity until meaningful reviews are impossible beyond a certain point.
At this point, you need an LLM to review the changes and at that point, all bets are off.
This is a very good point. So many times I would refactor entire parts of the code base just because it’s getting too complicated and an easier solution was possible. AI is do often just let’s drill down all these variables, whatever
So no one is in control at the wheel? Just press a button?
I can see in the future in school or on the job. Oral testing is coming back. You’re gonna have to explain everything you are doing at some point to your teacher/boss or to a panel of your peers in detail.
Any that value correctness over speed. Banking, safety critical embedded work, aerospace work, etc.
> Why wouldn’t careful human code review and extensive test coverage suffice?
Because anyone who has been in the industry for a while knows that code review is not a substitute for intentionality and understanding when writing the code. To properly validate a change you must fully understand the intention behind it and the design at play, and then check the changes made against the system design. That is best done by a human subject matter expert (this is the role which software developers have traditionally filled, for anyone new to the industry).
> I work in one of the most conservative and highly regulated industries in the country. My company and every single one of my peer companies I have knowledge of has transitioned to almost exclusively 100% LLM-generated code (with plenty of human review).
That's called "being in a bubble".
> I don’t live on a coast and I have a large and broad social network. I don’t know anyone who still mostly codes by hand except the small amount needed to preserve some aspect of their skills. I’m sorry to say that if I did I’d consider them foolish.
And I think it's foolish to let your coding and critical thinking skills atrophy like this, but you do you.
> It’s much more likely that you are not a professional, or you are the one in a bubble.
I’m perfectly willing to consider the possibility that you may be right, but “a bubble” implies something massive outside of it which constitutes a large majority of the whole, and that’s simply not the case here. I just don’t believe there are more than a small handful of companies like you describe. It’s not like these things aren’t extensively studied, and all the industry surveys I’ve seen point in the direction of more and more LLM-assistance in coding worldwide.
I have connections in most of the industries you named and I can promise you that they are no different. I don’t particularly care whether you believe me, but I encourage you to self-examine to understand whether what you are saying is what you would like to be true (I do too!) or whether it actually is.
> I have connections in most of the industries you named and I can promise you that they are no different. I don’t particularly care whether you believe me, but I encourage you to self-examine to understand whether what you are saying is what you would like to be true (I do too!) or whether it actually is.
You are literally talking with a professional developer who is telling you that they don't use LLMs to write their code and that they have connections who also continue to do this work manually.
I don't particularly care whether you believe me either, but I encourage you to take a look around - your initial claim that coding has been automated across the industry is incorrect and you seem to be in denial about that for some reason. You should question where your priors are coming from, and remember that just because your circle is comprised of people who are heavily using LLMs does not mean the entire industry is that way.
Dario Amodei and Eric Schmidt seem fairly well-calibrated, although a bit early. Elon Musk is constantly way, way overoptimistic (perhaps to the point of willful fraud). Zitron is hopelessly and ridiculously incompetent (and there are allegations he is willfully lying, too, but who knows).
Yep I distinctly remember at the beginning of 2023 that folks were predicting that we were less than two years away from there being no jobs for software developers. Pretty soon we'll reach double that timeline.
And of course it really has changed everything! But that was not all that a lot of people were prognosticating.
My bet is that Amodei's claims about the dangers of AI are the most likely to come true – I'm predicticing amodei/anthropic will become the evil it was against.
No, you see, they were right all along, they just "didn't anticipate the public outcry against data center expansion", thus the obviously inevitable AI takeover of the economy is being slowed by NIMBY curmudgeons who should be ignored and punished.
To be fair, Zitron's career is as a commentator. To some extent, I expect CEOs of companies to make ridiculous claims. At the end of the day, when shareholders come knocking, what they care about is whether or not your company is growing.
No such mechanism for social media personalities. You can be wrong 90% of the time, and your audience will still praise you for the 10% of the time you were right.
> To be fair, Zitron's career is as a commentator. To some extent, I expect CEOs of companies to make ridiculous claims.
This is not a comment directly at you, because I understand where you're coming from, but I think this attitude shows how far leadership and our expectations of the professional class in America have deteriorated.
My expectations are inverse to yours. I don't care if a commentator makes a claim that's wrong, if they keep being wrong people will stop listening. (In theory. Jim Cramer still has a job so who knows, really.) I certainly don't expect a commentator to have accurate internal information about a company.
CEOs on the other hand should be expected to be honest and accurate in their claims. The information a CEO shares should be accurate so that investors can make informed decisions. Instead, we seem to accept CEOs who act as salesmen first and leaders last.
If a CEO claims a product will be out later this year, and the stock goes up, then they announce actually things are delayed, and the stock still goes up, what is actually being rewarded here?
I don't think of Zitron as a journalist, I think of him as an entertainer, no different from all the columnists paid to tell people that what they already think is right.
The fact that you're holding him to a higher standard than fabulously compensated professional c-suite officers whose products are used in matters of life and death is... kinda weird?
The big difference is that Altman et al aren't just, or even mainly, pundits or prognosticators. Zitron's whole thing is commentary and predictions about AI and his predictions are almost all wrong.
Altman and friends are mainly actually making and delivering AI. If they also hype their timelines/valuations, they also seem to make directional progress on the goals.
But I think anyone who evaluates their claims understands that they’re talking their own books.
Zitron’s problems are more subtle. He benefits financially from his own claims, while also touting his impartiality and capacity for objective thought.
A person savvy enough to understand the indirect financial benefit to Dario promising that Claude is so dangerously smart it must be regulated understands Zitron’s schtick
Not very. I like to always watch both sides of this issue, the people who are optimistic, pessimistic, doomers, etc... He is someone who in my opinion misunderstands the bigger picture. He often downplays the capabilities of these systems, doesnt think they will be more powerful in the very near future and also more importantly makes a fatal misunderstanding that we live in a rational world with rational actors.
I don't really care what Zitron says or pay attention to him because it seems clear to me he has some kind of agenda.
But this article is not nearly as impartial as it claims to be. It interprets all Zitron's claims in a narrow and overly-literal way. Missing the point and refuting a technicality.
For example, looking at the last 3 year's revenue/profit growth. This tells us nothing without looking at a larger context. Has revenue growth slowed down? Have profit margins compressed? What makes up the income and has that changed? Etc.
I think anyone being intellectually honest understands that these tables alone don't refute Zitron's claims that big tech are "dying and thrashing around" which is something that could take many years and easily hide under these kind of top line / bottom line numbers. (Maybe further analysis would refute the claim, but that analysis is not present here.)
Or Zitron's claims that AI capabilities are "reaching the upper limits" back in 2024. I don't think even Zitron would disagree that AI capabilities have grown since then, but that doesn't refute his point. How long the "reaching" takes and how wide the "upper limits" are is completely up to a subjective interpretation, which this post makes no attempt to even explore.
By all means dunk on futurists. But at least steelman their positions or you look just as biased as them. (Although maybe I am off base and this bias is meant to be clear from the start by admitting to pro-AI predictions all the way back in 2015.)
Yeah, I think this is fair criticism, and I definitely felt the pointedness in the tone as well.
On the overly-literal / narrow thing, I think thats the culture around evaluating predictions overall. Like, all those posts around christmas where people make predictions and evaluate how last year went. The rigor is the norm.
He is a bit more of a PR person rage-farming disguised as a futurist. He's not optimizing for correct predictions. That's really hard and not his incentive.
There's a demand for loud and confident "AI tech will fail" and "big tech will fail", so it pays to peddle the goods.
A lot of people desperately want AI to be a nothingburger. Thus, they will seek a second opinion that just so happens to line up with their existing one. Wishful thinking at its finest.
There are an even larger amount of people who have gotten tired of the NFT levels of pushiness AI has become from a financial perspective. It's become worse than crypto bros at this point.
pragh@ (Prabhakar) (yes his ldap is an anagram of graph) absolutely gutted the fire wall between search and ads.
To pick a specific piece of public information to support my claim: the previous SVP of ads quit immediately before the coup to start a subscription based search engine.
One nonpublic piece of information: basically every member of search leadership was pushed out within two years of his ascension.
Zitron has become the distorted reflection of the very AI boosters he criticizes and mocks.
I think the worst thing that happened to him was AI skepticism becoming a political position. This gave him a captive audience - as long as he says what they want to hear, which means that he can never ever concede that he might have been wrong or that AI might actually be progressing or having successes.
This is not conducive to good prediction long-term - rather it leads one to a state of cognitive dissonance where one's chosen enemies must be simultaneously terrifyingly powerful and incompetent dunces. The propagandist's disease.
How? AFAIK, his arguments based around the economics remains the same, he just seems increasingly dramatic and exacerbated, which is understandable when you realize industry + ecosystem (politics/reporting) is tulip mania delulu and insists 1+1=100, or 30 trillion, or whatever. His position isn't based on AI progress - it's based on AI economics, at this point he can be an obnoxious rationalist slamming flat earthers - just because he's annoying/smug doesn't mean he's less right on fundamentals which if anything is more clear now.
> you realize industry + ecosystem (politics/reporting) is tulip mania
It could be "tulip mania" or it could be "the internet".
Luu analyzed the numbers instead of just reacting to hype.
Specifically:
>> Oct 2024: OpenAI's forecast of $3.7B revenue in 2024 and $11.6B in 2025 and $100B in 2029 are absurd, "a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud"
> Wrong (2025 goal exceeded, 2029 TBD but not an egregious financial crime level of implausible)
>> February 2025: Anthropic making $34.5B in revenue 2027 is "is laughable on many levels, chief of which is that OpenAI, which made around twice as much revenue as Anthropic did in 2024, barely made a billion dollars from API calls in the same year."
> Wrong (whether or not they make that in 2027, their 2026 ARR greatly exceeding that makes the 2027 estimate non-laughable)
On a spectrum between tulip wilting and fiber build out, we know deprecation cycle of DC hardware leans towards tulips i.e. <10 years (very generous) vs 20+ years for fiber layout, a lot of which is actually infra/earth works etc.
The numbers being cited is ~100B is well within accounting/ledger maxxxing tricks relative to current pool of investment. Luu is not analyzing number's he's just listing and believing numbers, and analytically entirely avoids the core Zitron thesis... once you tap out of easy investor $$$, FAANG warchest, accounting tricks... where is the rest of the order magnitude more $$$ that justifies existing spent relative to time frame coming from?
> On a spectrum between tulip wilting and fiber build out, we know deprecation cycle of DC hardware leans towards tulips i.e. <10 years (very generous) vs 20+ years for fiber layout, a lot of which is actually infra/earth works etc.
Counterargument: As advancements in transistor densities slow down, the rationale for increasing depreciation cycles makes more sense. As the performance gap between new & 5-year-old hardware continues to shrink, then the need to replace older hardware similarly shrinks, justifying longer depreciation cycles.
This narrow focus, of course some intermediaries in industrial chain is going to make $$$ selling/renting shovels - there is stupendous amount of $$$ being moved around, there will be some very phat winners, but even more losers in aggregate on broad ecosystem level. [1] is actually illustrative, there's a reason why opex low - capex premium is ridiculous right now, with almost everyone along compute industrial chain capturing 50%+ margins. Investors are burning $$$ and companies and pillaging warchests, intermediaries are raking in $$$, but that doesn't mean investors or companies doing all the spending will make more than they spend, i.e. the net ecosystem business model is not sustainable precisely because intermediaries are capturing crazy rent relative to actual monetization to sustain.
> but that doesn't mean investors or companies doing all the spending will make more than they spend, i.e. the net ecosystem business model is not sustainable precisely because intermediaries are capturing crazy rent relative to actual monetization to sustain.
You understand that this doesn't follow at all right?
The intermediaries margins can compress.
> opex low - capex premium is ridiculous right now
What does "capex premium" even mean?
Of course you spend more on capex when you build a data center than opex!
High capex matches the expected business model. If opex was high then everyone would be worried!
Investors exuberantly build $10 of housing when there is $5 of demand, builders extract $8, when they normally extract $2 under normal margins, builders raking it, but arrangement is net loses vs world where investors build same housing for $4 and make a profit. Intermediaries margins can compress but what they already extracted for current build out is already built in balance sheet.
>What does "capex premium" even mean?
>Of course you spend more on capex when you build a data center than opex!
No. Historically DC opex > capex, i.e. 60-80% goes towards power... because hardware costs were relative low % of TCO. Historically without delulu AI demand, IC producers capturing much less margin and TCO of DC was much lower than it is now. It's not opex vs capex it's TCO. AI is paying $10 vs $4, when demand is $5, $10 isn't sustainable, $4 is.
Now builders will be fine in case of crash, they'll compress margins for next round of buildouts, i.e. bubble bursts, current spend proves not sustainable. This is where the crux of argument is...
Future investors post crash when margins revert towards mean will be spending $4 to supply $5+ of demand. And due to nature of compute deprecatiion (i.e. tulips) they will have more efficient hardware with less opex/capex TCO per unit of compute, with much more sustainable balance sheet. The builders are still fine with their $2 margins, it sucks its not $8. But that leaves the current investors who spent $10 with stranded assets that are not competitive with more efficient $4 future build out, i.e. current investors have balance sheet black hole that cannot compete with none bubble market force.
This does not mean AI is doomed, it just means incumbents from current tranch of bubble driven, stupid high TCO build out is most likely doomed relative to future entrants. Unless incumbant has unassailable moat, or other hedge/cards (i.e. political bailout/intervention). That is the actual argument, Zitron is saying current ecosystem economics not sustainable, not that there is not a future model that isn't sustainable. But it does mean a lot of current players are balance sheet zombies, who _should_ die. But a reasonable disagreement is reality is size of bubble + contagion risk + influence of incumbents i.e. trillion dollar companies is such that they have non market lever (i.e. politics) to save themselves... but someone else is going to be doing the paying for a model that is net loss.
When you predict a company is going to fail and instead it sets revenue records you're not "dramatic and exacerbated". You're refuted.
Luu's post includes a (long!) list of specific predictions that aren't "exacerbated"; they're simply wrong.
Luu's point isn't that AI is going to succeed or that the "AI bubble" will never pop. It's that these predictions are all wrong. If you agree "directionally" with Zitron, all that means is that you're skeptical of AI. That's a totally reasonable position to have, but it has nothing to do with whether Zitron's predictions are good or bad.
No, the whole thesis is XYZ likely fail because REVENUE RECORDS is not enough to dig out of hole relative to MAGNITUDE MORE SPEND. Saying Zitron wrong because XYZ made $2 for every $10 it spends revenue needed to justify spending. Fixtaing on the $1-$2 is misdirection/innumeracy, the thesis is in reaching the $10 relative to time, i.e. that $2 has to be $10 in X time, but the current velocity suggest it will not be.
I agree with Zitron directionally on accounting, I in fact disagree with him on AI... I am extremely AI pilled, i.e. I think there is a future where AI is worth trillions and will capture large swatch of economy. The transformation will be extreme, unlike any past revolutions... but the accounting suggest that future isn't coming in time to rescue current AI incumbents from finance blackhole, which some may survive, i.e. bail outs, nationalization... but the $$$ suggest however we get there, there will likely be massive $$$ corrections involved irrespective of adoption.
You keep saying this. It doesn't mean anything to "directionally agree with Zitron" in the context of this Dan Luu piece. All you're saying is "you're skeptical of AI and the AI business model". Bully for you! Lots of people are. Nobody is dunking on you for having that skepticism. They're dunking on Ed Zitron for making a long series of patently risible specific predictions.
This just assumes Luu's piece has good argument that refutes Zitron's thesis when it doesn't. Saying Zitron is wrong because XYZ made $2 instead of $1 is different then Zitron staying XYZ is unlikely to make $10 in time when all signs still point to overperforming at $2 is not enough. It's a stupid reason to dunk.
That's a gross mischaracterization of what Dan Luu demonstrates in this piece as anybody can see for themselves simply by clicking on it. But the radical divergence of our premises (mine: based on the actual article; yours: unclear to me) explains why we're talking past each other.
It's not mischaracterization to point out limits of article is a poor basis to dunk on Zitron because it does not refute Zitron's broader thesis only nitpick what is really minutae/noise that can be explained by trillion dollar companies short term financial engineering / spreadsheet maxxing rosy picture. Even if Zitron short term forecasts/model sucks, it doesn't discount directional validity of his medium/long term thesis.
Someone in deep debt backstopping with maxing credit cards is not dunking on outside observer saying this arrangement ultimately not sustainable. The article is nitpicking over short term micro/liquidity when ultimate macro/solvency. Now maybe there's plenty of credit cards to max out, but systematically someone is going to end up holding the bag, and politically that could be public socializing costs. If folks want to use article to dunk on Zitron short term forecasts, it's whatever, but I think important to point out it doesn't refute his long term thesis around fundamentals, which again does not mean fundamentals cannot be overridden by non market means, but that's also a crux of the long term thesis - in lieu of correction/market clearing, we're going to see non market interventions to save current model from its fundamentals.
"Saying Zitron is wrong because XYZ made $2 instead of $1" is not a reasonable summary of the post we both just read and I don't think there's a point in trying to hash this out further if you disagree with that.
Did you read the article? It paints the picture of someone who does not in fact have a good track record on the 'fundamentals', even if his broad thesis of a bubble may prove correct.
e.g. when he suggested Anthropic may be fudging their revenue numbers / projections - which was actually due to him making some careless mistakes in a spreadsheet
(edited to remove snark)
Your comment seems to miss the point that the article does not (necessarily) have a problem with Zitron being insufferable/annoying/smug. It's that his predictions are verifiably wrong. It's one thing to be annoying and right. Zitron is annoying, but not right.
Yes? What happened to FAANG in last 3 years, they cut a fuck load of jobs, the raised rent/prices, then inflation, then experience surge in new category AI. 1 + 2, i.e. squeezing rock has limits. 3 is fundamentally not sustainable, i.e. AI revenue gap order of magnitude relative to spend. This like debt crisis, there's lot of levers to burn to maximize extraction and make ledger look good short term, but is fundamentally not long term sustainable. Articles arguing over minutiae / short term accuracy pointless, market can stay irrational than one can stay liquid blah, blah - I mean its useful for investing - but when talking about long term predictions he's just stating the obvious, the financials don't make sense within the business cycle current players are operating in.
Like one can believe AI is speciation event technology eventually, but still given actual constraints, i.e. literally not enough investors for $$$, not enough hardware, not enough infra over xyz time horizon that these companies carrying stupendous debt and mathematically guaranteed stranded / deprecated compute infra is only digging themselves deeper vs future competitors. Sure AI can eventually capture 30% of GDP and knowledge worker's life time achievement is worth a few $100 of compute or a few pennies in thinking sand. But ultimate winners is probably going to be some future startup that pays pennies for thinking sand not incumbent who paid magnitude more and simply can't operate profitably due to balance sheet.
Luu is pretty specific about the predictions Zitron is making, has taken the time to pull them out and date them, and they're both risible and not rescuable with vibes.
His point isn't that Google or Meta are doing well or have bright futures. Luu is generally critical of tech giant engineering and product culture. He's critical of Google in particular in this very article.
But the point of the article is that it's not enough to have directionally satisfying vibes. If you made concrete forward-looking predictions and they're catastrophically wrong, that matters. If you make backwards-looking predictions that were literally wrong the moment you published them, that matters even more.
"Did you read the article" is a frowned-upon response on HN. The better way to write that kind of response, per the guidelines, is "the article mentions that". So: the article mentions that.
I don't know if directed at me because I didn't ask if one read article.
> it's not enough
It's enough for some of us, like his broad predictions that work on timescale of business cycles seem directionally correct. Even considering we're dealing with fast hardware deprecation cycles it will take years to play out especially with investors and incumbents burning through accumulated war chest. Luu seem oblivious to notion that companies with trillions in market cap can certainly out manipulate fundamental short / medium term market sanity. Part of Zitron's rant I find similarly compelling is the danger of dismissing directionally "satisfying" vibes because $$$ can capture reporting distort reality, which is only going to lead to bigger/more painful correction because directionally "correct" was dismissed as merely directionally "satisfying."
Let’s say it’s fine to give emotionally based arguments the same credence as rational arguments. That’s a huge cede, and yet, it doesn’t change anything, let’s see here:
If my cousin kept ranting about my other cousin was going to go bankrupt and fail and it was 3 years later and their income was up 2x I think I’d stop listening.
I worked at Google from 2016 to 2022 and agree with everything he says and you say, modulo the companies who are 2-3x on revenue and profits are going to 0. I worry that both of you have found a real problem but misattributed it, and insisting emotional arguments are the same as rational prevents you from participating in real fixes (ex. metas problem isn’t AI, it’s that they have a god-king CEO who cannot be deposed and monopoly profits. Imagine a twin of you and Zitron but instead of AI it’s 2020-era VR. If they weren’t focused on how their emotional argument was fine, they’d be your compatriots in noticing something’s off in Big Tech. Instead, we don’t hear about them because that battle was fought and lost years ago, and they lost credibility due to imagining Meta was going to 0)
Zitron gives timelines, and they don't come true --- in fact, the opposite thing happens. You can't come back to that with "well, it hasn't happened yet". By that logic, no prediction is ever wrong; wait long enough and maybe it'll come true. That can't possibly be the logic you'd hang your hat on here.
> Luu is pretty specific about the predictions Zitron is making
He is not, though. He precisely points to imprecise predictions, decontextualize them so he misses the point of the ones this thread is focused on, analyzes them with even less precise rationales that don't really rebut the prediction, and points suggestively (enough that you seem to have got that suggestion) that this rebuttal destroys the main prediction of every Zitron piece, while saying otherwise several times at the end of the rationale.
Zitron's predictions aren't all very good, but this article isn't either.
Ah I understand what you're saying. Yes I agree that if you pull back to, "We're in a bubble," then you can say that Zitron is correct, at least fundamentally, despite being wildly inaccurate in almost every other prediction he makes.
But Zitron isn't just blogging about how we're in a bubble. The assertions he makes are not minutiae, he basically continuously says that all the big SW firms are walking corpses. He's not having a rational conversation about the long term prospects for companies who invest in AI. There is a population of people who (rightfully) hate Google et al and want them to fail, and he just stokes their anger and frustration.
He doesn't add anything substantial, and (as the article indicates), even when he brings economic figures into the conversation, he's frequently wrong or misrepresents them.
I edited while you were responding with second para. I think his analysis that existing investors are walking corpses (or economically exhausted/weakened) is substantial. You have new companies going into extreme debt and established companies burning war chests may actually is important, and also valid economic argument ESPECIALLY if you think think AI will be economically transformative. Like current players basically spent $1000 on a screw driver to do $10 of work. Some of them went $1000 into debt, some of them drained $1000, which is much of their savings/warchest. The incumbant players rationalize future has $100 or $1000, or of work, but these companies are going to be vs player buying $1 screw drivers, i.e. the compute deprecation curve makes spending $1000 on screwdrivers in the first place very detrimental/terminal vs future competition. Zitrons argument is broadly there even if there is $1000000 work in the future, companies that spend $1000 on screw drivers balance sheet is working on timescale where there is $100 of work, i.e. the economics is not in favor of incumbents. The economics might still be very favorite for future AI... but not for first round of players who has to recover from grossly overpaying.
He makes very specific predictions about specific companies and they are wrong.
You think we are in a bubble and that AI won't pay off for the companies investing in it.
While I'm sure there will be companies that invest badly the problem with your prediction is that the public hyperscalers (Google, Amazon and MS especially) are already seeing returns from their AI investments.
Look at the revenue growth - that is actual dollars coming through the door.
Here's an exercise you should consider doing: instead of your $1000/$10 numbers, use real numbers for the major software companies investing heavily in AI.
Software companies aren't walking zombies for the same reason cabinet manufacturers aren't. Everyone can make their own cabinets, but few do, because they simply don't want to.
> The assertions he makes are not minutiae, he basically continuously says that all the big SW firms are walking corpses. He's not having a rational conversation about the long term prospects for companies who invest in AI.
...huh? How is it "not rational"? He's saying that, based on the financial information available, it appears AI doesn't actually make very much money given the capital investments. To the point that there may never be AI ROI.
I'm not sure how much this or that "prediction" matters. His arguments would be just as strong without them, perhaps stronger because they wouldn't give folks like Luu something to snipe at.At this juncture, the analysis seems sound. AI costs an absolute fortune and appears to make very little money, comparatively.
Is that irrational? IDGI. One needs look no further than Oracle to see a company in dire financial straits.
- They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers
- Google Search has to compete with LLMs
- Meta hasn't demonstrated a credible argument on how they're planning to use AI. AI 'friends' would kill their business model. Their saving grace ironically is that people absolutely hate interacting with AIs. Same goes for other AI assistants.
- Hyperscalers have to compete for the same hardware as AI companies, driving their costs up
- AI turned out to be excellent at both porting software to more optimized stacks and deleting the 'prestige' of building these ultra-inefficient microservice containerized stuff. I haven't read a single article about somebody bragging about this stuff. When it comes to tech (which is not AI), usually its about Zig, Rust and going native.
- So if customers really start feeling the heat of rising costs, they have a realistic path of optimizing their compute usage by using AI to rewrite the worst-offending components. I think one of the few things in which AI has demonstrated measurable economic value is rewriting software in Rust to be more efficient
> They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers
Emphasis added, since having a horribly expensive AI infra allows offering enterprise contracts, which is a form of lock-in and has been pretty lucrative for GCP/Azure/AWS.
No. Net income is up quite a bit and profit margins maintained at Microsoft, Amazon, Alphabet, and Amazon. Meta net income is flat, but they are maintaining profit margins.
Zitron's claim is that much of that boost in profit for microsoft and alphabet and amazon is from only a few customers, specifically openAI and anthropic, and that those companies are buying and promising to buy lots of resources with money from investments from those same companies, and that largely this is unsustainable unless openai and anthropic can find a profitable business model.
He is right about that. Those companies are subsidizing the use of their models and at some point they are going to have to make a profit. It is unsustainable the direction they are currently headed in many people don’t like the messenger of bad news, but someone’s gonna be caught holding the bag stay clear of the blast crater.
And with both OpenAi and Anthropic are announcing record revenue growth to the point where Anthropic is now profitable this seems like it's going to work out fine for them.
To be fair to Ed, I’d describe his usual argument (at least currently) as saying that Meta, MS, google are “mature” companies trying to be maintain the high valuations and growth of a young company, which they no longer are.
If you take this to be his argument, then dan’s numbers are more consistent ed’s claim.
Are they? These companies have been caught tweaking their numbers. One example, not sure if cited by Zitron, or others, is that they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books. There have been trillions of debt discovered this way. Another issue is the apparently relentless progress of the hardware industry, needed to justify their super-high P/E ratios, measured against the fact, that to lessen the effect of HW amortization, hyperscalers opted to lengthen the depreciation timelines of their GPUs. So there is an apparent contradiction that new hardware needs to be both substantially better, and substantially the same, to make both stories true. I'm not a finance guy, and a lot of it is over my head, but even finance people keep asking the 'who's gonna pay for this' question. We're way past the belief that this is going to produce reasonable returns (as in a value for money kind of way), and hoping we can financially engineer ourselves out of this situation without having to feel the pain.
> These companies have been caught tweaking their numbers... they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books.
This is about as far from "tweaking their numbers" as you can get. It's a standard way infrastructure-heavy industries structure their investments and people would be asking questions if they didn't do this!
> hyperscalers opted to lengthen the depreciation timelines of their GPUs.
Yes and so they should! GPU depreciation timelines used to be 3 years!!
Google is famously still running 10 year old TPUs at 100% utilization, and 10 year old H100s are worth more now on the second hand market than they were when they were bought.
He has built a following of people that want to hear his extra skeptical views. And even if he changed his mind about some things, he cannot admit it, as that is not what his followers want to hear from him.
It's rare that people make the news and build a following by saying a very balanced, down to earth opinions... unfortunately.
I almost wonder if it's even possible now that so many of us get our information through algorithmic feeds.
I listened to one Zitron interview on YouTube and my home page was immediately crammed full of similarly foamy-mouthed AI critics. (As well as plenty more Zitron.) And it's suggested some people with un-nuanced pro-AI takes, too. But what the algorithm has never, not even once, given me is a sober voice that calls attention to the nuances.
>It's rare that people make the news and build a following by saying a very balanced, down to earth opinions
Humans are built for fighting and killing the rival tribe, not for pondering whether the other tribe might actually be correct. We are exceptional for even being able to overcome ourselves enough that the outcome of "fighting and killing" can be minimized in the large.
> And even if he changed his mind about some things, he cannot admit it, as that is not what his followers want to hear from him.
I don't think that's true - over the years he's changed his mind from "LLMs are useless slop machines" to "LLMs can be useful when applied wisely".
For instance in "The AI Hater's Manifesto" he says:
> It just came to me — the problem that I have with most people using LLMs is the delineation between outsourcing work and outsourcing thought. Those using LLMs to write little scripts or BQL code on a Bloomberg Terminal are inoffensive. [...] A tool being used as a tool to do tool things — in many cases involving the LLM writing a little 30-line Python script! — is not a problem, though it’s also not a trillion-dollar industry that needed to steal everybody’s art and writing.
Similarly, in "The More You Buy, The More You Lose":
> Sidenote: The only truly useful use case I’ve found is on the Bloomberg Terminal’s ASKB feature, which takes natural language and turns it into BQL code to make requests of Bloomberg’s datasets. It’s genuinely useful!
You can perhaps say that he underestimates what the technology is capable of (or, conversely, that other people overestimate LLMs) - but that's a different kind of conversation.
But even those concessions have been a shift: at every point, he's been as bearish as possible on LLMs, often past credibility.
And if you take it as a given that AI will never be any better than ~~now~~ a year ago, and that anyone who disagrees is an idiot or a liar, then that pretty much demands that the entire AI economy must be as fraudulent as he imagines. Which, while it serves his purpose of serving up AI-skeptic invective slop well, doesn't actually model what's going on, which is speculative investments that have the potential to generate extraordinary returns.
right, and look at current American politics. One side tried to tailor normal, routine and rational POVs.
The other...
EDIT: I do find it amusing when I write these types of comment, then suddenly realize the irrational man childs of the far right nationalist republic ethnostatists think they're the rational ones.
There are plenty of people on the far right whose positions are rational provided that you agree with their views. Conversely, there are plenty of people on the far left whose positions remain irrational despite that you might agree with their views. It is a serious cognitive error both to fail to see the irrationality of those you agree with as well as to fail to see the rationality of those you disagree with.
> I think the worst thing that happened to him was AI skepticism becoming a political position.
It is a political issue in the sense that the discussion around AI can't avoid material and cultural issues. Ed Zitron definitely has an ax to grind and I'm personally turned off by his hyperbole, but I don't think something being a political issue means it's not worth discussing. I've also noticed the pro-AI crowd pivot to accusing people of not having actual reasons for hating AI, being victims of Chinese propaganda, etc as a way to avoid actually talking about specific issues that people have about AI and DCs.
I never said it's not worth discussing, I'm just saying that it becoming a charged issue was bad for Zitron specifically because his style of content fell in demand with the most irrational parts of the crowd.
You're not wrong but for a lot of AI boosters it's also a political position - remember Anthropic and half of SV at this point is run by wide eyed effective altruists.
Ultimately one cannot separate technology or science from politics, it's inherently political
I'm not sure I have the force of will to not succumb to it. I think the only way to avoid it is to be so sure of the thing you are doing that the audience reaction is not the key metric by which you measure your success.
"Popular topic-expert" is a really cursed career to exist.
Ideally we would reward expert opinions on track-record, instead of how they make us feel. But we don't. Also ideally, the expert's conclusion wouldn't impact their ability to pay the rent (as long as it's correct), but again, that's not the world we live in.
This isn't about people who just happened to make it big in a market rally, though. You're talking as if I'm speaking about people who just happened to buy some Bitcoin in 2012 rather than leaders of some of the most successful corporations on Earth.
They're not infallible, but modelling them as complete idiots that just happened to get lucky is also... Not really consistent with reality, as far as I can tell. These people might not be good people, but they're good at playing a certain kind of game.
Things can look stupid when we don't understand them, but there has to be some intelligence somewhere at some point even if the arrival of wealth then suffocates it with sycophants. If Musk or Trump or GWB were all *merely* the idiots they're often mocked as being, chances are we'd never have even heard of them. They almost certainly weren't even "merely average".
Now, stupidity that arrives after the bank balance reads a billion dollars, that's terrifyingly powerful.
1. Trump was born wealthy. There was no "arrival of wealth" that smothered the intelligence you suppose he might have used to earn the wealth, because he didn't earn it.
2. You don't understand. Trump is successful because of his stupidity, selfishness, and vile behaviour. Not despite it. In 2016, the Republican primary field had 20 or so candidates on a wide range of reasonableness. Trump crushed them all, because he most represents the average Republican voter. If he were more intelligent, or if he cared more about anyone other than himself, they would not have voted for him. His arrogance, lack of intelligence and morals is quite literally his strength because it's what makes him so relateable to the American masses.
There are two possibilities. One is that half the country are total idiots and the people leading them, and leading the country, are also total idiots who only got into power because half the country are, again, complete idiots below average intelligence.
The other is that you are in a bubble and have been convinced that the leadership of the world’s premier superpower are below average intelligence, along with 70-80 million voters. The former is not something an intelligent person would believe, you have thrown out serious analysis for political theatre and memes and should rethink how you view the world. Now stop to consider that maybe actually half the country has a totally different worldview, and that their leadership, having reshaped global politics, is actually full of intelligent people who are cold and calculating. I know it’s harder to stomach, but just consider it for a moment.
Because it's not a single data point, intelligence is a wide surface area where you can be smart in some areas and stupid in others. Furthermore whether you are being intelligent is relative to ideals and goals, and not everyone has the same ones.
I find it difficult to imagine an intelligent person who finds it hard to get what they want. The trope of the oblivious genius who is incredibly competent in a single field of inquiry but completely unable to handle day-to-day life is more a creation of media than how reality works.
At first I thought you were referring to Umberto Eco's laws of fascism: "Fascist societies rhetorically cast their enemies as at the same time too strong and too weak."
but it's subtly different, because incompetence is not weakness.
It's pretty clear in how people talk about billionaires: They must somehow conclude that the people most successful within a system that rewards certain things are not competent because the things the system rewards are not what they think the system should reward (it is fine to believe the system rewards the wrong things, but people walk straight into denying that those people have skill even within the system, or they claim that skill within the bounds of the system does not reflect any "real" skill - totally ignoring that elites tend to stay elites even through, say, Communist uprisings).
Hence how someone can say that Musk is "dumb" with a straight face.
> the system rewards are not what they think the system should reward
It's the grown-up version of nerdy kids hating "the jocks" in high school. We're all just a bunch of dumb kids. Maybe obsolete children, but still children when it counts.
That said, Elon Musk celebrated cutting funding that fed starving children and supported cancer research by waving around a chainsaw on stage. The richest man on earth did this because he wanted lower taxes... for himself.
When Anubis weighs his soul against the feather it's likely to completely destroy the scale.
I'm not saying any of the people in charge are good people at all. I'm just saying that they are skilled at achieving their own goals, regardless of the morality or lack thereof of those goals.
I don't even think that. I think half of them accidentally stumbled into success. Elon was kicked out of PayPal with a nice golden parachute so he wouldn't sue.
Regression to the mean is pretty nasty. Stumbling into success can make you a car dealership owner or something like that, but being consistently successful in business requires just about as much skill as being consistently successful in, say, chess.
Ed Zitron’s job is to convince people to pay him money to read what he writes, of course he’s going to preach to the choir, they’re paying him to do that and he knows it.
This is why I always consider the agenda of an author, Ed Zitron’s agenda is to make money from subscribers who read his writing.
From the article "A more common defense is to say, just in general, people attack Zitron because of Y (usually his style), but they never address his points."
The article "engages with Zitron's work"; the post you responded to merely extended the discussion to speculate on why Zitron might be producing it.
(btw, for the record, I'm an AI-hype skeptic and _also_ an AI-head-in-sand skeptic; as far as I can tell, both sides are full of malarkey.)
he makes a shit ton of money off this - in this attention economy we are doomed, people of every side find that going all in on something, no matter how intellectually dishonest, is much more profitable. Extreme AI bros or Extreme AI doomers seem dishonest. AI is an amazing technology - it is simultaneously not going to replace us in the next 3 years and it's not total garbage - the truth lies in the middle.
Its pretty clear if you listen to him now he's just (re)playing the hits for his audience. Its like MSNBC/Fox News for people who think they're too smart to fall for that.
I used to think he was just early on some of this stuff but the sheer amount of content he produces its clear he's just cashing a check.
I'm not a huge fan of his style myself but fundamentally he isn't wrong. The whole "growth" so far has been all show and no go. I see people pouring in millions only to end up bankrupt a few months later. Evangelists portray those instances as rare and simply "skill issues" and "they don't know what they are doing but I am". Anyone that's ever had several servers running at home and seen the electricity bill at the end of the month knows it - I do as well. And we are talking about servers that use power, only a fraction of a server running 4x H100s at 100% 24/7. For those of us that have - we are talking servers that have one or two xeon silvers at best, 15% load on average. And I live in a country where the electricity is veeeeeeeeeeeery affordable. I'm not taking into account training, or investment to get it going, just inference.
20 bucks subscription a month, dario, you ain't fooling anyone with above-room-temperature IQ (Celsius). Even the expensive subscriptions - we know that's not the real price. And the limits, bumping up prices every two weeks and so on, just to keep the lights on while draining investors... Zitron's claims are pretty impossible to deny: the moment those companies go public, the real prices will need to come out of the shadows and end up on your monthly bill.
At the same time I fail to see the real world benefit to this, even in software: it's like comparing Lego (before they began their anti-consumer bs) to cheap Chinese toys. The moment you look at them side-by-side, you know which one is a premium product and which one is a cheap Chinese toy. While I have been a big supporter of open source since I was a child, I was never biblical about using open source - if some proprietary piece of software does a better job than the open source one - fine, take my money. Not anymore. I see the abysmal state of cyber-security as a direct consequence of slop. Slop-written code, slop-reviewed code, tests pass(also slop), ship it. Yeah, I'm not trusting you with my data, the hell with that, I'm self-hosting everything, adios. And I sure as hell don't trust the ai-bros for anything either.
And there's another thing: Microsoft was clear about it: github is constantly down because they can't handle the load. App stores are bumping up developer fees. Anyone can slop together a todo app(which was never hard to begin with). It's still a winner-takes-all economy - no one is going to install a todo app and migrate from Google/Apple just because. So the 1000 todo apps released daily will simply be a hole in the pocked of the people who slopped them together and another reason to be paying 500 bucks for 64 gigs of ram and another 500 bucks for a 2tb nvme. Raspberry pi's started off as educational platforms for 35 bucks and their commitment was to keep them at those prices. That aged well, right? If I decide to upgrade my uconsole, I have to pull out another 350+ bucks for a raspberry pi. All thanks to the sloppification. The bubble can't pop soon enough and frankly I don't care what it takes down with it.
Ed Zitron has the economics of AI basically right. Most technologies arrive by digging an enormous financial crater, followed by a contraction period in which everyone insists the crater is actually a revolutionary new business model, before the survivors eventually buy up whatever remains.
What likely resonates is AI really does feel like a science experiment. There is clearly real value here. The problem is that the economic value has yet to catch up with the technological value. And yet the claims coming from AI companies have the unmistakable energy of a state-fair entrepreneur standing beside a suspicious knife yelling, “You have never seen anything like this before, it slices it dices...!”
I think Ed goes too far when he compares LLMs to garbage. He’s tried them, had a handful of bad experiences, and apparently decided the entire technology belongs in the round file. But much of what humans do is essentially trial and error with better PR: apply some logic, see what happens, adjust, try again, and continue until you eventually solve the problem.
If you can get an LLM to reliably do that, you can solve certain classes of problems dramatically faster.
I think he's constantly trying to time the peak (of AI improvement, of compute capabilities, of profitability) and keeps having to readjust his predictions every time it's proven wrong. Timing the peak is a fool's errand unless you have extremely hard and unavoidable data that everyone will have to face by a deadline. But contrary to what AI boosters often imply in response to skeptics being wrong, failing to time the peak doesn't mean the peak doesn't exist. So far it has existed for every new technology.
To commit fraud you have to lie, deceive, or conceal. All of this bonkers financing is happening in broad daylight, announced to the markets, and met with rave reviews. I tend to agree with Zitron that the whole thing is a castle made of sand - not because the tech is bad or useless but because the financing, in its scope and structure, is so outlandish - but you can build a castle made of sand as long as you don’t tell anyone it’s made of steel.
So far NVIDIA has been very careful, it’s not actual fraud, at least based on public information. It’s a very unstable and extremely risky bet, that is very likely to blow in the face face of AI companies, but it’s not fraud
I think a lot of people (myself included) would love for it to be fraud. Because even if it's not fraud what is being done between NVidia, OAI, Anthropic, Microsoft, Meta, Musk and Google is funny accounting at the very least. It's hard to take any part of what's going on seriously in the US at this point and I feel like the bigger downside to all of this is that if/when they get away with this, and there are no repurcussions for any of the big names involved, then it erodes consumer trust that much further, pushing us deeper into a state of "doesn't matter anyway, why try".
Yes, you can include me too. I’m aware enough of the details to know we don’t have any proof of anything fraudulent, but that whole situation is just so disgusting
Doesn't this ultimately boil down to: other people are spending their money on things I don't want them to? Which I mean, yeah I feel like this about tons of things all the time. I'm human too. But I know this is a petty part of me not a thoughtful part.
Patrick Boyle had a vid specifically on whether there was Enron style fraud. The conclusion was no, though he thinks things may be a bit bubbly https://youtu.be/NufJ7g63KSY
Why? If there's no evidence of fraud, why are you imagining some new category of fraud that these companies have independently conjured up?
Suggesting that an entire industry is in cahoots to invent and participate in an entirely new fraud-like scheme, including companies that have lots of wealth and growth and much to lose from such an exposure...seems awfully conspiratorial, don't you think?
There is no evidence of fraud that I have seen beyond complete speculation from the likes of Zitron. He basically just says "Look how big the numbers are! It's so big it must be fraud!"
> If you are going to look at this and say “actually it didn’t” because of its Enrontastic accounting treatment, I also need to warn you — that identical guy in the bathroom is actually a thing called a “mirror,” a reflective surface that is showing you a reflection of you, not another person who is dressed like you and copies everything you do. I can’t imagine how scared you’ve been, and hope this has helped.
That’s his weird writing style, so I’m not 100% sure, but I don’t think he literally means that OpenAI is committing Enron style fraud. More of a stylistic way to say it’s a mess
>What follows may be an Enron-Lehman Brothers hybrid, one that leaves unbelievable destruction in its wake, an avoidable systemic risk empowered and enabled by a kneecapped media industry and sell-side analysts incapable of seeing further than two quarters in the future.
He also mocks the financial statements from the companies in a way that alludes to them being fraudulent (from the OP):
> February 2025: Anthropic making $34.5B in revenue 2027 is "is laughable on many levels, chief of which is that OpenAI, which made around twice as much revenue as Anthropic did in 2024, barely made a billion dollars from API calls in the same year."
Wrong (whether or not they make that in 2027, their 2026 ARR greatly exceeding that makes the 2027 estimate non-laughable)
> Oct 2024: OpenAI's forecast of $3.7B revenue in 2024 and $11.6B in 2025 and $100B in 2029 are absurd, "a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud"
Wrong (2025 goal exceeded, 2029 TBD but not an egregious financial crime level of implausible)
I'm realizing that he is very good at alluding to gross financial crimes without outright accusing them of it (probably as a hedge against libel or something)
I haven't read every word but I don't recall him saying AI is bad or useless ever either. His refrain is that they cannot keep up with their endless spending on training and they're not reaching new markets.
I look at the rapid rise and decline of OpenClaw and get the impression AI has not really found any foothold among average people.
August 2024: "generative AI is a dead-end technology that has peaked”
July 2024: "Generative AI models aren’t getting more energy-efficient, nor are they getting more “powerful” in a way that would increase their functionality"
Nov 2025: "the fact we're running out of high quality training data and we're hitting the walls of scaling laws, in the training paradigm, these models aren't getting better. What we're seeing today is pretty much what they're always gonna be like"
There are other examples too from his prose of talking about how they are barely useful but I don't want to dig it up
> I don't recall him saying AI is bad or useless ever either.
He does say that pretty often in interviews. That doesn’t change his thesis but that‘s one reasonable reason people dismiss him, he has often said that AI is useless when considering the externalities. And he will sometimes take a shortcut and just say „it’s useless, doesn’t do anything well“, which is of course way too simplified.
Zitron sells anti-hype and AI-hate. AI is not good for a lot of people and he's telling them what they want to hear. He's great at talking and making entertaining facial expressions. That's actually a real skill I admire but it has nothing to do with predicting markets correctly. He's in the business of selling entertainment views not predicting markets. He even admits he doesn't short AI.
How often are people that are paid by their content attracting eyeballs correct? Isn't this a universal thing that people in these roles are constantly stating all sorts of things that never happen. This happens in sports media, politics, tech reporting, stock market predictions, etc.
Shouldn't society have a clever name for people playing these roles by now? Something catchy, insulting and based on truth might help call this out easier. I would throw influencers in there too, they are writing/video-loggin/podcasting for the same money outcome.
How has it taken so long for this to get some proper attention?
I'm not Ed's biggest fan, but he's been pointing out some very important things for quite some time now, regarding the ludicrous over-investments going on around so many companies that are completely and utterly devoid of profits and will likely never have any.
Though the bubble has not popped, I don't see the following discussed in the post: Zitron would probably point out (as have others) that many of the hyperscalers are booking valuation increases in Anthropic, OpenAI as "Other Income", which is substantially increasing their reported revenue and earnings. It's roughly:
- Hyperscalers like Goog, Meta, Msft invest cash in Anthropic, OpenAI, in exchange for equity
- The ongoing investment actually boosts the valuations in the Anthr/OpenAI (new raises are done at higher valuations), so the valuation of the Hyperscaler's existing investments in Anthr/OpenAI increases, which gets recorded as Other Income in quarterly earnings
- Much of that invested cash will itself come back (circularly) to the hyperscalers as revenue since Anthropic and OpenAI spend a lot of money via datacenters etc.
Sorry what is the punch-line here supposed to be? These investments obviously increase correlation coeffs., but these are highly correlated stocks to begin with.
valuation gains on investments are one-offs, not signs of sustained improvements in profitability that would warrant higher market caps
when those valuation gains are in turn the result of circular financing schemes (a bakery giving out money so that people buy bread from it), we're getting to a dangerous situation
Circular financing is an issue if the wealth accumulation stays in the chip -> model provider ecosystem. However it seems like the labs are making quite a lot of revenue from the chips (customers).
Demand for compute is far outstripping what was projected in the initial rounds in which we pearl clutched over 'circular financing' - which is hardly distinguishable even from the classical bill of exchange, the core phenomenon of the money market in Bagehot's day, in which I provide you inputs and you give me a share. I keep reading people saying what amounts to: the primitive bill of exchange was circular!!; if the seller of inputs has reason to lend, so does everyone else etc etc. In fact if the projections about final sales are correct, it is plain all these deals will be fine.
The issue is simply that the posted article begins with a review of recent earnings/ revenues, but fails to discuss that a substantial part of those revenues are investment markups.
Whether it matters we don’t know yet, but it’s a fact worth noting. A better article might have tried to argue why it doesn’t matter
As far as I understand GAAP reporting standards actually require them to report gains on those positions as "earnings".
But they do report non-GAAP earnings sometimes excluding them. E.g. Google earnings per share last quater is $9.11 GAAP vs $2.85 non-GAAP (mainly because of SpaceX shares).
The first section of this post responding to "Meta, Google, and Microsoft are dying" is completely misrepresenting Zitron's arguments in the linked video. Zitron is making essentially an enshitification argument concerning Google and Meta. He's not talking about whether they will be able to squeeze out more revenue in the short run, but how they are willing to abuse their users to ensure that they do. Citing increased revenue for these companies is not arguing against Zitron's point.
Luu also fixates on Zitron mentioning Prabhakar Raghavan, but then proceeds to agree with Zitron's core point that Google has intentionally degraded it's search product to maximize revenue. Maybe Raghavan is not solely responsible, but it seems fair to hold him accountable for trends that accelerated under his leadership.
Fair enough on Zitron being wrong, but I think the opening argument about Meta, Google, and Microsoft misunderstands his point.
Zitron is saying that the hyperscalers had no genuine growth opportunities, so they're using the AI bubble to achieve growth. The fact that they've continued to grow for a few years doesn't contradict his point, and Meta's steadily decreasing profit margin certainly doesn't look healthy.
Seconding that observation. The IT folks in charge of the compute direction have been quietly raising those concerns for over a decade (“and what happens to those alleged lower costs when their attention diverts to a new industry or pumping margins for shareholders?”), and the major enterprises or customers had all but migrated wholesale into public CSPs - and been eyeing the exit when they finally opened those eye-watering bills IT had kept forwarding to stakeholders. The industry wasn’t going to collapse so much as right-size, and that would turn into an inevitable cycle of churn (higher prices to drive margins, leading to more customers leaving in part or in whole, which would drive up costs higher to continue delivering positive results, ad infinitum).
The current AI build and boom has done wonders to their bottom lines in the immediate, but even Wall Street has its limits, and it sounds like there’s decreasing appetite for such CAPEX builds without associated proven revenue. That might kill some companies outright, but more likely it’ll force the major CSPs into the churn cycle that much faster.
I think lot of people including Ed are mixing 2 things the AI tech itself and the economic viability with the inflated values of companies building it currently. Me personally I am optimistic about the tech itself but don't see the current AI companies valuations being realistic or even the economic systems they are building around AI/LLM. As it will all be comoditised down to cost of compute + cost of electricity in the end.
To me and most other non-West coast Americans its obvious he's right. Which is a good explanation of why SV has the resources and success it has because it can do things no one else believes in. While the rest of the world will always be catching up.
I used to pay attention to Ed Zitron, exactly because he seemed to be someone who did the research, and looked at numbers. Until one day, I realized that seems to only look at numbers as long as it serves his agenda. When it doesn't, he looks away or makes the case for why the numbers are wrong, and shields himself from these "incorrect" numbers - or people who would point to anything suggesting that AI is not a total fad.
In April 2025, Zitron wrote [1] "I am sick and tired of everybody pretending that generative AI is the next big thing." This was at the time when AI coding tools had already gone "mainstream" with devs, and pretty much everyone was using tools like GH Copilot, Cursor, or something similar.
So I replied with this observation, saying how, at least within software engineers, AI is being adopted faster than any technology before [2]. To stay objective, obviously I brought receipts: sharing how, based on an older survey I ran, ~75% of devs in that survey said they used AI coding tools. Zitron made fun of the small sample size (216 people), blocked, and pretended like AI had zero PMF anywhere in the world.
I stopped taking him seriously since then. And I'm wondering ever since: does he deliberately only look at numbers and facts that he can tell the AI doomer story around? Or is it more that he finds that there's not many people who are "informed sceptics", and decided to play this role?
Ed's right about OpenAI being out over its skis, he's right about the numbers for everything being wildly optimistic and he's right about the circular financing/leverage aspect of a bubble. He hates AI though so he can't acknowledge its usefulness, it was pretty clear to see on his DOAC interview, Stephen kept bringing up real wins and clear progress, and Ed wouldn't engage in a substantive way.
Yes, his thesis is pretty much correct, his personal opinions aren’t too relevant or valuable. It’s a mistake to take his predictions as the important thing, it’s pretty much irrelevant, the whole field is very dynamic and complex, and he obviously isn’t an oracle who can predict the future. The only thing that matters is the thesis
I think he deliberately looks at doomer facts. I'm not sure it's cynical so much as a genuine belief that it's all nonsense. But IMO the belief is based on a lack of understanding of AI.
Looking at it from an objective/historical perspective, when he first got on his high horse agents weren’t a thing, MCP was in its infancy at best, and half the code generated didn’t compile from frontier models.
From there everything split into two factions, which I’ll dub as believers and non-believers. From there, it has entirely been a cult following despite the evidence showing that models and agents have legs for software development.
FWIW my post history would show my extreme skepticism, and to an extent I still am. I think the real power of models isn’t the model at all but the harnesses.
Either way I think he lost the plot and runs on vibes himself. I also think this whole AI movement is going to have their 2000/2008 moment before the phoenix rises from the ashes.
I don't agree with the believers vs non-believers dichotomy. That makes this look like a religious war and it shouldn't have to be like that. To me AI is a very useful tool, no more no less, it isn't a 'make a wish' machine and it isn't a silver bullet for all of the issues that have plagued software so far. But when properly applied it's quite useful. "Non-believers" would have to be people that have yet to actually use AI, just like you can probably be a non-believer in peanuts until you've seen them, and most people that I know acknowledge the reality of AI tools and their use cases.
All tools, AI included, have a business end and as long as you point that away from yourself you will be fine. But to properly apply it (rather than as a faster way to make a huge mess) takes discipline and being methodical. It was never different.
what's it with people who think a bubble is literally destined to happen because of some religious belief that history repeats itself? I find it fascinating to understand the theory of mind of such people. So much confidence.
Just speaking from a gambling/odds perspective: the odds that a bubble never pops again in the history of mankind is a 1 out of 100, where the odds of a bubble popping again are 99/100. Your religious finger-pointing cracks me up.
He's part of the professional political / social media class now. He makes his money through engagement. I've stopped trusting people of this ilk. I listen to people who make most of their money not via the media ecosystem.
Luu kinda has a reputation for knowing his shit, for over a decade now. He's not a checks notes games journalist larping as economist, but he does all right.
Ed Zitron mostly covers the costs of data centers, circular spending, and predictions of large the market for AI has to be to justify the data center expenditures.
I was disappointed this article didn’t really cover Zitron’s main arguments.
Maybe a paid article placement? I don’t know, but I was dissapointed: I read Zitron’s material and I wanted to see good counter arguments to his rants about costs of data centers, circular spending, and predictions of large the market for AI has to be to justify the data center expenditures arguments.
I knew him personally years ago and he broke my trust, my own opinion is that Ed wants to be popular and make money. He couldn't care less about being a diligent reporter that cares about the subject matter, he's a hype merchant jumping on one side of the band wagon to get clicks.
I made the account to make the comment because I feel strongly about him being untrustworthy. You can take it at face value or assume I'm lying, that's your call.
On the off chance Dan sees this: one of the footnotes ("Some Zitron predictions" > July 2024) is broken. Right now it's showing a little 0 that doesn't actually link to anything if you click it :(
I've said this before in here but Zitron is completely captured by his audience at best and a grifter at worst. A couple of months ago he was tweeting that people were crazy talking about _agents_, that they didn't _exist_ and that people talking about them were shills or bots. The responses were full of incredulous software developers saying but but but I use them every day, they're so good they're scary actually...
Zitron is just, like Dan Luu says, wrong about everything and doesn't care anymore, he's in the business of extracting money from his engagement.
This entire genre of pundit is just a person who has figured out that you can sell copium to the masses. Once upon a time this was a decentralized "this is how Ron Paul can win" thing on Reddit, but it was inevitable that slowly it would coalesce around these kinds of engagement bait people. Every subculture has its own such figureheads who DESTROYS opponents with FACTS and REASONING or whatever, but really it's just a reality TV show. The Alex Jones, Gary Marcus, and so on of the world are mostly just selling an entertainment product.
It's just a question of what the entertainment is. Some people feel good about being told "we were being hoodwinked; there are lizard people" and others feel good about being told "you'll be 100x healthier and good looking if you take these supplements" and others feel good about being told "these people are evil demons who are stealing your water" and others feel good about being told "these idiot rich people are going to lose their shirts" and so on and so forth. It's like how I like slice of life shows and hate horror movies and my wife likes horror movies.
In a sense, the misinformation gambit of LLMs did not come fully to fruition in the West (as much as it has in 3rd world WhatsApp forward land) because the locals were already a fertile ground of poor epistemic hygiene and well served by human providers of misinformation. Hacker News itself only has some hundred thousand commenters or so and even this requires a practice of aggressive information curation to prevent unrepentant misinformation repetition nodes from polluting one's belief set.
Hate on him all you want (he's gotten very repetitive for the sake of subscribers and reads), but the basic premise that the modern AI industry is a circular-dealing, point-of-diminishing-returns grift still holds. The bubble is here and the longer it inflates, the worse the pop will be. Sure the goalposts have moved, but the basic numbers don't math.
The current cross-deals aren't purely circular; quite a bit of revenue is, in fact, flowing into the AI industry from the outside (you know, via customers). What's more notable is the shared risk, as the deals tie multiple companies across the chain to a set of shared bets.
If the frontier labs suddenly found themselves unable to compete with cheap open weight models running on widely available compute, then one might expect the frontier labs to be the only ones exposed to that risk, while a chip-manufacturer like nvidia could thrive in either environment. A partnership or commitment from the chip manufacturers to the frontier labs could change that. Whether that kind of inescapable connection exists is hard to predict without a lot of specific modeling, and at this point I'm inclined to think that neither chip nor datacenter demand is going to drop any time soon, and that the commitments would be unwound before a company like nvidia is threatened.
Zitron implied 2 years ago that OpenAI would collapse by now. How's that bubble popping going? All NVDA+memory co+frontier lab numbers are accelerating
The thing about bubbles is that everyone who thinks they’re going to pop look crazy until they pop.
And to be clear, a bubble popping doesn’t mean that AI goes away forever.
What it does mean is that we’ll see some kind of economic crash or recession, and we’ll probably see at least one big company fail or go bankrupt/restructure.
OpenAI is the company in most obvious peril.
I happen to think that Nvidia is in a more perilous position than they appear. Their hardware advancement pace is relatively weak and they’re in a crypto-like hardware bubble where they’re one technology breakthrough away from a complete collapse in demand for their AI data center solutions. They’re also doing a lot of sketchy hardware financing schemes.
Comparing to other bubbles in the past, this one could still have something like 2 years left. Patrick Boyle has a video on the topic, in which he's also very careful to point out he could easily be wrong.
By all means, keep betting on this being a wild success and we'll see who's right in a little while. If you don't think this is a bubble then you're in for a ride.
Look if we are going to raid pensions and 401Ks to prop up the valuation targets of Anthropic and OpenAI longer, then the bubble can stretch further and further, but eventually datacenters have to get built and powered. It's the power generation part that no one talks about. We simply don't have enough power in the United States to scale at the rate that Anthropic and OpenAI need to prop up their absurd valuations. AI is real, but these valuations are not.
TL;DR: Ed is directionally correct, but it's anyone's guess as to the exact timing.
In the meantime I'm not going to complain about subsidized credits from the big labs. :-)
I feel like just saying "wrong" to some of these feels a bit unconvincing.
e.g.
>April 2025: "It also, at this point, is pretty obvious that generative AI isn't going to do much more than it does today."
>>Wrong
Is generative AI really doing much more today relative to 1.5 years ago? Sure there have been sone improvements, but i feel like nothing fundamental has shifted in that time period. Nor would i really expect it to even if the statement was false, but it seems too early to tell.
Zitron reminds me of a lot of people who got oversized reputations after the 2008 financial crash. They predicted it, or could spin past statements as predicting it, and rode off that.
But from that point on they basically assumed this role of what financial punditry call perma-bears, people who constantly predict financial doom. It gets clicks and sells subscriptions, which is probably why they do it. But from that point on their predictions weren't very good. If you constantly predict doom then every now and then you'll look like you were a genius, but it's just survivorship bias. People discount all the other times you were wrong.
I don't know a whole lot about Zitron himself. Didn't he get big calling BS on cryptocurrency stuff that actually was BS?
The problem is that AI isn't cryptocurrency. This is very real.
I do suspect there's some bubbly stuff around it. I think data center construction looks very bubbly, especially the totally ludicrous amount of permitted planned data center construction. I bet no more than 20% of that ever comes online. I'm sure there's some AI companies that won't make it, and a bunch that are overvalued. But AI as a whole is real, not just hot air.
I don't know anything about this guy, but based on the discourse every time he comes up, Ed Zitron is a more polarizing figure for HNers than even Trump. Everyone here loves trying to dunk on the guy, yet he's apparently living rent free in everyone's social media feeds.
I think it's a mistake to make concrete predictions about something like a stock market crash on a given timeline. As they say, the market can remain irrational for longer than you can remain solvent. However, Zitron is directionally correct about a lot.
I will say, the first part Mr. Luu says about big tech not being out of ideas is pure horse shit. Anyone who has worked in big tech knows that leadership at those companies can have no idea what they are doing and still be successful in earnings or the stock market. They are sometimes successful despite themselves.
I knew him personally years ago and can't take a word he says seriously, speaking from my own experience, he is not a trustworthy person. He wants to be popular not accurate. He writes to make bank, not to be a diligent reporter that cares about the subject matter.
Zitron is an AI doomer and a clear fact-distorter. I follow him because even a broken clock is right twice a day and I do think he's a pretty smart guy. I don't read his newsletter (it's basically word vomit these days), but his interviews are marginally interesting. One of the quotes in the linked article is totally correct:
> He found a niche in anti-tech grift, and is now exploiting the niche for all he can.
Ed gets hard because of the love the anti-ai people give him and seeing him as the voice of anti-ai... If you listen to his arguments though he lacks knowledge of what these companies even do. He's been on so many shows discussing the negatives but he admitted to not even using the models for anything
I cannot shake the feeling that his two failed marriages suffuse his extreme negative outlook on everything that is not Ed Zitron, especially AI. His comments about photo shoots* and men resenting his emotional honesty** speak of narcissism and perhaps why those marriages didn't work out. Good luck convincing a narcissist to change their mind about anything, I speak from unfortunate experience.
Or there's this one:
"I also have not taken the route you are "meant to take" to get here...I did not "earn my stripes" in the traditional sense, and those that have believe I did not earn my way here"
And maybe he lived in a van down by the river as well? I can't take this guy seriously, I just can't.
But I get that he speaks to an audience that needs to hear his take and that's their call. I don't have time and I won't make the time for podcasts and sitting through the worldview of anyone for hours at a time, 2 to 5 times weekly. No one is that interesting IMO.
*"I do a good photo shoot, I do a good interview, and I capitalize on events...I believe there are some that would like this level of attention or prestige, but they do not want to do the work to get it, and that chafes"
**"some men don't like me because emotional honesty and introspection are difficult for them."
just give it time, anyone (even those with 115k subscribers) who predicts a crash every day will eventually always be right. might take a decade or two… :)
both ed zitron and dan luu are professional bloggers who earn their living from selling ai sensationalism, zitron using paywalls and luu using patreon. whether the sensationalism is positive or negative, either way it is a very clear conflict of interest.
The first correct, detailed prediction (in print) about the collapse of Fannie Mae and Freddie Mac as a result of the subprime crisis was made by Max Keiser, of Karmabanque, in (Zac Goldsmith's) The Ecologist magazine.
In 2004.
And he'd been talking about it before then.
People thought Max Keiser was a crank; instead he made detailed predictions based on his intuitions, limited insider feedback and cold hard facts. He couldn't say exactly when it would happen; he laid out some horsemen you could expect for the apocalypse and this was one.
The thing about a bubble is everything is fine until it isn't. And it's worth observing that key parts of what Zitron is discussing has been covered in the WSJ and FT.
It's all very well posting numbers to "disprove" him when what he is pointing out is that the AI hype train is delusional and the costs are buried.
But Zitron is directionally correct, I think, particularly with regards to Oracle, where things he has said have literally come true.
Frankly as a Brit I remain amused at how much Zitron winds Americans up just by being himself — sweary, vulgar, rude, catty. And since non-Brits can't read Brits, Luu has to engage in pretty immature character assassination about it.
I've always been suprised with the amount people take him seriously. I think he's someone who makes people who dislike AI "feel good". I don't blame someone who doesn't understand AI or have read what he's written.
But for the bloombergs and other podcasts I would have expected them to do a bit of research. I honestly think with the amount of doubling down he's been doing that he's a grifter.
Obviously Ed is a special case, but let's be honest, pretty much anybody telling you they can predict the future is selling you BS. And that includes all the people confidently predicting he was wrong. The actual situation is, there are genuine unknowns driving things with significant influence, and nobody actually knows what is going to happen. At best, people can talk about risks and likelihoods of outcomes.
> Now, if your CEO has never heard the phrase Ralph Loop, oh man, you are less than 30 days away from your next promotion. I'm not even exaggerating. Walk into his office, close the door, and say, hey chief, been experimenting with something. It's called Ralph Loops. And I think it could change literally everything. And he's gonna say, what's a Ralph loop? And you will say, give me $18,000 worth of API credits and I'll show you. Now you won't actually do anything, because you can't do anything. Because nobody can, because nobody knows what they're doing. But by the time he figures that out, you'll have a new title, and equity bump. [...]
> Talk about automation constantly. Nothing arouses the slumbering capitalists than the mention of automation. Drop names too, bro. Like talk about specific team members you can automate out of existence. Be like, yo, I automated Gary, bro. Tag Gary in the message. Tag him in Slack in a very public channel. Be like, yo, I just automated @Gary. His function has been Ralph Looped. And tag your CEO in the same message. You think you're getting laid off after that?
This is eerily similar to how a few people at work did some presentations about ralph loop and connecting agents to slack right when management was really pushing unrealistic AI productivity boosts. I was repeatedly asked to speed things up with AI while I was already heavily using AI to do work.
Not about Zitron specifically -- I don't read his study, but I don't know that making some statements in interviews or blog posts is the same as making a "prediction" (into which one would put much more though)
also statements can be interpreted many ways:
"Meta is dying" was countered by "Meta's revenue has increased since Zitron said that". OK, but 1) revenue/profit is only one measure of "not dying"; 2) what's the time scale? Nokia and Xerox were highly profitable companies that dominated their industries, and any prediction that they would go out of business at their height would have been laughed at, and yet, it wasn't too much later that they pretty much did.
He's dead wrong about the usefulness of the technology, but he's dead right about the uncontrolled corrupt circular financing that is driving this crazy over-expansion and market distortion. He fulfils a very useful function as a counterweight to the big tech horse-shit hosepipe that sprays us every day.
> For example, with a style that could be described as the opposite of clickbait, Simon Willison has written what I suspect is the most widely read blog among programmers for the past 3-4 years (in the same way that, at various times in the past, Joel Spolsky or Jeff Atwood or Steve Yegge seemed to be the most widely read programmer among programmers). Among programmers and other serious users of AI, I would guess that Willison has a larger audience than Zitron.
I have no idea Simon Willison is the most widely read blog among programmers. I truly have no idea, and I've been programming for just a decade.
A lot of Simon's blogs posted here are when new LLM models are released, on how good are these LLM models create pelican riding a bike using SVGs. Nothing particularly interesting to me.
I truly have no idea why would people be interested in blogs about LLM creating pelican riding a bike svgs every single time a new model is released. Maybe its a proof of AGI/ASI for some?
I guess to me, Simon Willison will always be the "create-a-pelican-riding-a-bike-using-svg-dude".
I used to read his posts about Django years ago (a little strange in itself as I'm not a Python guy) and it took me a while to realise he was the same person!
Zitron in general is representative of the conspiratorial thinking that has infected all spectra of the political space. Zitron obviously occupies more of the left space.
Good critique of LLMs & the companies behind them is hard to find, and it is harder when people gravitate towards this sort of thinking.
Zitron has staked his bear position and isn't budging, so regardless if he's been wrong and wrong again, he'll be remembered for calling the bubble if/when it pops, if only because so few in the media have done so without equivocation.
I don't know about Chegg, but the fundamental problem with Duolingo is their product does nothing to teach people a foreign language. The nasty reality of that product is if you go through their entire learning tree in a language, you might be at a CEFR level A1 for that language. And, you spent 10x the time and 10x the money you would have spent via something like Lingoda to get the same outcome.
This claim is just not true. And gets tiresome. You roughly end up where those courses claim to be in reading and listening - depending on language it can be over B1. (No course finishes B2, some do have B2 content). I ended up being able to watch some (not all) netflix series in foreign langue and I was in early B1 section. I clearly learned.
I just remembered that before AI, I knew Zitron from ranting about IoT and consumer tech. He just appeared one day in my Twitter Timeline, claiming to be the "man on the ground" at CES (or so my memory at least)
So from that standpoint, I guess it would make sense that a personality like that would now have ended up at the AI topic.
I would like to see a comparison with predictions of the pro-AI bubble and their hit rates though. This writing feels as selective as it tries to paint Zitron as.
All of the grifters (and lots of capital) can't wait to jump on the bandwagon because they see it as their chance to clean up. The same happened during the last 4 tech revolutions. (in my life so far: semiconductors, the internet, mobile communications, smart phones, crypto, EVs, probably forgot a few). And of course, as always, the longer term will be more amazing than the short term hype.
zitron is a jester. He knows his audience and plays it well. It is incredibly tiring to listen to his lies, but so are the AI boosters. I think it is net zero
Thanks for this post. Zitron is a prime example of how someone with little background, expertise, or domain experience can establish a grift in the outrage economy. Unfortunately, emotion and illusion when properly marketed can still go a long way in this world.
Easy to claim things as wrong without prodiving any facts.
Can I try?
> But when people bring him up, they're of course not generally citing his anger
Wrong.
> Google has been increasing the relative priority of revenue over the user experience over time
Wrong.
> I'm curious what people do after being on the wrong side
Wrong.
Some of the claims categorized as "wrong" are also completely true, such as training hitting diminishing returns. New models are barely an improvement and most people I know stuck on Opus 4.6 over any newer one for example.
Exact same thing for the claim "the fact we're running out of high quality training data and we're hitting the walls of scaling laws, in the training paradigm, these models aren't getting better. What we're seeing today is pretty much what they're always gonna be like".
If anything, model performance has regressed in actual use (i.e. not benchmarks) for the past half a year.
> Some of the claims categorized as "wrong" are also completely true, such as training hitting diminishing returns. New models are barely an improvement and most people I know stuck on Opus 4.6 over any newer one for example.
OK, but the first instance of a claim of diminishing returns was in February 2024, when GPT-4 was the best model available. Do you really think improvement since then has been minimal?
Only recently came across this guy and if u ignore the standard social media hyper hype hype he has, I dont think he is wrong even his 2024 predictions.
US has 1.5x the money supply since Covid. This means everything has to go up 1.5x to reach the same parity from before. eg inflation. All corporate earnings are going to inflate as 1b yesterday is 1.5b today.
There is no whete for these mega corps to go. They dont know how to grow. meta becoming well meta with the vr crap is case and point. meta blowing billions on a few hyped AI people is the nail.
Other than cloud, microsft/google aimt doing anything. xbox? nope, hardware? nah. It is all attention economy or selling the pick axes for it.
the only mega corp that still seems to be moving the needle is apple which i think speaks volumes.
Eds point is that AI tam or expectations are insane full stop and he admits coding has a use just not as big of a tam. Gen ai in art, music, etc did not take off at all esp compared to code. this makes sense, no one pays an artist 500k/year. their time is worth little compared to coding.
Where he is wrong tho is that this is not new. there is always a hype cycle of nonsense that screws the little people. what is new is the level of polarization. it feels like ai psychosis right now in ways that remind me of crypto but worse because ai is actually useful so people are even more insufferable.
Everything everyone is predicting has almost zero value. Nobody owns a crystal ball. Right now there could be someone working in a garage somewhere that could shake the entire LLM world to the core with a unique insight and innovation.
Think about the world before the 2017 "Attention Is All You Need" paper.
Did anyone predict that paper, what preceded and followed it?
Nope.
Same case now.
Maybe the word "prediction" is the problem; "guessing" would be better.
OK, what the heck. I'll make a prediction too:
You better buy SpaceX stock now. The way things are going in the US, the only way we build AI data centers at scale will be in space. Politicians have turned data centers into punching bags to be used to gain votes. We can't build power plants and people are being led to believe all kinds of things. Regardless of which, if any, are true or not, the rate of construction of AI data centers in the US is and will be seriously constrained by realities on the ground.
Zitron is providing a service: he's running the train for those who want to believe, or sincerely believe, AI is a bubble. His interviews are apocalyptical one sided rants that confuse what is with what Zitron thinks should be. I'm not sure he's wrong, by the way. As LLM performance is becoming more and more commoditized I fail to see how spend catches up to expectations to keep running this market as it does, but that's beside the point.
One annoying side effect is that YouTube's algorithms will always try to force feed you more of the things you last searched, to amplify your biases and send you down the doomscroll rabbit hole. So if you search for Zitron, next time you visit you'll be flooded senselessly with naysayers, contrarians and skeptics from all courses of life.
I think it would be naive to believe Zitron is unaware of what he's doing.
He's created a huge following (and is presumably making a lot of money) from pushing a hardcore AI-skeptic narrative, and I can't blame him for seeing that opportunity and running with it. We're ultimately all responsible for recognising these people and weighting their advise as necessary.
Additionally, from a public reputational perspective making bad predictions simply doesn't matter. In finance we're all aware of perma-bears who will predict the sky is about to fall, and when it doesn't just argue that the disaster is still coming, but is taking longer than expected, or that some unforeseeable thing happened which has compounded the risk but has for now kicked the can down the road.
So ultimately, it will be very hard to say Zitron is wrong unless he starts time-boxing his predictions, which I don't believe Zitron has done for obvious reasons.
That said I don't listen to him much at all. I've tried to listen to him a few times, but it's become evident very quickly that he doesn't understand the technical details enough to be making the predictions he's making and seems way too emotionally invested in the arguments he's pushing without good reason. I have strong personal filters for low-quality sources like Zitron – if someone raises enough flags I avoid them like the plague.
If anyone who predicts the future was reliably right, they could easily shut the hell up and become a billionaire on stock picks. But they don't do that, because nobody can predict the future. You can say what may happen, but not for certain, and definitely not exactly when. All predictions without insider knowledge are idle musings.
Also consider that the economy isn't rational. Our economy should have tanked several times by now. AI should have fallen apart by now. Meta, Google, Microsoft should have declined. Instead it's record profits. So don't try to make predictions by being rational.
It is funny to see mainstream media finally catching up to how much of a grifter this guy really is. I believe I was the first at least on HN to make a list of his horrible predictions over the time [1]. Since then Kelsey Piper [2] also wrote about it and got some traction.
I knew that somewhere in the future, something has to give because you can't just go around saying anything without losing some credibility. You still have some ardent followers in his cult of a subreddit.
But just to be clear: Ed is part of a bigger problem in tech journalism which is characterised by extreme pessimism and excessive skepticism. It is not correct to view Ed in isolation rather to see it as a part of the culture in which he can thrive.
I appreciate someone picking apart Zitron in a constructive way. He’s been an easy recommend to folks in my circles who just want to be angry, but there’s a reason I don’t read his stuff on the regular or in detail: I don’t want to be angry, I want to do something.
And I say this as someone who started as a doomer, and is increasingly a pessimistic pragmatist (“LLMs have value as tools, but not nearly as much monetary value as the main players believe they do”).
I get it though: for those of us who grew up alongside the net and tech sector, who loudly decried M$ greed for ME/Vista/8/11 but celebrated them at XP/7/10, who remembered when Google’s “Don’t Be Evil” was spoken with serious reverence, the current era of tech feels toxic and nauseating. Current AI is a prime target for that discontent, as are the companies whose motives very clearly aren’t societal progress so much as reality authoring and authoritarianism. In that vein, Zitron is magnetic because his entire position is “you’re right to be mad and they’re all going to die from hubris without you having to actually do anything”, which itself panders to the human desire for personally preferential outcomes sans individual effort.
Properly picked apart though, and he has as much substance to offer as the ardent boosters: a handful of “trust me bros” with a smattering of distractions to wind you up, but never actually address your concerns or questions.
i relate to zitron cuz of how much he seems to genuinely hate the people in charge of this AI bubble. he, like me, seems to wish that when this all falls apart they get proportionate harm to go.
that'll obviously never happen. it's wishful thinking and venting tbh. that's why i like listening to his stuff.
it's better than reading the wholly AI slop docs my CEO keeps sending out
Posting revenue numbers as an example of a company not dying seems rather foolish. Microsoft's gaming side is floundering and dying and Linux has been growing at an unprecedented rate as a result of Microsoft's decisions. Not to mention the geopolitical aspects at play here as countries make a serious consideration to drop Windows.
These companies are all heavily buoyed by their investments in AI which is essentially an oroboros of money.
I think the most enjoyable part of this is to have written it in the characteristic long-form Zitron wall of text style while still managing to pack almost the whole text with meaning, which is entirely the opposite of Zitron style.
Zitron is just a rage farmer that tells angry people what they want hear while selling them subscriptions.
Maybe he is well meaning, but it's pretty common these types are just milking an audience that they dialed in on with zero regard for integrity or honesty.
As always, shooting down commentary asking for more and more evidence is very simple.
Zitron has a somewhat ranting style. Luu's passage on Google search for example just nitpicks on the person that Zitron allegedly named as responsible for the decline of Google search.
The real issue of course is that search quality clearly has gone down. What does Luu want? A "study"? Everyone can see that. The person is not the issue.
This is a highly selective analysis of Zitron's writings that focuses on a couple of mistakes. People need to understand that any normie will understand the difference between rants, numbers and speculation in Zitron's essays. They are not written for autists who talk of "priors" and "evidence".
"This is a highly selective analysis of Zitron's writings that focuses on a couple of mistakes"
While reading this I was thinking it would be interesting to see just a few examples of Zitron predictions that he got right. Since you appear to follow his work, do you know of any?
The issue is the conspiracy. By pinning the whole problem on a single villain rather than the incentives the larger organization has created he 1. doesnt help solve the problem 2. creates an environment ripe for tribalism. Even if you ignore the racist undertones(fine its a stretch) he's still misleading people about what is happening.
I do think you have to consider predictions in the context of the world around them; he's been incorrect, sure, but has he been more incorrect than the predictions of those opposing him? Being less wrong than others is the same as being more right.
I want to point out that Zitron is _just a guy_. He’s not a billionaire CEO. He’s not a politician. He’s allowed to say what he wants whether it’s right or wrong, and _he’s just a guy_. He’s not swinging stock values for a group of insiders by tweeting. He’s not using pension funds to pay for a jacked-up IPO. He’s blogging and making a podcast, neither of which is compulsory for you to read.
You don’t have to spend effort proving him wrong. Just don’t read it and move on with your life. Regardless of which “side” of AI you’re on it’s kinda ridiculous how much effort gets spent on screaming gotcha at this one commentator.
He charges people money for a newsletter that reinforces completely detached from reality viewpoints. If he's just making stuff up, that's called grifting, and it's good people call that out.
This critique is leaning really hard on their interpretation of "dying". They take the literal company is going to fail type of dying where as I have always taken it the same way he has presented it in his "rot-economy" context. They can remain financially "successful", but more and more people hate their products, their products are getting worse, their products are "dying". Google Search is still a good example, the old Google search is "dead" if you like, a know many people, including myself who no longer use it. More people hate and getting off Facebook. More people are jumping from Windows to macOS or Linux.
These tech giants need AI to continue to grow, and that growth at the moment seems to be coming from just two AI companies who are burning a record about of investments. OpenAI has raised nearly $200B, that is more money than Australia's tax revenue.. and they are getting further from being profitable as Chinese models are getting better and much cheaper.
The article linked seems right, but you have to take these morbid analogies in a very specific way, and assume that the only way to measure these companies is revenue/profits/money rather than their products.
I wish people would hold actual professional media economists to the same standards, along with journalists who just repeat press releases without actually challenging statements. His main argument has been the numbers don't make sense, and can't see how this won't end badly for a lot of people.
If many people hated their products, they wouldn't use them. If they didn't use them they would not be financially successful. Google is not dying just because you personally have a feeling the results are worse than before and there is no definition of dying that would be consistent with Google's current state. If Google were to die they would die the way Yahoo did, because a competitor was demonstrably better than them and everyone switched off. There is no realistic evidence that this might occur in the near future.
If I have a billion trillion dollars but 20% of the population hates me, but I get to live in a giant solid gold mansion with an army of servants keeping the 20% away from me, have I really failed?
Still a failure because it is propped up by an inflated US dollar. Those trillions would mean nothing when the US economy collapses due to a cumulative effect of massive national debt, unending wars and inflation.
At least if you have the population by your side, you wouldn't have "guns, gold, potassium iodide, antibiotics, batteries, water, gas masks from the Israeli Defense Force, and a big patch of land in Big Sur I can fly to" [1]
They are all willing to risk everything to see if their bet on achieving "singularity" fructifies. I don't see us getting anywhere close (at least with the current tech).
[1]: https://futurism.com/the-byte/openai-ceo-survivalist-prepper
type shit Louis the XVI would ponder about
Was Microsoft dying under Balmer? I think we’d say yes. Even if the SEC filings indicated otherwise.
This avoids the more interesting question: Why does anyone care if a social media user is wrong
It seems there are some HN users, including the author, who cannot ignore Zitron
Why
One thing I’m observing in these comments is a willingness of folks to project their own predictions onto Ed’s statements when validating their plausibility. Eg. “I think he’s wrong about the timing but I do expect AI companies to go to zero.”
You can do that, but then you’re no longer discussing his predictions. You’re discussing your predictions, and your own positioning.
Those differ from Dan’s essay, which engages with the literal text of Ed’s numerous predictions during 2024 and 2025 which are demonstrably invalidated by their measurable outcomes.
On the flip side, I also see many people taking this thread as an opportunity to shit on Zitron as a person, and not "discussing his prediction". Incompetent/ blow hard/ dishonest are ones I remember off the top of my head.
AI by itself, is surprisingly polarized; Ed Zitron even more so.
Not sure why you see it as such;
Incompetent and dishonest are characteristics that follow from this professional work, adequately describing an individual who continues to make poor predictions, analyses and false statements refuted by past events.
Far from “shitting on” Zitron
Here's two possible set of predictions:
- a list of predictions that are entirely wrong, from A-to-Z, and are not even resembling what ends up happening
- a list of predictions that are wrong, but where the underlying points are in fact interesting and have some predictive value, and it's just the "last step" that is wrong
For example, one person might say "oh it's raining in Dallas therefore I should buy some TI stock". And we'll say for sake of argument that they say that even though it's nice and sunny in Dallas at the moment.
Another person says "Oh its raining a lot in Idaho and that is going to increase potato yields and therefore I will buy McDonalds stocks cuz fries will be cheaper". In this hypothetical it turns out McDonalds buys all their potatoes from ... Kansas or something instead (and it's a specific kind of potato in a completely separate market)... but Idaho potato yields _did in fact go up_.
An even more straightforward point: the iphone 3GS comes out in 2010, people are very hyped, someone looks at how RIM _still_ hasn't gotten its shit together and declares "RIM isn't going to to be able to stay profitable 18 months from now, they're gonna have their lunch eaten".
Turns out that RIM still made a healthy profit in 2010. and 2011. And 2012. 2013 was their first loss in a while... and then it wasn't until 2014 that they really got kicked in the face.
The prediction was early, overestimated how long of a tail RIM would experience, but how wrong was it? Was the prediction of some utility?
I'm saying this... it would be helpful if _some_ more AI companies flamed out. In some sense he does himself no favors by focusing on the corps with the biggest war chest instead of the various AI companies that spend a bunch to go nowhere fast and then have just disappeared.
Why is Zitron’s repute evaluated entirely on the basis of failed predictions? Predictions are incredibly hard. AI enthusiasts and thought leaders have made so many demonstrably incorrect predictions it’s hard to keep track. Based on this metric, Altman and Amodei should never be taken seriously again.
What else would his repute be based on? Maybe telling retrospective truth? Per the article, he does terribly by that metric as well.
Have you ever listened to Zitron speak? He's not exactly the type to hedge his predictions behind careful language about how hard predictions are. He makes every one of these predictions with absolute confidence and conviction.
So does everyone else, including prominent AI enthusiasts and tech CEOs. And most of those predictions are wrong, because predictions are really hard.
And we're used to insulting and making fun of the prominent members of those circles too, see: "Scam Altman", the large variety of jokes about Musk's timelines, comments about Dario waking up in a cold sweat whenever a powerful new open weight model drops, the "AGI achieved" meme etc.
Both can be bad, and I think people take issue with intentionally projecting false or irresponsible confidence (lying).
Zitron twists and misreports a lot of facts where they should know better.
CEO hypemen knowingly conflate Ambitions for certainty
> February 2025: "I will keep writing this stuff until I’m proven wrong."
> Wrong (Zitron continues to write despite repeatedly being proven wrong)
Technically he didn't say he would stop if he was proven wrong.
Being thorough and accurate might make you a lot of money in the stock market, but it's not a good way to get any media presence, because that demands being in front of people quite often, and basically nobody can be insightful and well researched in all topics of the day. Once you become a pundit, whether on politics or tech, and rely on eyeballs to feed you, you are going to be throwing stinkers. And at that point, you might as well just align with an audience and not care too much about whether you are predicting anything accurately.
We have people telling us the next recession being imminent all the time. Others told us that NFTs were key to the future of art. That's the pundit way. If you want accuracy, you become like Charlie Munger, have maybe 2, 3 really good insights througout your career, and hope do to well using the insights yourself, not by being a pundit
This is exactly right. Now, that does mean something about Zitron: he’s a pundit, not an expert or a forecasting genius. You could point to any number of analogous booster types. Twitter/X somehow loves pushing these people onto my recommended feed. I remember reading breathless threads about how o3 was going to single-handedly end white collar work. There are just more of that sort of person, so none of them in particular gets the same amount of attention as Zitron, who seems to be the only person willing to go on the record against AI. Maybe his overall worldview is sound, and maybe it isn’t. But he’s not really making confident, specific predictions about the future.
Which leads me to a criticism of the piece: several assertions are described as “Wrong,” with no explanation or citation, which are not obviously wrong to my mind. For example, the assertion that “DeepSeek has commoditized the [LLM]” is at least debatable. It is a prospect that the major labs seem to have at least considered.
In my experience, people who make fun of AI's ability to eliminate white-collar work are exactly the same people who are white-knuckling it, hoping they can make another $300k next year to buy that Rivian.
People who don't need a salary look at the situation more objectively and, in general, can see that a lot of white-collar work is in peril.
The flip side of that is that at least half of all white-collar work was already useless before AI. If it hasn't already been eliminated, there's no reason to assume a-priori that AI can eliminate it.
I think that is tied to the general trend that people see themselves as far less replaceable than others. And I’m not sure that people who don’t need a salary are exactly objective about it - unless you mean people who live off the state or something, those are people who need their capital reserves to continue to appreciate in order to sustain their lifestyles, and are thus relying on the destruction of white collar work to justify the valuations of the technology companies which are underpinning the strength of the markets. It’s like saying in the 19th century that only the propertied classes should be allowed to make decisions about labor policy, because the laborers themselves have their judgment clouded by their position.
But I take your point, and I only brought up the o3 example to emphasize that people on both sides of the booster/doubter debate can be prisoners of the moment. There are boosters eternally convinced that the utopia (or armageddon, for the doomer-inclined) is either already here or imminent, and there are doubters eternally convinced that we have reached the peak. One of them will eventually be right, but neither has been yet. You can’t fault one of them for calling their shot if you’re not willing to see it happening on the other side.
is this comment written by ai?
> We have people telling us the next recession being imminent all the time.
Yeah uhm so I'm not sure if you've like seen the world recently, but uh.
Yea
S&P 500 - All time high
DJIA - All time high
Unemployment rate - Near all time low (for last 20 years)
Number of US small businesses - All time high
US GDP - All time high
[Sources]
https://www.bls.gov/charts/employment-situation/civilian-une...
https://www.sellerscommerce.com/blog/small-business-statisti...
https://fred.stlouisfed.org/series/GDP
How well I remember people pointing to the scoreboard in early 2008...
How well I remember someone predicting 7 of the last 2 recessions...
Yes, one day, we'll have a recession. It doesn't mean the doom prophets were correct.
They haven’t allowed a recession to happen since ~2009 when they massively inflated their way out of the worst of the last one. Learned to have the cake and eat it too.
The only problem is after a few rounds of this the currency becomes worthless, and we’re well on our way. Inflation is a major component of those numbers rising.
And that's when we pay off the national debt for pennies on the worthless dollar. The pro move would be to stop lending the US money, but that's not going to happen.
The US doesn't require that you lend it money, it possesses the global reserve currency. It'll take it from you via currency debasement. That's a world problem whether the world likes it or not. There is still no viable (realistic) alternative, and that includes the Euro, Yen, Yuan, gold, Bitcoin.
There are no lenders outside or inside of the US for $20 trillion in new debt over the next decade. Monetization is the only path. If you mean lend the US money in regards to holding or using USD (while it's being debased as it is now), then sure.
And if the world tries to shake off the USD, well, Iran & Venezuela (oil transactions assist USD dominance) would like a word. I'm not suggesting defending the USD reserve position via military action is moral, I'm suggesting it's certain to occur.
Bloomberg: It Won’t Take Much to Burst the Stock Market Bubble - https://www.bloomberg.com/opinion/articles/2026-08-20/us-sto... | https://archive.today/O9sQE - August 20th, 2026
> First, the favorable impact of the artificial intelligence investment boom on economic activity and earnings will likely diminish significantly in 2027. That’s because what’s relevant for growth is how much investment is increasing, not its level. The increase in investment in 2026 will almost certainly be the peak. There aren’t sufficient resources — construction workers, electrical generation capacity, or chip manufacturing capacity - to increase investment by the same magnitude in 2027. Nor are the dominant hyperscalers likely to have the free cash flow and balance sheet capacity to sustain a bigger increase in investment in 2027 compared with 2026.
> Second, as the growth of investment spending slows, the growth in earnings of hyperscaler suppliers will falter, profit expectations will diminish and price-earnings ratios will shrink. The “picks and shovels” providers will suffer a double whammy - slower demand growth and profit margin compression. On the way up, higher demand leads to wider profit margins that sustain equity market valuations. On the way down, the outlook for earnings deteriorates quickly as the shortfall of demand relative to expectations is exacerbated by a collapse in profit margins.
> Third, as the investment cycle matures, the focus will shift to the returns that the hyperscalers are expected to earn on their massive investments. I suspect it will be difficult for the AI hyperscalers to generate sufficient revenue ($2 trillion or more per year) to generate the returns needed to justify an AI capital base that is likely to reach $5 trillion.
(I'd encourage you to read the entire piece, it was written by Bill Dudley, a former president of the Federal Reserve Bank of New York, and is too much to quote in its entirety)
Nearly 25% of U.S. workers are functionally unemployed, economic analysis finds - https://news.ycombinator.com/item?id=49403381 - August 2026 (7 comments)
42% of adults rely on their parents for financial support - https://news.ycombinator.com/item?id=48937288 - July 2026 (274 comments)
49% of young adults live at home, up 12 points since 2019. An economist says the fallout will reshape marriage, kids, and home-buying - https://fortune.com/2026/07/09/half-young-adults-live-home-f... | https://archive.today/1uB8d - July 9th, 2026 (Federal Reserve survey: https://www.federalreserve.gov/publications/2026-economic-we...)
The housing crisis is pushing Gen Z into crypto and economic nihilism - https://news.ycombinator.com/item?id=46079617 - November 2025 (4 comments)
Why millennials feel hopeless about the economy - https://news.ycombinator.com/item?id=46062082 - November 2025 (15 comments)
Most Americans don't earn enough to afford basic costs of living, analysis finds - https://news.ycombinator.com/item?id=44119317 - May 2025 (9 comments) [Report: https://www.lisep.org/mql]
https://en.wikipedia.org/wiki/Lies,_damned_lies,_and_statist...
And yet with all that, Democrats are likely to retake the US Congress because a majority of Americans are experiencing an affordability crisis.
Yet with all what? AI stock pushing indexes high and US stock market being cheap because dollar lost 30% of volume in last few years so the whole world is trying to profit from short ride? Record low unemployment because gas and groceries are so expensive most people work 2 or 3 jobs just not to end up homeless? Democrats are going to retake because ballroom and gold arch does not affect gas or grocery price. They will retake because Republicans proved they are extremely soft on corruption. Not only they allow POTUS & Fam. steal billions from taxpayers, they are not stopping it and some even profit themselves. Dems will retake because we have a dangerous version of plutocracy mixed with socialism, where one person on the top (POTUS) unilaterally decides that US Government will take a free chunk out of Intel, or that 20 billion of taxpayers money will go to help Argentina or Brazil or Japan. That's why.
I mean I wish you a lot of fun playing this discussion game online, but I kinda fail to see the point of it.
Someone could now of course say "hey, but are your sure that these are really the metrics we should be looking at?", which could then be countered with a "well of course! This is how one measures a recession, no?"
And that could go on forever, achieving absolutely nothing.
I believe the saying goes:
The markets may not be claiming a recession, but the real world certainly is.
I feel like I've been in a recession economy since the day I entered the workforce 14 years ago. The movement of the stock market has had no effect on my reality. It's like two different universes inhabited by two different sets of people.
IMO, all the narratives we were exposed to around privilege before and after COVID were a cover up of this fact that we have a two-class system which is explicitly creating this condition. The issue is at the system design level and goes far beyond "technology putting people out of a job". The privilege narrative was classic communist-style "accuse your enemy of what you're doing yourself." It was literally the privileged few preemptively accusing the unprivileged masses of being unfairly privileged in order to take control that narrative before it was used on them.
> We have people telling us the next recession being imminent all the time. Others told us that NFTs were key to the future of art.
That's quite the conflation, and a very subtle way to tie a claim that's still unresolved to one that is to try and make the first one seem wrong with no evidence. Recessions are almost guaranteed in our system, they're a part of a cycle. Unless you think that the Great Recession was the last one in history, saying the next one is 'imminent' would be correct for any other viewpoint. We just don't know when it'll officially start.
...get any media presence, because that demands being in front of people quite often, and basically nobody can be insightful and well researched in all topics of the day
What? Zitron is getting a lot of media attention by repeating the same takes hundreds of times. He's not a general pundit.
> For any of his posts that I read, while there are numbers thrown around, the numbers don't actually connect to a coherent argument. In many cases, as we saw above, the numbers don't even really support his argument (such as an MAU decline in Facebook causing Meta financial problems which would then cause Meta to spuriously insert AI in places it doesn't belong). I suspect he's relying on people's eyes glazing over when they see numbers and just not thinking about what the numbers mean.
A frustrating thing about Ed Zitron is that he sometimes breaks news - gets hold of leaked numbers that nobody else has, for example - but he then wraps those numbers in his own extremely biased commentary. This makes it much harder to evaluate how credible the new information is.
Didn’t the FT both vet his numbers and also publish on the same leak?
Yes, and his post about the exact same data was noticeably more confusing and less illuminating than theirs because he was primarily concerned to point to whatever the biggest number was and go "Ooh, big number!"
https://www.wheresyoured.at/exclusive-openai-financials/
https://www.ft.com/content/e15b0d7e-ff6b-4f16-ba7a-4068feddb... (https://archive.ph/pAIEa)
There was a major material difference between the FT and Ed's post: FT explicitly noted that OpenAI has $billions in cash on hand (which is relevant if you are analyzing data about solvency), while Ed's post obfuscated that data point.
“Because Danny had a mortgage and a boss to answer to … The guilty don't feel guilty, they learn not to“
As someone else mentioned, ignore Ed’s personality and look solely at the balance sheets and capital analysis. Regardless of delivery, the math doesn’t math.
It's wild to me how much Ed is criticized while pathological liars like Musk and Altman are glossed over.
(Disclosure: I pay for Zitron's publication for the capital figures and exclusives he gets his hands on, I do not pay attention to his interviews, we are fact finding, if he wants to perform, I am not bothered, I've seen the performers on the other side, just keep the facts coming for ground truth)
This was mentioned in the article.
> For example, when Timothy B. Lee looked at a spreadsheet that Zitron used to create a projection of Anthropic's revenue, he found, "He doesn't count February 1-10, counts March 1-10 twice, counts August 21-October 21 as one month instead of two, and doesn't count October 21-November 1. [another commenter notes that his spreadsheet also contains February 30] ... Ed claims he tried to compute Anthropic's revenue for 2025 and came up with $3.6 billion, suggesting some funny business [but the numbers work out once you fix the errors]"
As someone with a bit of understanding of accounts and finance I don't think Ed's analysis is very good. He's not someone who would pass a finance exam.
Is the source material good, in your opinion?
I posted here a while ago when his bubble prediction lapsed and plenty of his fans were here. Telling me how I was wrong and the Q2 reports weren't complete yet because it was still early July and blah blah
Are we living in the same universe? Musk and Altman are glossed over and not criticized?
Criticized as being poor human beings, or as being poor executives?
Because the former, as P.T. Barnum pointed out, is just free advertising. And I see far more of that than the latter. Now, if and when their various empires collapse there will be no shortage of people pointing back and saying "all the signs were there", but in my everyday life (obviously just a single point of anecdata), it feels like I see a lot more coverage of them as "bad people" than as "bad at what they claim to be experts on".
HN has a fairly complex user footprint, it's not everyone of course and I do not mean to paint too broadly, but there is a strong contingent of those pro in a cluster.
https://hackernewstrends.com/?q=Musk&q=Altman&from=151234560...
I don't see any sentiment in that data.
Would you like a list of pro Musk and Altman users based on their comment and submission history? I'm unsure if that violates the site guidelines, and I prefer not to have my subthreads detached or stern reprimands by mods (it makes me feel bothersome in a host's home).
Profiling Hacker News users based on their comments - https://news.ycombinator.com/item?id=47473086 - March 2026 (86 comments)
(simonw's work I cribbed off of)
I certainly believe there are some Musk and Altman glazers on this site. There are also certainly Ed Zitron glazers.
The point is not a few users you can point out, it wouldn't prove anything. The point is that you claimed that Musk and Altman are "Pathological liars like Musk and Altman are glossed over". I would say that requires at least sentiment analysis that an extremely high percentage(90+%) of hackernews users match that description. And that is simply not what I observe when I use this site. My feeling is that sentiment for Musk and Altman are neutral at best.
I will return with data.
> while pathological liars like Musk and Altman are glossed over.
You seem to live in a bubble where these people are worshipped ... :-(
The bubble you’re talking about exists, it is SF and the rest of the tech industry. It’s literally where the AI leaders are located, where they overhype each others
gestures broadly at HN and the tech industry
https://www.ycombinator.com/blog/ai-startupschool
I am a realist, I understand the cult of personality, etc. Just like I wouldn't spend a moment trying to talk a Catholic out of their faith. I have no feelings on the topic, this can only last so long based on capital trajectories.
> gestures broadly at HN and the tech industry
For me, HN ist rather some kind of counterweight/counterbubble where not everybody is insanely critical and cynical about Elon Musk and Sam Altman. :-)
> counterbubble
Gonna start using that one
I respect the bubble here for what it is. You've found your people, I hope it helps. I am a polite guest in this tribe's town square.
Edit: I am not asking for anyone to be overly critical of those I mention. Facts and evidence are objective, feelings are subjective.
Find Your People - https://news.ycombinator.com/item?id=44074017 - May 2025 (283 comments)
FWIW I think you spend too long on this site. I'm not trying to be mean but I see you much too often here having strong opinions thinly sourced and think that perhaps your time would be better spent elsewhere. I, too, spend more time than is healthy for myself on this site but think I spend a fraction of what you do.
I realize we've both been in this community for a long time but I think one of the things I find about participating in Reddit and HN communities over time is that, I stop both being able to separate the truth of a matter from the argument itself and I stop being able to conceptualize the people in the thread as people and not mouthpieces for argument. There's a special toxicity that arises on these sites, where the argument becomes the main issue at hand and I see a conversation as a large conflict between world views. I may be projecting my own feelings here, but think it's worth contemplating these hot button issues elsewhere and responding in a lower temperature forum more conducive to actual discourse.
The concern is noted and appreciated. I am here (as you mention, likely too much) to learn, to grow, to share, and to be curious. I don't take this place too seriously, and I hope you don't either, it's not meant to be serious. Take value from what you can, discard that which you cannot. I have enough, and so have more free time than most. I am a scholar first now.
> and think that perhaps your time would be better spent elsewhere
Open to ideas, propose where. I have...looked extensively for work with meaning and am coming up short. Mods have my email if you want to reach out. I am always open to being proven wrong and/or updating my priors. What needs to be built that is also worth building? I am always happy to contribute my time, energy, and resources to meaningful causes and work. I have done my best to be interesting to people who can provide opportunity, and yet find opportunity in the scope of meaningful work in short supply.
> Open to ideas, propose where. I have...looked extensively for work with meaning and am coming up short.
FWIW I've decided to view sites like HN and Reddit as "intellectual junk food." There's a feeling that one is engaging in intellectual betterment by using these sites, but in practice none of the outcomes valued in intellectual output fall out of reading and posting a lot on these sites. I can't tell you what you should work on; every human who wishes to be creative struggles with this problem.
Ultimately very few problems can be solved by talking endlessly about them, whether that's online or in real life. I suggest just trying to actually make solutions to problems if you want to use your time that way. Talking with others can be a great way to get energized about solving problems, but doesn't take the place of actually solving them.
I don’t understand the issue, cannot you ignore his commentary and just look at the numbers?
I'm not financially literate enough to trust my own analysis of the numbers. Ideally I'd like commentary from someone like Bloomberg's Matt Levine, a genuine expert in financial matters who is also extremely good at explaining them in terms non-finance-professionals like me can understand.
I didn’t even see the OP comment as a criticism of his analyses, just that he likes to do this rhetorical trick of dropping in numbers that are, at best, tangential to his point to prop up the argument’s credibility. Sometimes he does this in the middle of a real financial analysis which is even more maddening and confusing.
Fair, if you’re looking for reliable financial commentary Matt Levine is indeed the goat. Zitron is more like an old school blogger, with a very aggressive and corrosive style. My approach for internal documents leaked by Zitron is just to wait to see if Bloomberg picks up on the info or not.
No, you can't. The numbers are genuinely confusing, and Zitron actively works to make them more confusing rather than explaining what they mean because he needs them to sound as bad as possible. He also buries the numbers in thousands of words of prose!
The problem is that some numbers genuinely require a critical eye. If a source tells you that the OpenAI CFO told employees July ARR exceeded the Q2 total, there are a number of serious questions to be raised on how these numbers were calculated and what the point of such a confusing comparison is supposed to be. (I think the answer has to be that ChatGPT wrote the CFO’s script, no human financial expert would think to compare an annualized figure to the sum of three specific months.) But it’s hard to analyze the facts appropriately when they’re relayed by a guy who tells you that it’s all a giant scam and infers the worst possible answer to all the questions.
You're broadly right but I think you're dead wrong about the CFO statement — I think "July revenue alone exceeded all of Q2" is an extremely normal thing to say when revenue is going up at an insane rate. For example, if it was not true that June revenue exceeded March-May revenue, the point would be to show how their revenue growth has accelerated.
If he meant that he would've said July revenue, not ARR. ARR means it's multiplied by twelve.
She, and we do not have the direct quote. It's a paraphrase, and the report can't seem to decide whether they're talking about revenue or growth. If she was talking about growth, "the ARR growth in July exceeded the ARR growth of Q2" is perfectly coherent.
https://www.cnbc.com/2026/07/29/openai-cfo-sarah-friar-tells...
OP is way overinterpreting something we don't even have verbatim in a way that unfortunately resembles what they're rightly accusing Zitron of.
"July revenue alone exceeded all of Q2" would be a very normal thing to say, but you're skipping over some of the words. Unless revenue is sharply dropping, annualized recurring revenue in any month will exceed the revenue incurred in any quarter, because it's an annualized figure.
I think the most likely explanation is that the CFO misspoke and intended to say something more like your quote, or perhaps she spoke correctly and was misquoted. But without audited financial statements, all we have is speculation, and there have definitely been times in the past when executives of major companies made intentionally misleading statements about their revenue. (In fact, this thread began with a question about why you can't just look at the numbers, and here the answer is that nobody has reported the actual revenue numbers this comparison is based on.)
But you are using the misquote to do the thing Zitron does that you hate! I don't get it!
I didn't say I hate it. I've never seen any reason to doubt that Ed Zitron is a great guy who's working hard to tell the truth as he understands it.
My point is that any discussion of how a large, complex company is doing requires making judgment calls about which numbers are more or less reliable, do or don't matter, etc. This is especially so when it's a private company that has not yet any kind of meaningful disclosures. So if you don't think Ed Zitron's judgment is sound, there's no good way to adjust his commentary for that and "just look at the numbers", because the numbers have been filtered by his judgment even if they all came from accurate underlying sources.
Completely agree there.
> Given how fast these companies are growing (in terms of revenue and profit), it doesn't seem that AI is, as Zitron implied, some kind of desperation move they're reaching for because "they don't know how to grow" and are all out of ideas
Growth isn't a valid rebuttal, unless we can also sus out how much of that growth is tied up in circular financing of AI projects. We have a pretty good idea how much of Nvidia's valuation is tied up in the AI craze, it's a bit harder to tell with the megascalers....
You are confusing Capex and revenue.
The predictions were predictions of revenue. Circular financing of AI projects does not create revenue for OpenAI, Anthropic, Meta, or Google. Only Nvidia benefits from it.
Predicting revenue growth will stall and it does not was wrong.
Circular financing absolutely creates revenue.
A startup raises $50 million from OpenAI and Anthropic to finance API calls to OpenAI and Anthropic that they are using at a loss who in turn spend that money on compute with Microsoft and Google who in turn invest in Anthropic and OpenAI who then invest the startup using the startup’s revenue to value it… the cycle repeats.
There are multi-billion dollar valued startups invested in by OpenAI and Anthropic with hundreds of millions in ARR that are spending 90% of their revenue with Anthropic and OpenAI.
Situational Awareness, the fund that recently imploded, invested tens of billions into AI companies using their holdings in Anthropic to help finance the investments…
This could all work out fine in the long term, we’re all just speculating at this point, but the circular financing is absolutely making it to revenue because capital invested into startups is used to fund growth which is achieved by subsidizing costs incurred with OpenAI and Anthropic.
The vast majority of startups are not funded by OpenAI or Anthropic. They are not a significant source of venture capital. Meanwhile, OpenAI is pulling in $40B+ per year and Anthropic $65B+ per year.
You are mixing up valuations with liquid cash and you're also making sweeping statements about how those startups are spending their cash. A majority of a raise is not spent on AI compute.
Situational Awareness blew up because they used leverage to invest, and leverage is a great way to blow up any fund even if they were directionally correct about AI.
You’re applying pre-AI investing to a post-AI world. Yes, a decade ago, a startup raised money and spent 90% of it on people. The people built software which had incredible margins. Build it and then print money for ever more. That’s not the case any more, these startups no longer have incredible margins, they’re not collecting $100/m per user and banking $99 of it. They’re collecting $1000 and sending $999 of it to Anthropic and OpenAI.
Revenue numbers are vastly inflated compared to pre-AI but these startups aren’t keeping the money. Profits are worse than ever before. Startups with 30 employees that reach $100m ARR in 6 months are not banking $90m or $80m or… they’re just passing that money straight through to OpenAI and Anthropic.
If startups aren’t just funnelling all their funds raised straight through to OpenAI and Anthropic, where is this combined $100bn in revenue coming from? Who is paying for it? My spend on software certainly hasn’t gone up in a post-AI world. My company is spending less on software now.
OpenAI have stopped being so reckless with their cash investments which is why they appear to have slowed down but they’re still investing millions in huge numbers of startups through token allowances. They invest $2 million in every YC startup (or did a few months ago). There’s an entire market of reselling these tokens!
https://mlq.ai/news/openai-and-anthropic-pour-up-to-800m-a-y...
Hell, I’ll go one step further and bet they book these credits being spent as revenue.
As public companies, the megascalers publish pretty detailed financial reports.
Can you provide any examples of any of the megascalers publishing any detailed financials that touch on their AI spend or revenue or profit? The only one I’m aware of that comes close is Microsoft and they have still buried it in barely related line items which still leave us making assumptions.
There’s speculation on both sides and certainly Zitron is on the extreme end of the anti-AI side with the most cynical speculation but it is indisputable that none of the megascalers are open about their AI financials. Hence, we are all speculating endlessly. If only there were published financials then the speculation could end!
The obfuscation of financials doesn’t necessarily mean something bad is happening, it could be a competitive advantage for Google to be secretive about how cost effective their TPUs are or for Microsoft to hide how much revenue uplift they’ve experienced by adding AI to 365.
They don't publish their AI spending, revenue, and profit - but they do tend to break out other non-AI segments of their companies which can demonstrate that at least part of their growth isn't relevant to AI.
Page 24 of Amazon's 2025 report for example https://www.sec.gov/Archives/edgar/data/1018724/000101872426... separates AWS from the rest of the company.
Or Google/Alphabet's 2025 report https://www.sec.gov/Archives/edgar/data/1652044/000165204426... page which breaks out search revenue and YouTube revenue.
> They don't publish their AI spending, revenue, and profit - but they do tend to break out other non-AI segments of their companies which can demonstrate that at least part of their growth isn't relevant to AI.
So the previous statement that "As public companies, the megascalers publish pretty detailed financial reports" is incorrect and irrelevant to the question that was asked.
But you just wrote above "As public companies, the megascalers publish pretty detailed financial reports". Haha wtf is going on here?
Consider this original comment: https://news.ycombinator.com/item?id=49526069#49527546
I'll expand the section of the article that it quotes:
> Although this wouldn't be in the spirit of Zitron's statement, one could argue that Meta is actually dying, it just hasn't died yet. However, the reasoning in Zitron's argument is incorrect here—the Meta, Google, and Microsoft ecosystems are not dying. Given how fast these companies are growing (in terms of revenue and profit), it doesn't seem that AI is, as Zitron implied, some kind of desperation move they're reaching for because "they don't know how to grow" and are all out of ideas.
So the argument here is that Ed says those companies are dying, but Dan Luu points out that their economic figures show that they are not.
The counter-argument is "Growth isn't a valid rebuttal, unless we can also sus out how much of that growth is tied up in circular financing of AI projects"
My point is that the public reports of these companies, while not helping us unwind the circular financing, do at least show us that their non-AI businesses are growing at a healthy pace. Which supports Dan's argument that these companies are not dying.
Financial reports alone don’t paint the whole picture when it comes to valuations. For example, theoretically amazon has committed to invest 25 billion in anthropic, and anthropic has committed to spend 100 billion on aws compute. As far as we can tell, no real money has actually changed hands in either direction, but both valuations are being buoyed by their prospective investments…
They actually do not, they do not share details on their AI revenue and investments
Reports which are (un)surprisingly light on actual financial details regarding their AI ‘investments’ and any profits therein.
Because of accounting tricks, quarterly financials don't accurately reflect the size of this fiery money pit.
The datacenter build-outs are all majority (>50% ownership) financed by other companies, with a shell company owned by the hyperscaler as a minority owner. The data center then grants the hyperscaler an exclusive leasing agreement, and because the shell company is a minority owner, legally, it's not their debt.
The only reason this has worked is because there's such a long delay taking delivery on GPUs. When these capital allocators start paying for GPUs in data centers which haven't yet broken ground, then we'll see a very visceral market reaction. Some of that has already happened, but there's enough momentum that it can be absorbed and dismissed as an anomaly. But with governments unexpectedly passing moratoriums on data centers everywhere, it's only a matter of time before there's no data center to offload those GPUs to. That's when the music stops.
I believe that was Zitron's central thesis and why he started reporting on this. It mirrors the mortgage-backed securities situation that led to the 2008 GFC, except with even fewer guard rails to prevent financial calamity.
Investors are very savvy and keenly aware of what's going to happen. There's just zero incentive to pull the fire alarm and risk being blamed for crashing the market. If you're wondering why everyone's running toward the exits instead of treating these tech companies as 10+ year investments, you have your answer.
Over the past few years, I had helped Ed with some difficult nuances around the obscure technical aspects of serving LLMs (e.g. benchmarks and model caching); he has also shouted myself and Simon Willison out positively multiple times. I stopped assisting him because he repeatedly misused said advice to the most cynical interpretation ("how can this be interpreted to make AI boosters sound crazy?) and often made it misleading at best. Nowadays I suspect he views me as one of those crazy AI boosters.
Not challenging him was a mistake in hindsight, and I own it. Going forward I will no longer be helping writers/journalists with a clear anti-AI bias.
>I will no longer be helping writers/journalists with a clear anti-AI bias.
Take out the 'anti-AI' qualification, and you've got a decent general principle.
He made a blog post, literally last month, and it said that AIs have no use outside of coding.
It just shows he's done zero research on the things he talks about all day. Radiologists are using them, ad firms, artists, translators, law firms, auditors... It's hard to think of a white collar firm not using them.
This reads slightly weird and more like a pledge of alignment than a statement from the heart.
But apart from that, I guess that's always the learning? Journalists (or people labeling themselves as such) often have their own story they want to tell, and usually do so by building it out of little blocks of reality stacked together to form the desired picture.
I would predict a similarly frustrating experience being equally probable even without the "clear anti-AI bias" attribute set.
That's an unfair characterization of tech journalists in general. When BuzzFeed News was around, I worked closely with them on technical aspects and projects to ensure that everything was correct and accurate, and there were very receptive to it; it was not a "directionally correct" thing, the journalists wanted to avoid any unintentional. That was also one of the reasons I was open-minded to helping Ed even though we ideologically disagree: the truth is what's important.
BuzzFeed News incidentally was how I first came across Ed on Twitter from his tech PR work about 9 years ago, back when he was writing guest editorials on Gizmodo about Person of Interest (which is very very funny in hindsight). It's from the heart that I'm a bit bummed out that things turned out this way.
> February 2025: "I will keep writing this stuff until I’m proven wrong." Wrong (Zitron continues to write despite repeatedly being proven wrong)
Lol, I appreciate the sprinkling of well timed humor in an article that is mostly straightforward facts and analysis.
Upon further thought, I realized this should be counted as a correct prediction for Zitron! Zitron did indeed “keep writing this stuff until…proven wrong”. Zitron’s prediction says nothing about what happens after being proven wrong.
> In terms of the style of reasoning, of the futurists reviewed, he's probably closest to Kurzweil, in that he uses numbers to give a kind of aura of credibility, but if you know something about the topic he's discussing or look at the numbers, the reasoning falls apart.
In one of his posts a few months ago, he went on a weird tangent about the CEO of ServiceNow talking about sales planning and whether his teams are "on plan" or not. For people who haven't spent time in or around sales, this is an extremely common shorthand for quota tracking.
Ed's rant about how impossibly weird and inhuman the framing was revealed how little he knows, and cares to know, about the mechanics of the businesses he claims to profile. Yes, something like "on plan" is jargon, but a shred of reasonable journalistic curiosity (a Google search) would explain what it means and how it's a normal statement for a career-sales CEO.
>Ed's rant about how impossibly weird and inhuman the framing was revealed how little he knows, and cares to know, about the mechanics of the businesses he claims to profile. Yes, something like "on plan" is jargon, but a shred of reasonable journalistic curiosity (a Google search) would explain what it means and how it's a normal statement for a career-sales CEO.
This is precisely the sort of feedback an LLM could provide him before he hits the publish button, funny enough.
This is a common issue I face on HN as well. A lot of "folk wisdom" on here is divorced from how stuff actually operates.
Big shout out to Zitron. Everyone knows how to monetize good predictions (stock market, etc), but he might be one of the few who successfully monetized bad predictions, making him a step ahead of the rest of us.
Consider two propositions:
P1. AI is useful powerful and (P1a) will continue to get more useful and powerful at the same rapid pace it's been improving
2. AI companies are very profitable, and (P2a) will be wildly profitable (eg $30T TAM) in the next few years
These are completely separate. But in practice people seem to be either proAI (both true) or anti AI (both false). P1 is clearly true and I find it hard to take anybody seriously who says otherwise. P1a... Who knows, gotta hit a wall sometime. P2 I'm way more uncertain about (especially P2a) but it seems like people like Zitron reason backwards from hating AI.
I can certainly see one happening without the other, but I'd expect P1 and P2 to be correlated at least some of the time?
The most successful use of AI has almost certainly been advertising, which companies were already doing before the recent AI hype.
If by AI we mean LLMs, the question looks a bit different.
In my mind the most obvious scenario where AI gets used a lot but AI companies (exlc. NVIDIA / chip makers) aren't worth much is the hardware becomes capable of running the current state-of-the-art models locally, cheaply, and those models are basically "good enough" for 90% of tasks.
Sounds like the dot com bubble to me. many companies went bankrupt but the technology marched on.
Currently they don’t seem to be. At least OpenAI is haemorrhaging money left and right. Thing is, the compute for all this is far more expensive than anyone is willing or able to pay.
I’m not really convinced by any of this, in fact it seems most of the predictions were pretty correct and that Meta and Alphabet are having big issues is a shared opinion by multiple observers and pretty much every employee they have.
If they were doing so well why the layoffs? Why the tightening both in salaries and perks and work life balance? Why so many choices disrupting morale for their employees?
Help me understand where Meta and Alphabet's issues are. They seem to be doing quite well on paper -- nothing anomalous in terms of profitability or scaling recently. Layoffs are to be expected when AI can increase productivity.
Meta narrowly avoided disaster earlier this year: https://www.reuters.com/investigations/mark-zuckerberg-had-b...
The problem with judging Alphabet and Meta on aggregate performance is that their advertising businesses print so much money that they can invest everything in a boondoggle and coast when it blows up. Zuckerberg burned $100,000,000,000 on the metaverse and it didn’t make a dent.
That said, Alphabet and Meta are borrowing against their future advertising profits to fund their AI boondoggles. If the advertising businesses keep growing then they’re somewhat insulated from their own missteps but the reliability of the advertising business depends on companies having money to spend on advertising.
The metaverse was mostly self-contained and the failure had zero consequence for the broader economy. AI on the other hand, every major fund is investing everything into AI companies. Every advertiser is using subsidized AI tools to generate hyper specific adverts. If this all goes south, who knows how advertising spend will be impacted.
Google specifically are backstopping billions in data centre build out costs. They’ve committed to spending, like, all of their cash to data centres. If the market gets nervous and funding disappears, Google are deep in the hole.
Anthropic “invested” $50bn in data centers to be built by Fluidstack who raised a billion dollars from Situational Awareness who used their Anthropic ownership to raise money to fund these investments. Google are backstopping much of the Fluidstack build out, i.e: if Fluidstack goes out of business then Google is on the hook for $10bn+ in costs. And Google’s Anthropic investment makes up like $100bn on the balance sheet. So, Anthropic fails to live up to expectations and fails to pay Fluidstack who can’t pay their suppliers which puts Google on the hook to hand over tens of billions in cash while at the same time their biggest investment is going down the pan.
The top line numbers don’t really do justice to the scale of the risk. You need to look at the long term commitments they’re making.
Alphabet hasn’t had any layoffs, tightening of salaries and perks, or impacts to work life balance. Morale is quite good, imo as an employee
He didnt mention EZs claims about lack of data center construction compared to projected growth and valuation. I wonder if that was substanciated, since it overlaps with the bubble portrait of the "coming" wall of due service contracts hitting in 2027.
I don’t really care of anyone’s predictions, whether that of Altman or Zitron. I can make a prediction that sun will collapse into itself and stop shining. I would probably be right as long as I don’t give any too strict timeframe to ky prediction. In terms of Zitron, his style is that of a British tabloid columnist. It’s rather refreshing when most tech journalism is just selling gadgets, stock or whatever without questioning at all what either Musk, Altman, Amodei or whoever says. It aggravates many people because, well, it is suppose to.
Regardless of whether you love LLM’s as technology, the financial realities of Anthropic and especially OpenAI really does not look good. They have a massive expenditure that they need to keep going in order to make profits, which at least in terms of OpenAI are horrendously behind. Zitron published these numbers together with Financial Times, so you gotta give him that at least. Meanwhile the CEO’s talk all kind of nonsense and give their own predictions to get more investors money to fund what might or might not be the biggest bubble in the history of finance. I certainly do not hope this happens, since the consequences would be horrific. But there is likely to be a some sort of correction in horizon, since the models will plateau and they will run out of money at some point.
Let me finish with my own prediction. I think a lot of people are going to lose a lot of money some time next couple of years.
If we sample from Zitron’s claims, a lot of them are wrong. Probably most of them.
I think his contribution to the discourse is the bigger picture. These companies are going into potentially economy-wrecking debt over a speculative future that looks much foggier than the last two previous technological booms.
I've come to see Ed Zitron's dramatic predictions as reminiscent of a trend I noticed on YouTube a while back;
Whenever you'd look up anything pertaining to China's future, you'd inevitably find your screen plastered wall to wall with thumbnails of a photoshopped Xi Jinping, tears streaming down his face, next to large impact font text reading "CHINA WILL COLLAPSE IN X DAYS", with X varying from 1 to 30. Much like Ed Zitron's predictions, these events obviously never occur.
I find it ironic, that one of the most memorable articles Dan Luu has written imo is about how futurists faked 'exponential scaling' about semiconductors, and we ran out of the 'good kind' of scaling, Dennard scaling a while ago, and people interested in maintaining the narrative have been making up marketing numbers, which are believable to outsiders, but not to those who know:
https://danluu.com/futurist-predictions/
Yet, in this case, he takes the marketing numbers at face value, not being an expert in AI financing, while those who know more, can spot the sleight of hand, just like he can when it comes to semiconductors.
Who are the people who know more about AI financing and can point out the sleight of hand? I'd be interested in reading them.
I’m with Zitron on the frustration and even the analysis of the economic feasibility of AI.
What I’ve stopped doing is reading him regularly. It feels hard to parse the factual from the obviously exaggerated.
I get he’s frustrated. We all are. But I’m not sure letting it out that much helps making the very urgent case he’s making.
I don't think Zitron is wrong, exactly. He's just early. There are a lot of analysts who have faced the same criticism over the past 10-15 years. IMO the issue is that they fail to understand the staggering size and scope of the government fiscal + monetary interventions across those years. Essentially, the government has jammed all the risk into the future to repeatedly rescue near-term results.
I think something similar is happening with e.g. Amodei's predictions of mass unemployment due to AI. It won't happen in the immediate term, because deficit spending removes the economic incentive for firms to pare down their workforces.
All that said, I don't think these people are "wrong," per se. They're just early. When the sh*t hits the fan on all this, it's going to be a big problem. And, for example, companies whose primary business is collecting money for Internet ads will come face to face with the reality of how low value their products are. I have some insight into this, as I work for such a firm, and I know the true extent of the bot traffic out there.
No, hes been extremely wrong multiple times, he should not be treated seriously
Its silly to say hes just early, when his predictions give specific timelines that don't work at all
- "so egregious that I am surprised it's not some kind of financial crime to say it out loud" — on OpenAI forecasting $11.6B for 2025 (https://www.wheresyoured.at/exclusive-openai-financials/) actual: $13.07B. source is his own scoop (https://www.wheresyoured.at/exclusive-openai-financials/)
- "artificial intelligence has three quarters to prove itself before the apocalypse comes" — Mar 2024
- "If OpenAI doesn’t either reduce their $8.5bn operating costs to $1bn or less and raise at least $5bn in the next year, they will die." — Jul 2024 2025 costs: $34B
- Generative AI “isn’t getting much more efficient” (Jul 2024 ). OpenAI’s frontier-model API price fell from $30/$60 per million input/output tokens for GPT-4 to $4/$20 for GPT-5.6 Sol, alongside major capability gains.
- “I would be shocked if [Musk’s] wealth doesn’t return to something more like he had in 2019 or 2020” (Dec 2022 ). Musk is now worth approximately $873 billion , several times his wealth when Zitron wrote this.
sauce https://x.com/pitdesi/status/2093783287097602052
The actual quote and topic is far different than you’ve portrayed it. Here’s the actual quote: “ yet the company says that it expects to make $11.6 billion in 2025 and *$100 billion by 2029*, a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud.” from https://www.wheresyoured.at/oai-business/
He goes on to specifically discuss how unrealistic $100B by 2029 is given that OAI is structurally unprofitable.
The fact that you’re skewing your misinterpretation of what he said so much shows your own bias I’m afraid.
I think it's fair to call his specific predictions "early." I'm saying his timelines are too short. Like almost all bearish market commentators, he doesn't understand the scope of the government stimulus. This is a systemic problem in market commentary. But, don't kid yourself. If the US stops massive deficit spending, a lot of what Zitron's saying moves forward on the timeline.
It's not government stimulus driving this. It's that when you start with a "successful" company, the financial consequences of bad decisions or bad leadership can take a long time to have a negative effect, if at all, because financial success has a momentum to it.
I left Microsoft during the windows 8 cycle in large part because I could tell nobody knew what the hell they were doing, which is an objectively true statement about the time and place. My dad happened to buy Microsoft stock at that same time and did very well with it.
That's the paradoxical problem that I think all big tech has. Poor decisions by incompetent people, met with inexplicable financial success.
A prediction definitionally includes an outcome, and it _can_ include a timeline. (if you’re serious about your forecasting, then you generally include a timeline; forecasting is non-actionable if it does not include a timeline).
You might choose a different timeline for Ed’s outcomes. Okay: those are now your predictions, not his.
Zitron has done us the favor of including timelines with his predictions, so that Dan can invalidate almost all of them.
Would you say the 2012 apocalypse doomsayers were correct but just "early"? After all the sun exploding in a billion years will ultimately prove them correct.
What? No, they were correct; the world ended in 2012.
The world actually ended when harambe got shot in may 2016.
The US can safely reduce its deficit spending by $1 trillion and absolutely nothing big will happen.
The US typically adds that much annual GDP every 16-24 months at this point. The notion that somehow the gigantic ~$31 trillion economy will fall apart if the outsized deficits don't continue, is very absurd.
The exact same things were said of the Bush deficits. The US economy was supposedly dead in 2009-2010. Here in 2026 the economy is 50% larger inflation adjusted and it has left most of Europe in the dust. The housing bubble contagion was much worse than anything we're sitting on now with AI spend.
Why do I say $1 trillion instead of $2 trillion? There are plausible scenarios where increased taxes bring down the deficits (the Dems will take the House + Senate + Presidency, we'll see how much taxes go up), there's no plausible scenario where the deficits go away completely.
>> I think it's fair to call his specific predictions "early." I'm saying his timelines are too short.
That means his predictions were either wrong, or meaningless.
> OpenAI’s frontier-model API price fell from $30/$60 per million input/output tokens for GPT-4 to $4/$20 for GPT-5.6 Sol, alongside major capability gains.
on this specific point: tokens aren't fungible between models right? Like the argument Zitron makes is that improvements in output are due to, glibly, using more tokens to get there. We see people turn on new models and instantly use up all their tokens.
Like the actual measure is more something like "for this specific task, did it cost less now to do it than it did 3 years ago with these AI pipelines" right? The token pricing isn't actually relevant in that discussion.
If you're saying that OpenAI forecast something and you're saying it's validation that the numbers match the forecast, I don't think you're really paying attention to the problems (with annualised run rate bullshit when these are proper companies who could be publishing proper numbers), with unclear financials that are designed to look good, etc.
> He's just early
The whole point of making predictions is timing. I can tell you the US dollar will continue to devalue (a 100% accurate prediction). But it's a worthless statement unless I can tell you when and how much.
"I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be."
This was said in February 2024. This is months before GPT-4o released. GPT 4.5 was released a year later.
I don't know anyone holding on to models of GPT 4.5 caliber, yet know 4o. ChatGPT 4o and 4.5 score 8 and 14 points on Artificial Analysis benchmarks. [1]
For perspective, Qwen 3.6 27B, which can be ran on single GPU setups, scores 3-5x that on modern benchmarks.
I don't know why anyone would even make a claim like that in the first place. It's like saying "Computers are never going to get faster". I feel like we could run out of sand and still have faster machines over time. Just a silly thing to say.
[1] https://artificialanalysis.ai/?models=muse-spark-1-2%2Cgemin...
> I don't think Zitron is wrong, exactly. He's just early.
By that metric, so was Nostradamus. The apocalypse is coming for sure, we're just quibbling about the timeline.
Realistically, timing is everything. You don't need to get it precisely right, but you also don't get a pass if you, for example, keep predicting an imminent recession through a decade of unprecedented growth.
"Being right at the wrong time is indistinguishable from being wrong” - Howard Marks.
Worse, actually, because the knowledge that you're right will keep you from changing course.
After looking at Nvidia's orderbook, it's a reasonable conclusion that nothing bad will happen for at least another year. In which case Ed Zitron is off by at least a year.
But there are enough signs of trouble that could happen soon: Oracle debt is junk. OpenAI might not be on a viable trajectory to IPO. One or both of those could collapse the lower quality data center companies. Zitron is probably overconfident about a crash in the short term. Probably.
> After looking at Nvidia's orderbook, it's a reasonable conclusion that nothing bad will happen for at least another year. In which case Ed Zitron is off by at least a year.
Zitron is fairly clear that nothing is going to happen for a year or so — he says himself that he thinks there's another round of funding possible for both OpenAI and Anthropic.
Idk about that. A bunch of his wrong predictions were predicated on things turning sour sooner than a "year or so" than now.
Right, but you know the thing. The market can stay irrational longer than you can stay solvent. Predicting the medium future is hardest.
Markets don't just pre-plan their behaviour three years earlier and act it out lock-step. Other circumstances can change. By now, the world's financial press has covered some of the scariest aspects of this, and the situation has evolved.
There are other moves (the OpenAI/Blackrock AI debt securitization idea for one) that could delay it even further.
Zitron, I get the impression, has moved on to talking about the horsemen of the bubble apocalypse — talking about banner events that would need to happen for his predictions to be true. This is safer ground for a forecaster, because every forecast affects the future.
His shorter term predictions have not all failed by any means: he described Oracle's woes before the ratings agency downgraded them specifically because of OpenAI.
But most of his predictions will be irrelevant if the insane securitization plan happens. Because it will stop being about an AI bubble then; the worst risk will be the collapse of the entire US economy. It will need a different kind of analyst.
Me, I don't really care either way. I'm not on the cloud AI hype train, I don't work for a YC company, I'm not an American taxpayer so I will not be directly on the hook, and as Americans like to point out, the UK economy is behind on the whole AI thing so (unlike Ireland, which the USA will 100% leave to fail) we are ironically insulated. Maybe a couple of small British investment banks will fail and a pension fund or two will default.
For the most part we'll just watch the flames.
I do enjoy watching a Brit — albeit an ex-pat — upset a bunch of po-faced AI evangelists. It’s like “Itanic” all over again.
I think he is directionally correct. My own impression is that the bubble will burst at the worst time, and so my assessment is that, given the way this is entangled with the functioning of the USA as an economic power and with the future of the US political hard right, it will therefore darkly but poetically burst sometime around Labor Day 2028, which is the worst possible time.
I agree he is directionally correct, or at least is a vessel to raise important points and valid criticisms.
But predictions need to be specific and falsifable. If not, its just rag-chewing over a beer (luv that shit, but i aint predicting on taco tuesday). If they arent falsifable, then its not a prediction.
I think a lot of the HN comments generally can be described as one camp which cares about and enforces the rigor of predictions and trying to direct limited ear-time to voices which tend to get predictions right, vs the other camp that puts more weight towards directional accuracy.
Why would one ever predict anything at all if it was always falsifiable? Do you mean like eventually falsifiable? Like, I don't know about you, but I tend to go ahead and do any falsifying of something first if possible, before I resort to predicting.
Can you give an example of what a good/proper prediction might be, even in a hypothetical universe, in this schema? Does one "predict" when they play blackjack? Or is there a different concept for that kind of thing?
Falsifiable means able to be correct or incorrect. So if i said that my stepmom was kinda whelp, that wouldnt be falsifable, because like what does that even mean. But if I said my stepmom is going to be on her third marriage by the end of the decade, that is, because in 2030 someone can yell at me either way.
This is a spectrum of course: a prediction that OAI will collapse is probably right as _eventually_ all companies come to an end, but under that interpretation, the prediction is useless. It's more signal / useful / falsifable to say OAI is going to collapse around/at <year> due to <thesis>.
Anyway thats my two cents. Its fine to outline forces and trends, but when you make predictions there are useful (better, falsifiable) and useless.
I honestly don’t understand why you care so much about the “rigor of predictions”. Short-term predictions are almost always at least somewhat inaccurate, no matter who’s doing the predicting. Directional accuracy strikes me as far more important.
Take a look at the thread below yours, but basically if the prediction has to be wishy-washy or just interpreted as 'direction', theres way more noise and way less signal. Why not just state the underlying trend/forces instead? Why lean into the online culture of predictions and do it badly.
Bad (form) prediction: OAI is gonna be wobbly in a bit Good (form) prediction (could be totally wrong): OAI as we know it today is going to collapse due to running out of money around/at 20xx.
And sure we can be pedantic about detail, but the litmus test is: is the prediction useful if you had a crystal ball and you could know if it was true/false a priori?
Who cares about predictions to this extent? They’re practically always incorrect or flawed in some way, and most people understand and accept that. No need to be so neurotic about it.
That’s the crux of it!! You don’t have to agree but people do care, and I think (ignoring the obvious partisans) that’s the two dominant camps of commenters on this thread.
One pony’s trash is another pony’s treasure, so I guess here one persons pedanticism is another persons hobby.
Oracle fits in Nvidia's pocket at this point: $67b sales, $22b op income.
Vs of course Nvidia: $302b sales, $197b op income.
Oracle was never as big of a deal as that brief market cap run implied. The herd pushed it up for no reason.
The comparison to Apple, Microsoft, Google and Amazon are pretty similar. Oracle fits in their pockets too. Who cares if their debt is junk. Ellison has nearly wrecked that ship on numerous occasions over the decades. He went on an elaborate acquisition binge in the previous epoch, buying his way to the next stage (preventing Oracle from being market-eliminated, or acquired), and that was an incredible mess that took a long time to sort. He's doing the same move now, trying to spend to stay on the board as the world rapidly changes under his feet.
> Who cares if their debt is junk.
Non-rhetorical answer to your rhetorical question, but:
The near future of the political right wing of the USA is dependent on the Ellisons staying afloat to create an impervious right-wing media sphere that would survive the end of Fox.
The Paramount-Skydance/Warner merger is now delayed until 2027. Trump/the GOP needs that merger to go ahead, but if Larry's debt position worsens it really might not.
So you can expect the executive branch to push for the USA to backstop Oracle's debt in some way, whether directly or indirectly (taking some sort of stake in OpenAI to allow it to guarantee Oracle gets most of its money, for example — anything to get the credit rating back up).
It will be the first stage of this becoming a problem for the American taxpayer.
I don’t think you read the article, which documents many cases of him being wrong
For example saying in 2024 that LLMs had peaked. That’s not early, that is already, definitively wrong.
You can make that claim for the general case that genAI capabilities will plateau or fishy financing in the sector will cause trouble at some point, but not for the specific talking heads that haven't constrained themselves to that sort of "broad future trajectory" prediction.
FTA:
> Note that I didn't attempt to catalogue statements that are nonsensical or were simply factually incorrect statements at the time, such as his December 2024 claim that “Generative AI's products have effectively been trapped in amber for over a year.” January 2026 claim that "[models are] basically the same as they were a year ago. They have the same efficacy". Zitron has not only made forward-looking statements that AI capabilities will not improve, he's also consistently made backwards-looking statements that capabilities have not improved which, while obviously false at the time, seem to play well to his base (along with his other false statements). If you connect all his statements together, it's implied that AI had the same capabilities in January 2026 as they did in December 2023 (and if you connect later statements, it's actually implied that capabilities in August 2026 are the same as in December 2023, though to be fair to Zitron he frequently contradicts himself and has also admitted to limited improvement at times).
Yes. I was specifically referring to Zitron's circular-financing complaints. I can't defend his separate claims that AI just isn't that useful. If he were involved in the tech industry, he'd know how preposterous those claims are.
What predictions would you say he is not wrong, but just early about?
If his issue is that he is accurate on something shady going on with the finances of AI companies but the effects are mitigated due to government intervention, he should say.
Your explanation gives him more credit than I think he deserves. He has been unambiguously incorrect many times over the past years in the time scales over which he makes predictions.
In general, claiming that a prediction is just early in an unfalsifiable claim. It allows no admission of being incorrect whether you are correct or incorrect in a given moment. If you are right, then good, you've made a correct claim. If you're wrong, just claim there are clandestine corrective forces keeping the disaster you are predicting at bay. Either way you make it out clean and still have some sense of legitimacy.
Not sure about being early when it comes to points about models reaching the peak of their capability. Honestly, I don't understand how he's qualified (in terms of knowledge) to make such claims.
Being early is being wrong.
Being wrong about when a financial bubble will burst is different than being wrong that there is a financial bubble. That's the question, because if AI is driving a bubble, then it will burst at some point.
"Early" works for an open-ended bubble thesis. It does not rescue dated claims that already failed.
Google's 500 million Gemini-user goal had an end-of-2025 deadline. Zitron called it so unrealistic that Sundar Pichai should be fired. Google reported more than 650 million monthly users by October.
"AI had already peaked" is also a claim about the state of the technology at that time. Agent and coding benchmarks moved sharply after it. The fact that every technology eventually peaks does not make a past claim that it already peaked correct.
The bubble may still burst. That would validate the bubble thesis. It would not retroactively fix the prediction record.
btw Zitron has the only fan base that has come after me with doxxing and death threats so far. Truly misery loves company!
Some numbers have a lot of squish to them. Gemini can't be called a failure. But Copilot is a flop and yet Microsoft can probably show you similar numbers to what Gemini has.
But we’re talking about Gemini, which is one of Dan’s point: the surface area is so large that any prediction is almost laughable. Zitron’s prediction here is laughable in fact because he claims both (1) Pichai is jamming AI everywhere and (2) the 500M number is impossible. Those statements are immediately contradictory to anyone who understands the scale of Google’s products.
> The bubble may still burst. That would validate the bubble thesis. It would not retroactively fix the prediction record.
If it does not burst it will be because specific efforts have been taken to deflate it in the face of concerns like those he is raising.
The bubble may not burst for example if the securitization of AI debt really happens. Then when it happens it won't be an "AI bubble" that bursts, it will be a full-on collapse of the US economy. Like when 2008 happened it wasn't really about mortgages anymore.
Zitron is wrong, not "early", and the post has an extremely long list of examples.
in fairness, if you make the same prediction over and over again, you will probably be right eventually by sheer random chance.
Macrofinance expert Nathan Tankus has an excellent post on why the financing situation around the AI boom is just not big enough to mess up the financial system.
https://www.crisesnotes.com/sigh-no-ed-zitron-ai-bond-issuan...
I agree that the specific amounts invested in AI aren't enough to cause a calamity directly.
The problem is you have the vise of a stock-market decline on one side (something basically everyone thinks is impossible), and AI-induced unemployment on the other side (something a lot of commentators, including Zitron sometimes, seem to think won't happen). Those two things in tandem would be worse than 2009 by a multiple. I doubt the US government will be able to bail it out.
I recall a time when Google was struggling to monetize ads and then something changed and they started becoming profitable. The narrative was about improved targeting.
I think it might have helped a little but I never fully bought this argument. I don't think I've ever bought a product which was advertised to me online and I was using some of these platforms for years. I'm probably a liability to them; using up compute but not clicking on ads or buying anything.
Also when I ran social media ads many years back, I never got any users out of it. It literally seemed like mostly bot traffic back then; I can't imagine how bad the situation would be now with LLMs.
Did you read the post? The author cited very clearly a plethora of very specific predictions made by Zitron that were verifiably and factually wrong. False. Incorrect. Not “early”.
I've been doubting him myself (his recent articles just hedge on data centers more than anything else) but then I want to ask, are there any valid critics of AI? Not a "code is bad but it'll get better" but actual criticism in the nature of the financing, politics, etc. I think separating AI as a tool and it's capabilities and AI as product that needs to make a profit is helpful, however most people are really hedging in one camp or the other in their takes.
Cal Newport has been interesting on the topic. But it’s also possible to read Zitron and skip his personal opinions and just follow the discussion of financing, that’s what I personally do. I don’t understand why anyone would take the commentary of an internet pundit as a set of predictions to evaluate as gospel
I enjoy Newport myself, he's probably the most level-headed take I've come across. Everyone else has some agenda (or product) they're trying to get at and very much ruins the messaging (ex the agent 'civilization' piece is extremely overblown especially since..that's how multi agent systems coordinate already. Nothing happened that is unprecedented and isn't how the system is designed to work.
Check out the writing of Baldur Bjarnason. There are a lot of blog posts and a book outlining the risks and tradeoffs.
https://www.baldurbjarnason.com/2023/ai-position/ https://illusion.baldurbjarnason.com/
To shamelessly shill a passion project: A friend of mine and I try to be skeptical-but-reasonable on our podcast https://kairos.fm/muckraikers/ we aggregate papers and reporting and try to contextualize it with our own (hopefully useful) perspectives and takes
> however most people are really hedging in one camp or the other in their takes.
As with most things, most people are somewhere in the middle, as the silent majority. You only see the comments of the strongly aligned, which are also the most emotionally motivated to comment.
The internet is not real life.
The data center growth questions he raised have been where I found him interesting. I could never find any other articles to corroborate his predictions though. My question is when will the AI bubble burst?
I didn't know he'd had a long history of mispredicting AI quality and growth of companies like Microsoft and Google.
I ended up on this comment after looking through the linked article and realizing the words "data center" never come up in it.
>I think separating AI as a tool and it's capabilities and AI as product that needs to make a profit is helpful, however most people are really hedging in one camp or the other in their takes.
There are a myriad of people out there who have brought up genuine issues that AI presents, or preexisting issues that AI is exacerbating.
This series of articles is perhaps the best long form critique of AI as both a technology and an industry I've encountered [1].
[1] https://aphyr.com/posts/420-the-future-of-everything-is-lies...
Valid criticisms of AI
- safety critics who think AI can take over the world like Yud (I find this the least credible but still valid)
- Bernie type of critics who think AI can cause widespread job losses
- Ruxandra Teslo who thinks AI can remove meaning which I feel is the most serious one [1]
What are not valid
- environmental like emissions and water usage
- AI is useless and it will take the economy with it because it is a bubble
- AI spreads misinformation and causes societal damage
- AI is trained on copyright (are we really on this side of the debate ?!)
[1] https://substack.com/@ruxandrabio/p-213699661
> - environmental like emissions and water usage
Water usage, sure. But emissions has plenty of reasonable concern.
There are the various xAI data centers have/are running using mobile gas turbines.
In general, the extreme amount of power is going to put pressure on the grids. I hope this leads to the world doubling down on renewables to offset it all, but is that going to happen? Hell, the US actively paid [0] to stop a turbine project.
[0]: https://www.bbc.com/news/articles/c1e1vg0gjl5o
Water usage may be a drop in the bucket nationally, but they tend to put datacenters in areas without much water (often because evaporative cooling is less expensive in arid regions) and the effects to those local water supplies can be extreme.
What is invalid about the environmental angle? (aside from the dubious water claims)
I personally see it as:
These companies subsidizing green energy expansion, because it's now the cheapest power to expand.
These companies are going to help "correct" the widespread problem with utility monopolies, in the US. Datacenters are deploying their own power generation, partly because power cost no longer aligns with power generation costs. This mismatch is motivating research into local nuclear power generation [1] (which is almost certainly an effort to force the monopolies, rather than actually deploy).
[1] https://www.reuters.com/legal/litigation/big-tech-puts-finan...
> These companies subsidizing green energy expansion, because it's now the cheapest power to expand.
Unless you consider natural gass green energy, it's quite the opposite for the moment. This is because the AI build-out is about speed, not cost-effectiveness. That is why xai's Colossus I & II were illegally running gas turbines, and Google recanted its pledge for data center renewables targets.
> it's quite the opposite for the moment
This point is about power generation companies accommodating the new power demand. It's true that the power companies are keeping coal and gas peaker plants running, that they planned to retire. But, actual additions are all green [1].
And, step functions are inefficient, always, so "for the moment" isn't so unreasonable. Dataceners are something like 100 million tonnes of CO2 per year, where cars are 1,800! So, this isn't some world ending emissions, within this moment. Everything is trending green. Why? Because it's cheaper (thank you China).
Xai using gas turbines is closer to my second point of side-stepping monopolies (improperly in that case), but is also just one example. See previous link for very long term, and all the datacenters using green energy, mid term.
Everyone will do what's cheapest. Luckily, China has made that solar power. We just need to get the monopolies off their asses, and put some of their record profits into actual power expansion. Lucky for them, everyone blames the data centers for all of this. Where I am, the single power company has already raised rates so much, in preparation for electric, that it's more expensive to fast charge an electric car at noon than to buy gas, with a planned 10% increase over the next few years. So, they're dodging criticism too!
[1] https://www.eia.gov/todayinenergy/detail.php?id=67205
That's wrong. US battery energy is growing faster than ever, not in small part thanks to the push by data centers.
https://www.siliconvalley.com/2026/09/01/us-battery-installs...
Here's what I find invalid about environment angle.
I fundamentally don't think it is wrong to increase emissions as long as you consider the tradeoffs and externalities. Every single action you do in life has externalities - if you start opposing all of them then what really is your point? You just hate people doing stuff.
If you think emissions are so harmful, try putting a number to it. I implore you to do the exercise and convince yourself or me or others and suggest that the pros don't outweigh the cons. I'm half predicting that the conversation will end in dubious claims about tail risks and world itself collapsing (I hope you don't do that).
I don't think AI is uniquely harmful for the environment given the value it provides. Hell, it can even contribute to accelerating renewable resources and increasing efficiencies overall. There's way more to lose by slowing down AI because of emission control than to gain by reducing emissions.
> There's way more to lose by slowing down AI because of emission control than to gain by reducing emissions.
If AI works out as proponents would make you believe, then either you'll see masses of people out of a job - for which society is unprepared. Or you'll see a big, society-wide productivity boost. Read: consuming non-renewable resources on this planet even faster (not just energy).
Society as a whole would benefit if rollout would slow down. Give us time to reflect on those 2nd-order effects & how to address them. But instead we have the opposite: a crazy race with big AI labs trying to out-spend & out-do the other guy, ignoring externalities everywhere.
You are making claims for why you think the emissions are worth it but I don't see how this makes concerns about emissions invalid. Even water usage, while blown out of proportion, can be a rational concern if you have a fossil fuel power station.
You can just flip this around and ask why is slowing down AI to control emissions harmful? What numbers that don't make tail risk claims are you providing for this?
wait, please stick to the argument. Why is increasing emissions bad while considering tradeoffs?
>You can just flip this around and ask why is slowing down AI to control emissions harmful? What numbers that don't make tail risk claims are you providing for this?
Slowing down reduces the value it provides to humans, that's clear to me and you I hope.
Our current emissions level is causing climate change.
>Why is increasing emissions bad while considering tradeoffs?
Because climate change stands to be the biggest market failure in history. You need to show that the rapid scale out of data centers is going to reasonably offset the current trajectory we're on.
Another one: data centers making electricity more expensive while not contributing much to the local economy.
I think the three valid criticisms you listed are valid, but there are other quite a few other IMO-valid criticisms of AI. Here are a few as I see them:
- AI centralizes power in the hands of capital, rendering those who can afford compute hardware vastly more capable than those who cannot and thus increasing social stratification
- AI is generally trained on the creative output of humanity without those who train it giving back proportionally (copyright "rules for thee, not for me")
- AI breaks social processes built around the idea that TRYING something is inherently a cost in time or effort, such as filing a legal claim or sending someone a threatening letter. We haven't made the social changes to punish or charge people for using every appeal/option/application, so this makes asymmetric-effort tasks like applying for a job really bad in the interim
- AI use makes it harder to develop the ability to critically think for yourself, especially among those who most need to develop that ability
- AI produces large amounts of mid-tier content, making it harder to discover exceptional human-created creative content produced after AI started to exist
- AI leads to distrust in remote communication, increasing cynicism and breaking social bonds generally. This is NOT your point about "AI spreads misinformation" - no matter whether it's true or not that AI can be used to produce misinformation, having people doubt each other is a harm
- AI demand crunches hardware and time availability for other adjacent markets, such as computer gaming, construction, 3D graphics production, etc. This harms both hobbies and professions in those fields having to cope with rising prices and lower availability of materials
- Everyone is using the same or similar AI, leading to a homogenization of culture and process across humanity. This is perhaps a mixed blessing, because humans are capricious, but less variety can be viewed as a harm
I will also say I personally hate seeing "job loss" said to mean "wealth loss" or "people starving". The goal of life isn't to have a job, it's to be well and happy. If you can be well and happy without a job, great, so it's really painful to me how people don't even see those things are not the same.
> - AI centralizes power in the hands of capital, rendering those who can afford compute hardware vastly more capable than those who cannot and thus increasing social stratification
Looks to me like I can run Claude Code without being able to afford my own datacenter.
> - AI produces large amounts of mid-tier content, making it harder to discover exceptional human-created creative content produced after AI started to exist
That it does, but I think the real social evil is bad recommender systems. eg YouTube is basically on a mission to drive me insane because it literally only recommends me a) reviews of espresso machines b) video essays by autistic people about Mario 64 c) PBS scienceslop about how quantum physics is super mysterious. None of these are even what I watch, but they're also not what I want to watch.
> Looks to me like I can run Claude Code without being able to afford my own datacenter.
Until Anthropic bans you from using their data centers, at which point you cannot run Claude Code at all. Welcome to being a have-not (at least in a world where only genAI-assisted coding is acceptable).
He who controls the GPUs controls the world.
Unlike GPT (I think?), Claude is served by all of AWS/GCP/Azure and you can go buy it from any of them.
Whether Claude is or is not available via AWS Bedrock is entirely decided by Anthropic, not by you and not by Amazon. And you can't buy the data sets (the REAL power...) from any AI company.
> - environmental like emissions and water usage
Those are two very different things, and the former should be a serious concern. If AI does indeed become a double-digit percentage of electricity usage as the AI labs themselves predict, then it becomes a significant contributor to emissions, full stop.
This sounds completely reasonable:
> - AI spreads misinformation and causes societal damage
Agreed. And so are the other two, if stated reasonably instead of as strawmen.
Basically, all criticism of issues that affect real people is invalid per you.
> environmental like emissions and water usage
There is real crisis with warming this year, yes the plan to consume staggering anounts of energy and make environment worst in the process is valid criticism.
> AI is useless and it will take the economy with it because it is a bubble
If it turns out to be true, a lot of innocent people get hurt. Valid.
> AI spreads misinformation and causes societal damage
As valid as criticism of facebook was valid the whole time. And yes, facebook made world into worst place.
> AI is trained on copyright (are we really on this side of the debate ?!)
100% valid.
> safety critics who think AI can take over the world
Not valid, that is bullshit. If you think the word is wrong suggest polite word that says the same.
Yeah well, why not focus on Zitron's Oracle predictions? Article from May 27, 2025, when ORCL was skyrocketing.
https://www.wheresyoured.at/measures/
Now ORCL is back to $140.
I found this in two minutes via a search engine, but the star blogger Dan Luu apparently cannot handle that. I'm not a regular Zitron reader, but incidentally this blog post that came up in the search is several levels above Luu's post.
Zitron gets the big picture right.
From the blog:
> Although Zitron's past predictions have generally been wrong, maybe he'll be right about something in the future. Perhaps some of these companies will have valuations decline for some reason. But, even if there's some kind of massive AI crash and OpenAI and Anthropic go to zero, in terms of the societal impact, if on top of that, some other event occurs that prevents further progress in models beyond whatever AI labs have internally right now, that's still going to result in a fair amount of change. Which companies are successful will change who gets rich, but particular companies failing won't stop changes that fall out of current or next generation model capabilities from happening; it just moves around who benefits the most.
> If Zitron ends up being right about some company or other collapsing, that's pretty uninteresting to me compared to how capabilities have developed and will develop, where he's been wrong to date. It also happens that he's been wrong about the financial predictions he's made to date, but that doesn't really interest me, though I included a number of financial predictions for completeness.
Not sure how you can "get the big picture right" while having many egregiously wrong predictions.
So your guru Luu preemptively excludes evidence and you follow him? I'm not going to fact check all purported refutations from that blowhard Luu either.
I've literally never heard of this guy until today, they're not my guru. I am just showing where in the post the criticism was covered
You made a poor characterization of the content of the post and were rebutted with direct quotes. It happens, thats okay! Its not an attack on your character. There's no need to feel defensive!
Agree. Even Zitron's predictions about AI peaking are arguably correct if you step outside the silicon valley bubble. People I know who don't work in tech who use AI at work are doing the same stuff they were a couple years ago: they use it to summarize emails, generate an occasional slide deck, and mostly just send workslop to their coworkers.
And for personal use, I can count on a single hand people I know who pay for an AI subscription, and of those people nobody pays for more than the $20/month plan. And they all just use it as search or maybe to vibecode some one-off party game they use once and then throw away.
I don't know a single person who has done something like run Openclaw or leaves coding agents running on their laptop open all day.
I don't like Ed, but it seems that Luu spends far more attention documenting failed predictions than checking other predictions that might have been correct.
Telling me that quite a few of Zitron's predictions turned out to be accurate, while many others were completely off base, means he's throwing darts on a dartboard. Why should I listen to him?
I'm sure I can make a lot of accurate predictions. It doesn't mean I'm worth listening to, if people can't distinguish the accurate from the inaccurate in the moment.
Reminds me of a tactic I've seen often amongst both critics and shills on fads. An OpenClaw fanatic on Youtube comes to mind. He makes opposing claims in different videos. One of them has to turn out to be true, and he trumpets his successes ("Look, I predicted this!"). Only a few notice he also predicted the opposite.
Just look at the other thread about Zitron and his Enron comparisons.
What predictions have Ed made that were correct? And how do they weigh against the incorrect ones, in terms of both quantity and quality?
That's relevant because if you make a thousand predictions, a few of them might turn out to be true. That doesn't mean you're good at making accurate predictions.
Side-bar: I once hired Ed for PR for my startup. He was very difficult to work with, not even willing to share how he pitched our startup to publications because he considered the pitch his IP. So it was hard to know what was resonating or not.
I share this less to take a shot at Ed but more so that you all know to ask this if you ever hire a PR person.
This kind of back and forth reminds me of the Dot Com bubble circa 1999. There were endless articles saying that the internet was a new golden era for mankind and that the hyperbolic company valuations were justified; the detractors cried bullocks.
I use AI every day as I assume everyone else on Hacker News does. Will the S&P 500 drop 20%? I have no idea. If you know, please let me know so I can adjust by 401K.
Looking at the refutations of Zitrons predictions in TFA, it boils down to two categories:
1. Zitron claims model capability has peaked 2. Zitron claims AI lab growth (user and revenue) has stalled.
In the first case, TFA refutes by claiming 'wrong' repeatedly, which does not convince me of anything. If anything, Zitron is probably right in this regard, since the majority of progress in recent LLM tech has been setting up of guardrails to cajole the models using 'agents'.
In the second case, numbers are given showing growth, directly refuting Zitron. However, I'm giving Zitron the benefit of the doubt, given the old saying - market can remain irrational far longer than you can remain solvent. As long as people can be convinced that the sky is falling, rational predictions rarely pan out.
> 1. Zitron claims model capability has peaked … Zitron is probably right in this regard …
Is there some objective measure that you’d say show this?
> 2. Zitron claims AI lab growth (user and revenue) has stalled.… I'm giving Zitron the benefit of the doubt …
Is there some date by which you think it would be fair to evaluate Z’s claims and no longer give the benefit of the doubt?
What’s particularly bad about Zitron is his financial analysis. Some people have the idea in their heads that “yeah, Zitron is wrong about a lot of things, but his economic data and analysis is tight.” That couldn’t be further from the truth.
The entire AI industry, especially the vested interests, are often full of shit, sure, but the sheer amount of misunderstanding that has surrounded the economy and its relation to AI has been mind boggling. There is much bologna being accepted as reasonable or even standard by HN comment sections.
I was skeptical of LLMs making it to where we have them today, but the test results are evident, empirical, and hold up to hard scrutiny. I remain quite skeptical of a singularity event, GAI, and anything beyond what we've seen LLMs output today. It will get faster, cheaper, but not much smarter without another breakthrough. They will not be able to save the planet from their own pollution and overconsumption.
> but the test results are evident, empirical, and hold up to hard scrutiny
Sorry which test results? The gamed benchmarks?
https://x.com/victormustar/status/2094901703468306626
Danluu claims Ray Kurzweil's predictions are wrong. I asked
> list 50 predictions by Ray Kurzweil that he made before 2005, the date he made the prediction, and whether to not his prediction was correct. If it was correct, give some proof.
Of the 50 that were listed, 43 were correct, 7 incorrect.
Cannot take profits of these companies seriously when they have been laying off employees by the droves the past couple of years. Obviously profits will increase when workforce expenses have reduced. I'll only take it seriously after a couple more years and see how the company has held up with massively reduced workforce (powered by AI™). Another point would be to see how these incumbents get challenged by new startups and if incumbents can survive this phase.
I would be interested in seeing a similar list of predictions from Altman, Amodei, etc with annotations about how many have come true. Ed Zitron is a blow hard and frequently overstates things to the point where it is hard to take seriously, but so are the AI industry leaders.
I have heard multiple breathless press releases warning that the end of white collar work is "just 6 months away" and that people not using the latest Mythos/Fable/Whatever model will be hopelessly left behind.
Dan Luu's piece talks about this! He gives the example of Ray Kurzweil, who is similarly catastrophically wrong about everything, just in the opposite direction as Zitron. Luu's point isn't that anti-AI analysis is bad; it's that Zitron is bad. Zitron is bad in this analysis no matter what Altman says. It could be the case that Altman is also bad.
> He gives the example of Ray Kurzweil, who is similarly catastrophically wrong about everything
Is he, though? It seems to me that a lot of his predictions were surprisingly close to the mark, especially given how long ago they were made.
I'm convinced all of Kurzweil's predictions through the years can be simplified as (and originate from) "whatever least-implausible dream scenario allows a man of Ray Kurzweil's exact age and health to barely avoid the hitherto-universal icy grip of mortality."
I was awed by the future he promised, especially https://en.wikipedia.org/wiki/Respirocyte
Looking back, he’s great at selling a future of possibility as long as you don’t track all the errors.
This SMBC comic https://www.smbc-comics.com/comics/20100813.gif
Tangentially related in terms of "old stuff from other things I read", this 2006 critique [0] by Derek Lowe:
> Later in Kurzweil's article, he says:
> > "So what does the future hold? By 2019, we will largely overcome the major diseases that kill 95 percent of us in the developed world, and we will be dramatically slowing and reversing the dozen or so processes that underlie aging."
> [...] I really do expect to put cancer, heart disease, the major infections, and the degenerative disorders in their place. But do I expect to do it by 20-flipping-19?
It's hard to be optimistic when it's been those 13 years plus another 7 and somehow measles is back again, although I admit that's one isn't a pure technology-problem.
[0] https://www.science.org/content/blog-post/ray-kurzweil-s-fut...
But that's kinda the point, there's no such thing as "a pure technology-problem". I think that's the fundamental - and obvious - thing that these folks seem to constantly miss.
Luu's piece linked his analysis! Kurzweil scores 7% accuracy.
If you scroll to the appendix he grades individual predictions.
https://danluu.com/futurist-predictions/
Reading through them, Luu's grades seem fair and accurate to me. Best defense of Kurzweil I can give is that if you give a grace period of a decade and scope them down substantially (to maybe a subset of well-off Americans in coastal cities), he looks much better, though still under 50%.
One of Kurzweil's close-but-no-cigar failed predictions was "neural nets and genetic algorithms," killed off by the conjunction and being a couple years too early (2009 for increasing interest, and 2019 for wide use).
Fair, sure. But it seems to be underselling how reasonable Kurzweil is.
We've got things like 2009 - "Computers can recognize their owner's face from a picture or video. No." And ok, sure, but that has happened by 2026 and we have more than 2000 years of recorded history of people making predictions.
I don't think that situation reflects at all badly on Kurzweil except that he doesn't explicitly say he has a 15 year error bar. Which, yes, technically inaccurate, but it seems quite likely nobody would be talking about him if he spent that much time exploring the minor caveats.
And hitting him for the "and genetic algorithms" is verging on pedantry. Ok so genetic algorithms aren't a civilisation-level success that appears to be reshaping the fate of the species in the same way neural nets are. He was right that learning systems were going to be huge and he was off on a detail.
The list in the appendix is pretty telling: Yes, the moments are off by a lot, but many of the predictions describe reality well.
I'd say that 7% accuracy is on the low side and 86% on the high side. Looking through the list I'd put it more at 50-60% personally. For me that still means that I'd much rather hear about what he has to say about the potential future than most other people.
If you grade what was linked by whether it is "approximately achievable today", and not some less interesting metric like being predicted for the correct year or if it was outcompeted by some other thing, he's closer to 70-90% depending on how close you're willing to grade.
It's very easy to say 'person X made a highly specific testable prediction, while respectable people said nothing like it would ever happen, and it only 90% happened, so person X was a fool unlike all the respectable people', but it's a trap. In reality Kurzweil was directionally correct about most things, overspecified the details, and had optimistic timelines in the way that everyone has optimistic timelines about everything.
Kurzweil predicted in the late 90s that we will have AGI by 2029. And ASI by 2045. Seems very likely to me.
Altman and Zitron are like pro wrestlers. Their speech acts aren't for truth, they're for some spectacular effect on your feelings and your imagination that keeps you coming back for more.
I encourage anyone interested in this to read On Bullshit by Harry Frankfurt, the best popular philosophy work in a long time.
Ed Zitrons wild claims might be for entertainment value, but Altman’s are for his own valuation. He’s bringing in hundreds of billions of dollars off those claims.
Talking one's own book is a grand and ancient American tradition!
Without reference to either person, I think this is essentially a misunderstanding of Frankfurt’s analysis: On Bullshit is about expressing sentiments without caring about their truth value, i.e. the concept of a “bull session.”
Both Altman and Zitron are the opposite of Frankfurt’s bullshitter, because they both appear to evince genuine care for the truth value of their position.
(Frankfurt is very subtle about this, in that he distinguishes the kind of performative lying you’re suggesting as distinct in moral and rhetorical content from bullshitting. The liar wants you to believe a specific thing; the bullshitter wants to regale you.)
Bullshitting is where you don't care about whether what you say is true. Your goal is to influence a certain way of thinking or feeling, and you just say stuff that you think will cause that in other people. Appearing to care about truth is not opposed to that, it's part of it.
I don’t think these mental states are in evidence for either of them. I think they’re both credibly earnest in their views.
(Frankfurt’s characterization of the bullshitter rests on not just the truth value being absent, but also on the bullshitter’s misrepresentation of what he’s “up to.” I don’t feel that either Zitron or Altman is misrepresenting what they’re getting up to.)
So, you don't see how someone could both be "credibly earnest" and misrepresenting what they're up to?
Do you think misrepresentation has to be consciously deceptive? That it feels insincere to the person doing it?
I mean, the point of Frankfurt’s bullshitter is that we know they’re bullshitting (or more expansively, Frankfurt gives us a set of criteria to test them against). We know they don’t care about the truth value of their statement, only that they are misrepresenting themselves because of a hidden “enterprise.” But there’s no such unknown enterprise in either’s case, and neither appears to be misrepresenting themselves (to my point about appearing earnest). Maybe that latter part is itself deception, but without the former they would fall into Frankfurt’s classification of a “liar” instead.
(I have to admit a bias when it comes to Frankfurt: I don’t think On Bullshit is that convincing. In particular, I think Frankfurt doesn’t do a good job of motivating the connection between bull sessions and bullshit in his strong sense, and many of his examples - like the Pascal/Wittgenstein one - don’t demonstrate misrepresentation either.)
> Both Altman and Zitron are the opposite of Frankfurt’s bullshitter, because they both appear to evince genuine care for the truth value of their position.
I can't really judge Zitron, but when it comes to Altman, I have absolutely no idea how you arrived at that assessment. In my view, he's clearly dishonest. I’ll remind you of his attempt to use government intervention to erect barriers to market entry for his competitors. Or his claims about AGI being just around the corner—claims that haven’t come true so far and were clearly aimed at investors. I’ve never heard a single statement from this man that struck me as honest.
I think it’s appropriate in this day that people have to really shout and lament on and on about their thing just to get a few people to listen and/or consider parts of their argument. Nobody listens if you’re just casually proselytizing your grift.
Kurzweil made one big claim — Singularity around 2045. Everyone at the time thought it was a total joke and hundreds of years off, if even possible. Now, that is seen as a laughably long timeline.
The rest is noise, I don't care what minor predictions he was wrong about, he called the big trend back when nobody else could make a trendline.
The fact that you know Ed Zitron's name means that, regardless of his predictions being consistently wrong (which they are), his strategy for manipulating human attention has been correct.
The question is whether he sincerely believes his own predictions or if he cynically is aware that you can create a career for yourself being a guy who says bombastic clickbait-worthy things people emotionally want to be true, instead of measured assessments of reality.
Problem is, you wouldn't know Ed Zitron's name if every piece he wrote basically said "AI might be a bit overhyped short term but will have lasting economic impacts." Booooorrrring.
The reverse is also true. OpenAI and Anthropic aren't going to get much media attention if they don't make silly claims like "all white collar jobs gone in 2 years."
And no, this isn't a new problem due to "the algorithm." Media has always been like this. Zitron is just another Peter Schiff with younger skin. The problem is human nature in general.
Hence why AI isn't going to kill media. We don't actually want sober, rational assessments of all available information from hyper-intelligent LLMs. This is unsatisfying. We want emotional validation, drama, adversarial identity and spectacle. Truth is rarely what we are seeking.
I don't care whether he believes his own predictions, only that they're so frequently incoherent and false.
> his strategy for manipulating human attention has been correct.
"Correct" is not the word you're looking for here. More like "very effective". His strategy for manipulating human attention is very effective, but the correctness of his strategy isn't relevant here, so I'm not sure why you're bringing that up.
Because a sincere discussion of media (a fundamentally insincere medium with perverse incentives) is silly without addressing this.
Autistically pretending the world is rational and not factoring this in is just as false as Zitron’s predictions.
Nothing in acknowledging those perverse incentives requires that one misleadingly use the word “correct” in place of “effective”.
I'm going to need some evidence that Kurzweil was wrong. AFAICT he was right in 80%+ of his predictions with several more on track.
It’s linked in the article. The 85% accuracy is just shameless self promotion.
https://danluu.com/futurist-predictions/#:~:text=flowing%20i...
I'm going to need some evidence that Kurzweil was right in 80%+ of his predictions with several more on track.
I think you missed a "I won't respond further."
https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
What? no human in history has gotten anything 80% right. You're doing exactly what this piece complains about.
> Ed Zitron is a blow hard and frequently overstates things to the point where it is hard to take seriously, but so are the AI industry leaders.
Except that the AI industry leaders actually have skin in the game/are in the trenches and competing in the market. Ed Zitron wants you to subscribe to a newsletter so that you can read doom and gloom and...?
If you invested based on his advice, you'd have missed huge gains and/or lost money.
And I say this as a person who thinks most of the "AI industry leaders" are ethically questionable, at best, and ethically bankrupt, at worst, and that the stock market should be approached with caution due to valuations.
The fact is there is BullSh_t and hype on both sides.
Both Zitron and AI execs have good points, but both are trying to sell you something. The murky truth lies between the two extremes.
IMHO, having Zitron around is a counter to the AI leaders. Is he the best? No. Is he the loudest? Yes.
> multiple breathless press releases warning that the end of white collar work is "just 6 months away"
I'd like to see an example of this.
I think Altman and Amodei have been quite sober with their actual predictions. They've said things like "models can now do white collar work" but haven't yet said it is the end of white collar work.
The closest actual quote to this was in In March 2025, Anthropic CEO Dario Amodei told a Council on Foreign Relations audience that AI would be writing 90 percent of code in three to six months, and essentially all of it within twelve months.
I think that he underestimated how long it takes for technology to get uptake but in terms of capabilities he was perhaps 6 months out. I'd say that Fable class models are definitely capable of writing essentially all software, and that was released June 2026.
You could try checking the news.
> In a remarkable interview with Y Combinator in November 2024, Sam Altman, CEO of OpenAI, shared a vision that could redefine the technological landscape as we know it. Altman confidently revealed that OpenAI has a clear roadmap for achieving AGI by 2025.
https://www.tomsguide.com/ai/chatgpt/sam-altman-claims-agi-i...
Now Altman is claiming it'll be this year for sure: https://www.msn.com/en-in/news/other/sam-altman-makes-bold-a...
What specifically was he wrong about in either of those? I.e, something that can be falsified.
> Altman claimed that AGI could be achieved in 2025 during an interview for Y Combinator, declaring that it is now simply an engineering problem. He said things were moving faster than expected and that the path to AGI was "basically clear."
"AGI" isn't a useful term because - as noted in the article you linked - people disagree about what it means. Also his actual claim here seems to have been that the path to AGI was "basically clear."
That isn't a prediction that can be falsified.
Whoa, be careful, I think those goalposts just broke the speed of sound.
> Altman claimed that AGI could be achieved in 2025 during an interview for Y Combinator, declaring that it is now simply an engineering problem. He said things were moving faster than expected and that the path to AGI was "basically clear."
He was wrong that AGI was "now simply an engineering problem".
He was wrong that the path to AGI was "basically clear".
And if you want to play definition games and start waving your hands around and accept the claim "oh well actually we don't really know how to define AGI now", then he was wrong to claim that the path to AGI was "basically clear"!
Even if you play that game, it's still simple: either he was wrong about the path being clear, or he was wrong about the destination being clearly definable. That's still being wrong.
> He was wrong that AGI was "now simply an engineering problem".
> He was wrong that the path to AGI was "basically clear".
Why do you say that?
For context, Jensen Huang says:
> "For many tasks, we could say that we’ve already achieved AGI... I think of all of those milestones…they’re kind of senseless at this point.[1]
Even if you disagree with that, Altman's statement seems more about the idea that "more data + more compute + transformer based neural networks" will get us to something called AGI.
I think that statement is true. I guess you don't.
> if you want to play definition games and start waving your hands around and accept the claim "oh well actually we don't really know how to define AGI now", then he was wrong to claim that the path to AGI was "basically clear"!
No - because I think his and Jenson's definition means we have achieved AGI.
So it goes back to my point: this isn't falsifiable.
[1] https://mashable.com/tech/nvidia-ceo-jensen-huang-says-agi-a...
> Why do you say that?
Because he was wrong. That's how it works.
> For context, Jensen Huang says:
>> "For many tasks, we could say that we’ve already achieved AGI... I think of all of those milestones…they’re kind of senseless at this point.[1]
This statement is nonsense. It's Artificial General Intelligence that was promised. Not Artificial Some Things Intelligence.
> Even if you disagree with that, Altman's statement seems more about the idea that "more data + more compute + transformer based neural networks" will get us to something called AGI.
His statement was wrong. I don't care what other ideas you want to read into it, he was incorrect about AGI arriving in 2025. That's all there is to it. Twist it into a knot and smear butter on it if you want, wrong is wrong.
> No - because I think his and Jenson's definition means we have achieved AGI
Yeah they can twist definitions all they want. I don't really care. We have seen that LLMs and transformers have not delivered AGI, and they certainly didn't deliver it in 2025.
> Because he was wrong. That's how it works.
> His statement was wrong. I don't care what other ideas you want to read into it, he was incorrect about AGI arriving in 2025.
No
Sam Altman never claimed we'd get AGI in 2025. That is Tom's Hardware incorrect headline.
Altman's quote is:
"I felt like we actually know what to do like I think from here to building an AGI will still take a huge amount of work there are some known unknowns but I think we basically know what to go what to go do and it'll take a while it'll be hard but that's tremendously exciting I also think on the product side there's more to figure out but roughly we know what to shoot at and what we want to optimize for that's a really exciting time.."
See here: https://youtu.be/xXCBz_8hM9w?t=2327
It's not Altman's fault that people misreported him.
All in all, it's clearly the AI skeptics that have egg on their faces. Sam Altman is very flawed and you could make a strong argument for why that's why he blew an enormous lead to Anthropic. Dario's predictions in general haven't been that far off. The general public is becoming increasingly aware of AI as a big deal (and something about 60% hates). Our jobs, regardless of where on the adoption curve we are, have undeniably changed a lot.
Zitron and a whole lot of people on HN were trying to claim this was a nothingburger or at least no more important than the invention of IDEs up until Dec 2025, and then all of a sudden everyone quietly shifted what the "reasonable" opinion was. If I were those people, I'd spend more time taking a look at what was wrong with my priors than look outward.
Note that no one ever quotes the end of Dario's line, either, where he said programmers would still be needed in that 12 months. People think the prediction was more extreme than it really was because all the clips didn't include the latter part.
> .... and in 12 months, we might be in a world where the ai is writing essentially all of the code. But the programmer still needs to specify what are the conditions of what you're doing; What is the overall app you're trying to make; What is the overall design decision; How we collaborate with other code that has been written; How do we have some common sense with whether this is a secure design or an insecure design. So as long as there are these small pieces that a programmer has to do, then I think human productivity will actually be enhanced
I think one important distinction is at least they have some humility to admit they were wrong. I think Ed Zitron has rarely, if ever acknowledged he was wrong.
I actually think you’ve got it backwards
I think one of Zitron’s problems is that his moral righteousness has blinded him to how embarrassingly incorrect he is about the AI space.
It’s similarly hubristic with the benefit of shielding from his adversarial framing.
I see this so much. "This shouldn't work, therefore it won't work." It's like the world is imagined to run on a moral causal framework rather than uncaring quantum mechanics.
I have watched many of his screeds; I think he undercuts his thesis with excess bile.
His core observation is that the unit economics of openAI and anthropic don't actually yield enough profit to pay off the huge debts that these two companies have incurred, and that as a result all the debt they've taken on will have to be written off which will trigger "the hyperscalers" to themselves suffer huge losses (likely wounding google and microsoft and destroying oracle).
He is rather more negative about the utility of LLMs than lots of other people (myself included); but his overall view of
seems pretty reasonable. There seem to have been lots of bets placed on the hope that this stuff will continue scaling as it has in the past, if it is given more compute and data, and that bet is one that has yet to have demonstrated itself as correct.Elsewhere, people have pointed out that many of the "FAANG" companies have shed lots of people and driven lots of profits, largely on the back of internal use of LLM tools. That doesn't necessarily contradict the skepticism that anthropic and openAI will succeed, and given all their obligations, if they fail it'll be a big mess.
But again, big Z doesn't do himself any favors when he rants about "failsons" or whatever.
Seems to me it's a reasonable position that runs face first into the irrational market.
Like they're digging a gigantic hole and Ed's up the top saying if you keep digging the hole will collapse (+ a whole lot of unnecessary swearing), and then a bunch of people jump into the hole to brace it and say "nuh uh, see we can keep digging" but really it's just postponing the inevitable and increasing the number of people who will be destroyed when it all crashes down
> I think one important distinction is at least they have some humility to admit they were wrong.
I'd be amazed to see a source proving that statement. There's never been a retraction around the AGI claims for example as far as I'm aware.
I can't find a counter to every statement they have made and not sure about your specific AGI claim but.
https://www.youtube.com/shorts/QMhtTO3u61A https://www.youtube.com/watch?v=L_ueDUrkOlQ
Examples of acknowledging he was wrong
I only watched the first one so far but you misunderstood what he says, he doesn't admit being wrong at all, in fact he doubles down on wrong claims.
Interesting; he is clearly saying that they were ("as a field") "confident and wrong" to believe that "the economy would have been completely upended" by the appearance of a model as strong as GPT4. What seems to be missing, from your point of view, to consider it an admission of being wrong?
Humility? I don't think they know what the word means let alone possess the capacity to demonstrate it.
Altman has admitted that some things are taking longer than he expected, and has walked one or two things back (usually to keep people from throwing bombs at his house, but still...)
Zitron continues to boast of a predictive record entirely unblemished by accuracy.
When Altman “admits” things it seems more manipulative than humility
The until Anthropic et al IPO to the tune of trillions Ed is more right than he is wrong.
Man, as a former extreme skeptic, I watched a video from Eric Schmidt in early 2025 where he said that by the end of the year nobody would be coding, and that one was dead frickin on.
As far as I'm aware, aside from toy prototypes, all software is still built by humans coding, albeit with better auto-complete.
This seems to be more a problem of your awareness than a lack of projects.
Apart from every software engineer I know building almost completely with AI now there have been numerous projects posted on HN that are AI coded.
There's also Claude desktop which is famously all AI built and very widely used.
> now there have been numerous projects posted on HN that are AI coded.
Yes, all of which are toy projects and get criticized every time they are posted. On actual serious projects, not someones pet home project, I've only seen "vibe coding" used in very low risk places like small UI components. And even then they are generally heavily tweaked after the fact.
My anecdotal personal experience seem to agree with the general sentiment I see here on HN. Some people or companies do it, but with generally heavy criticism.
Have you ever considered:
- that you don't know most people in the world
- that some of the people you know are using these tools because they were forced
?
> that you don't know most people in the world
Of course.
To be clear, the claim was "all software is still built by humans coding"
I know this all software claim is false because I've seen it. Proof by example.
> that some of the people you know are using these tools because they were forced
Irrelevant to that claim.
It is all very unevenly distributed. SaaS and general web is basically on auto mode.
A lot of infra is vibe coded nowadays too.
Even prototypes are contributing to the speed of software development. Many people vibe code throwaway dashboards around the main platform which gives a lot of insights.
I guess I don't exist...
I guess the GP is joking. But on the current climate, it's really hard to be sure.
Everyone who started using claude clode when it came out in early 2025, knew it was coming (not quite yet). That felt more like reporting than prophesying.
There are whole industries that still don't let LLM-generated code touch production
You may be living in a bubble. There are tons of developers still coding by hand, and many industries that don't trust machine generated code in general.
It does raise the question, what percentage of programmers are predominantly writing code by hand? Is it higher than 50%?
Do they also not trust their code review processes?
Have you considered that they do trust their code review processes, and that they don't trust the generated code because it doesn't pass their process?
> they don't trust the generated code because it doesn't pass their process
That's not a credible scenario. Developers can either make changes by hand, or by asking an LLM, which is the common process when there is a downstream failure. Humans dont metaphorically throw their hands up and say "well the tool doesn't meet our expectations at every scale so we're not going to use it". Granted, most developers scale back how much they rely on it based on experience (good and bad).
That's very much a credible scenario. I think I use code from SO in a single digit of occasions. But I use it a lot more for giving me insight like a keyword for doing a proper web search. Or the name of a flag for a cli command, or the general shape of an algorithm or what to check in a troubleshooting session.
I won't generalize, but it's very rare for me to need code as most of my diffs are either boilerplate (generated with a tool or copied from docs or samples) or core logic that is mostly the translation of some design that I've already spent hours or days on. My core issue has always been incomplete specs from Product or incomplete docs for some tool/sdk/library (alleviated by having access to the source code).
Generated code is just not that useful, especially when designing the core architecture of a new project. And later it's not that useful either as the specs (why and how) is more valuable than any code (what).
I don’t live on a coast and I have a large and broad social network. I don’t know anyone who still mostly codes by hand except the small amount needed to preserve some aspect of their skills. I’m sorry to say that if I did I’d consider them foolish. Even a very restrictive workflow where you used an LLM to specify granular edits you intend to make is vastly faster than doing it by hand. And the level of test coverage and depth you can achieve now is simply life-changing.
It’s much more likely that you are not a professional, or you are the one in a bubble.
>Why wouldn’t careful human code review and extensive test coverage suffice?
I have come to understand that LLM generated code, even when carefully reviewed, ends up being hard to review as time progress.
This is because when you are coding yourselves, you get a first hand sense of the complexity creeping in. Then you refactor some stuff to keep complexity in check. LLMs does not "feel" such friction, and will happily keep adding on complexity until meaningful reviews are impossible beyond a certain point.
At this point, you need an LLM to review the changes and at that point, all bets are off.
This is a very good point. So many times I would refactor entire parts of the code base just because it’s getting too complicated and an easier solution was possible. AI is do often just let’s drill down all these variables, whatever
So no one is in control at the wheel? Just press a button?
I can see in the future in school or on the job. Oral testing is coming back. You’re gonna have to explain everything you are doing at some point to your teacher/boss or to a panel of your peers in detail.
> Which ones?
Any that value correctness over speed. Banking, safety critical embedded work, aerospace work, etc.
> Why wouldn’t careful human code review and extensive test coverage suffice?
Because anyone who has been in the industry for a while knows that code review is not a substitute for intentionality and understanding when writing the code. To properly validate a change you must fully understand the intention behind it and the design at play, and then check the changes made against the system design. That is best done by a human subject matter expert (this is the role which software developers have traditionally filled, for anyone new to the industry).
> I work in one of the most conservative and highly regulated industries in the country. My company and every single one of my peer companies I have knowledge of has transitioned to almost exclusively 100% LLM-generated code (with plenty of human review).
That's called "being in a bubble".
> I don’t live on a coast and I have a large and broad social network. I don’t know anyone who still mostly codes by hand except the small amount needed to preserve some aspect of their skills. I’m sorry to say that if I did I’d consider them foolish.
And I think it's foolish to let your coding and critical thinking skills atrophy like this, but you do you.
> It’s much more likely that you are not a professional, or you are the one in a bubble.
Not even worth a reply.
I have connections in most of the industries you named and I can promise you that they are no different. I don’t particularly care whether you believe me, but I encourage you to self-examine to understand whether what you are saying is what you would like to be true (I do too!) or whether it actually is.
> I have connections in most of the industries you named and I can promise you that they are no different. I don’t particularly care whether you believe me, but I encourage you to self-examine to understand whether what you are saying is what you would like to be true (I do too!) or whether it actually is.
You are literally talking with a professional developer who is telling you that they don't use LLMs to write their code and that they have connections who also continue to do this work manually.
I don't particularly care whether you believe me either, but I encourage you to take a look around - your initial claim that coding has been automated across the industry is incorrect and you seem to be in denial about that for some reason. You should question where your priors are coming from, and remember that just because your circle is comprised of people who are heavily using LLMs does not mean the entire industry is that way.
Of course I believe that you act as you describe. But you are not an industry unto yourself.
I apologize for questioning your professionalism and wish you all the best. Truly.
On a second reading I'm going to take this as sarcasm.
I mean, I code?
Dario Amodei and Eric Schmidt seem fairly well-calibrated, although a bit early. Elon Musk is constantly way, way overoptimistic (perhaps to the point of willful fraud). Zitron is hopelessly and ridiculously incompetent (and there are allegations he is willfully lying, too, but who knows).
The AGI that appeared mid 2023 and killed single every person in 8 months was neat!
Live long enough and all these apocalypses start to smell the same.
Yep I distinctly remember at the beginning of 2023 that folks were predicting that we were less than two years away from there being no jobs for software developers. Pretty soon we'll reach double that timeline.
And of course it really has changed everything! But that was not all that a lot of people were prognosticating.
My bet is that Amodei's claims about the dangers of AI are the most likely to come true – I'm predicticing amodei/anthropic will become the evil it was against.
I predict they go bankrupt.
Those claims are warnings if you're working class, and marketing if you're corporate.
No, you see, they were right all along, they just "didn't anticipate the public outcry against data center expansion", thus the obviously inevitable AI takeover of the economy is being slowed by NIMBY curmudgeons who should be ignored and punished.
The 5090 Nvidia card evidently is selling for five grand now! It’s just a question of when the bubble burst….
The end of white collar work mean that company can finish all jobs by new model.
To be fair, Zitron's career is as a commentator. To some extent, I expect CEOs of companies to make ridiculous claims. At the end of the day, when shareholders come knocking, what they care about is whether or not your company is growing.
No such mechanism for social media personalities. You can be wrong 90% of the time, and your audience will still praise you for the 10% of the time you were right.
> To be fair, Zitron's career is as a commentator. To some extent, I expect CEOs of companies to make ridiculous claims.
This is not a comment directly at you, because I understand where you're coming from, but I think this attitude shows how far leadership and our expectations of the professional class in America have deteriorated.
My expectations are inverse to yours. I don't care if a commentator makes a claim that's wrong, if they keep being wrong people will stop listening. (In theory. Jim Cramer still has a job so who knows, really.) I certainly don't expect a commentator to have accurate internal information about a company.
CEOs on the other hand should be expected to be honest and accurate in their claims. The information a CEO shares should be accurate so that investors can make informed decisions. Instead, we seem to accept CEOs who act as salesmen first and leaders last.
If a CEO claims a product will be out later this year, and the stock goes up, then they announce actually things are delayed, and the stock still goes up, what is actually being rewarded here?
CEOs and leaders used to trade on credibility.
I don't think of Zitron as a journalist, I think of him as an entertainer, no different from all the columnists paid to tell people that what they already think is right.
The fact that you're holding him to a higher standard than fabulously compensated professional c-suite officers whose products are used in matters of life and death is... kinda weird?
The big difference is that Altman et al aren't just, or even mainly, pundits or prognosticators. Zitron's whole thing is commentary and predictions about AI and his predictions are almost all wrong.
Altman and friends are mainly actually making and delivering AI. If they also hype their timelines/valuations, they also seem to make directional progress on the goals.
Here's an example https://en.wikipedia.org/wiki/List_of_predictions_for_autono...
But I think anyone who evaluates their claims understands that they’re talking their own books.
Zitron’s problems are more subtle. He benefits financially from his own claims, while also touting his impartiality and capacity for objective thought.
A person savvy enough to understand the indirect financial benefit to Dario promising that Claude is so dangerously smart it must be regulated understands Zitron’s schtick
Not very. I like to always watch both sides of this issue, the people who are optimistic, pessimistic, doomers, etc... He is someone who in my opinion misunderstands the bigger picture. He often downplays the capabilities of these systems, doesnt think they will be more powerful in the very near future and also more importantly makes a fatal misunderstanding that we live in a rational world with rational actors.
I don't really care what Zitron says or pay attention to him because it seems clear to me he has some kind of agenda.
But this article is not nearly as impartial as it claims to be. It interprets all Zitron's claims in a narrow and overly-literal way. Missing the point and refuting a technicality.
For example, looking at the last 3 year's revenue/profit growth. This tells us nothing without looking at a larger context. Has revenue growth slowed down? Have profit margins compressed? What makes up the income and has that changed? Etc.
I think anyone being intellectually honest understands that these tables alone don't refute Zitron's claims that big tech are "dying and thrashing around" which is something that could take many years and easily hide under these kind of top line / bottom line numbers. (Maybe further analysis would refute the claim, but that analysis is not present here.)
Or Zitron's claims that AI capabilities are "reaching the upper limits" back in 2024. I don't think even Zitron would disagree that AI capabilities have grown since then, but that doesn't refute his point. How long the "reaching" takes and how wide the "upper limits" are is completely up to a subjective interpretation, which this post makes no attempt to even explore.
By all means dunk on futurists. But at least steelman their positions or you look just as biased as them. (Although maybe I am off base and this bias is meant to be clear from the start by admitting to pro-AI predictions all the way back in 2015.)
Yeah, I think this is fair criticism, and I definitely felt the pointedness in the tone as well.
On the overly-literal / narrow thing, I think thats the culture around evaluating predictions overall. Like, all those posts around christmas where people make predictions and evaluate how last year went. The rigor is the norm.
He is a bit more of a PR person rage-farming disguised as a futurist. He's not optimizing for correct predictions. That's really hard and not his incentive.
Look at his incentives. It makes more sense.
There's a demand for loud and confident "AI tech will fail" and "big tech will fail", so it pays to peddle the goods.
A lot of people desperately want AI to be a nothingburger. Thus, they will seek a second opinion that just so happens to line up with their existing one. Wishful thinking at its finest.
There are an even larger amount of people who have gotten tired of the NFT levels of pushiness AI has become from a financial perspective. It's become worse than crypto bros at this point.
Sometimes the thing being pushed as "the next big thing" is, in fact, the next big thing. Regardless of how annoying you find the push to be.
Push is fine, to the detriment of society and farcical levels of current usage is a bit of a problem.
I’m going to be so happy once these morons ipo. No point in running the ai spam accounts at that point.
pragh@ (Prabhakar) (yes his ldap is an anagram of graph) absolutely gutted the fire wall between search and ads.
To pick a specific piece of public information to support my claim: the previous SVP of ads quit immediately before the coup to start a subscription based search engine.
One nonpublic piece of information: basically every member of search leadership was pushed out within two years of his ascension.
Do his predictions about the datacenters being a risky and unprofitable business suffer the same fate as the others?
Zitron has become the distorted reflection of the very AI boosters he criticizes and mocks.
I think the worst thing that happened to him was AI skepticism becoming a political position. This gave him a captive audience - as long as he says what they want to hear, which means that he can never ever concede that he might have been wrong or that AI might actually be progressing or having successes.
This is not conducive to good prediction long-term - rather it leads one to a state of cognitive dissonance where one's chosen enemies must be simultaneously terrifyingly powerful and incompetent dunces. The propagandist's disease.
How? AFAIK, his arguments based around the economics remains the same, he just seems increasingly dramatic and exacerbated, which is understandable when you realize industry + ecosystem (politics/reporting) is tulip mania delulu and insists 1+1=100, or 30 trillion, or whatever. His position isn't based on AI progress - it's based on AI economics, at this point he can be an obnoxious rationalist slamming flat earthers - just because he's annoying/smug doesn't mean he's less right on fundamentals which if anything is more clear now.
> you realize industry + ecosystem (politics/reporting) is tulip mania
It could be "tulip mania" or it could be "the internet".
Luu analyzed the numbers instead of just reacting to hype.
Specifically:
>> Oct 2024: OpenAI's forecast of $3.7B revenue in 2024 and $11.6B in 2025 and $100B in 2029 are absurd, "a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud"
> Wrong (2025 goal exceeded, 2029 TBD but not an egregious financial crime level of implausible)
>> February 2025: Anthropic making $34.5B in revenue 2027 is "is laughable on many levels, chief of which is that OpenAI, which made around twice as much revenue as Anthropic did in 2024, barely made a billion dollars from API calls in the same year."
> Wrong (whether or not they make that in 2027, their 2026 ARR greatly exceeding that makes the 2027 estimate non-laughable)
On a spectrum between tulip wilting and fiber build out, we know deprecation cycle of DC hardware leans towards tulips i.e. <10 years (very generous) vs 20+ years for fiber layout, a lot of which is actually infra/earth works etc.
The numbers being cited is ~100B is well within accounting/ledger maxxxing tricks relative to current pool of investment. Luu is not analyzing number's he's just listing and believing numbers, and analytically entirely avoids the core Zitron thesis... once you tap out of easy investor $$$, FAANG warchest, accounting tricks... where is the rest of the order magnitude more $$$ that justifies existing spent relative to time frame coming from?
> On a spectrum between tulip wilting and fiber build out, we know deprecation cycle of DC hardware leans towards tulips i.e. <10 years (very generous) vs 20+ years for fiber layout, a lot of which is actually infra/earth works etc.
Counterargument: As advancements in transistor densities slow down, the rationale for increasing depreciation cycles makes more sense. As the performance gap between new & 5-year-old hardware continues to shrink, then the need to replace older hardware similarly shrinks, justifying longer depreciation cycles.
> we know deprecation cycle of DC hardware leans towards tulips i.e. <10 years (very generous) vs 20+ years for fiber layout
[1] is a reasonable discussion of DC cost models, which calculates depreciation as part of the annual cost.
> here is the rest of the order magnitude more $$$ that justifies existing spent relative to time frame coming from?
That money comes from long term debt (ie bonds by public companies[3]) and new investment into neo-cloud companies (ie, IPOs like 4).
The justification comes revenue. Eg, the NScale IPO above[4] has $51B in long term contracted revenue with an annual run rate of $500M.
[1] https://epoch.ai/data-insights/ai-datacenter-cost-breakdown
[2] https://www.cushmanwakefield.com/en/united-states/insights/d...
[3] eg https://www.yondrgroup.com/newsroom/press-release/yondr-secu... (but you'll find lots of similar bonds issued)
[4] https://dealroom.co/news/143730-nscale-eyes-september-us-ipo...
This narrow focus, of course some intermediaries in industrial chain is going to make $$$ selling/renting shovels - there is stupendous amount of $$$ being moved around, there will be some very phat winners, but even more losers in aggregate on broad ecosystem level. [1] is actually illustrative, there's a reason why opex low - capex premium is ridiculous right now, with almost everyone along compute industrial chain capturing 50%+ margins. Investors are burning $$$ and companies and pillaging warchests, intermediaries are raking in $$$, but that doesn't mean investors or companies doing all the spending will make more than they spend, i.e. the net ecosystem business model is not sustainable precisely because intermediaries are capturing crazy rent relative to actual monetization to sustain.
> but that doesn't mean investors or companies doing all the spending will make more than they spend, i.e. the net ecosystem business model is not sustainable precisely because intermediaries are capturing crazy rent relative to actual monetization to sustain.
You understand that this doesn't follow at all right?
The intermediaries margins can compress.
> opex low - capex premium is ridiculous right now
What does "capex premium" even mean?
Of course you spend more on capex when you build a data center than opex!
High capex matches the expected business model. If opex was high then everyone would be worried!
Of course it follows.
Investors exuberantly build $10 of housing when there is $5 of demand, builders extract $8, when they normally extract $2 under normal margins, builders raking it, but arrangement is net loses vs world where investors build same housing for $4 and make a profit. Intermediaries margins can compress but what they already extracted for current build out is already built in balance sheet.
>What does "capex premium" even mean? >Of course you spend more on capex when you build a data center than opex!
No. Historically DC opex > capex, i.e. 60-80% goes towards power... because hardware costs were relative low % of TCO. Historically without delulu AI demand, IC producers capturing much less margin and TCO of DC was much lower than it is now. It's not opex vs capex it's TCO. AI is paying $10 vs $4, when demand is $5, $10 isn't sustainable, $4 is.
Now builders will be fine in case of crash, they'll compress margins for next round of buildouts, i.e. bubble bursts, current spend proves not sustainable. This is where the crux of argument is...
Future investors post crash when margins revert towards mean will be spending $4 to supply $5+ of demand. And due to nature of compute deprecatiion (i.e. tulips) they will have more efficient hardware with less opex/capex TCO per unit of compute, with much more sustainable balance sheet. The builders are still fine with their $2 margins, it sucks its not $8. But that leaves the current investors who spent $10 with stranded assets that are not competitive with more efficient $4 future build out, i.e. current investors have balance sheet black hole that cannot compete with none bubble market force.
This does not mean AI is doomed, it just means incumbents from current tranch of bubble driven, stupid high TCO build out is most likely doomed relative to future entrants. Unless incumbant has unassailable moat, or other hedge/cards (i.e. political bailout/intervention). That is the actual argument, Zitron is saying current ecosystem economics not sustainable, not that there is not a future model that isn't sustainable. But it does mean a lot of current players are balance sheet zombies, who _should_ die. But a reasonable disagreement is reality is size of bubble + contagion risk + influence of incumbents i.e. trillion dollar companies is such that they have non market lever (i.e. politics) to save themselves... but someone else is going to be doing the paying for a model that is net loss.
When you predict a company is going to fail and instead it sets revenue records you're not "dramatic and exacerbated". You're refuted.
Luu's post includes a (long!) list of specific predictions that aren't "exacerbated"; they're simply wrong.
Luu's point isn't that AI is going to succeed or that the "AI bubble" will never pop. It's that these predictions are all wrong. If you agree "directionally" with Zitron, all that means is that you're skeptical of AI. That's a totally reasonable position to have, but it has nothing to do with whether Zitron's predictions are good or bad.
>You're refuted.
No, the whole thesis is XYZ likely fail because REVENUE RECORDS is not enough to dig out of hole relative to MAGNITUDE MORE SPEND. Saying Zitron wrong because XYZ made $2 for every $10 it spends revenue needed to justify spending. Fixtaing on the $1-$2 is misdirection/innumeracy, the thesis is in reaching the $10 relative to time, i.e. that $2 has to be $10 in X time, but the current velocity suggest it will not be.
I agree with Zitron directionally on accounting, I in fact disagree with him on AI... I am extremely AI pilled, i.e. I think there is a future where AI is worth trillions and will capture large swatch of economy. The transformation will be extreme, unlike any past revolutions... but the accounting suggest that future isn't coming in time to rescue current AI incumbents from finance blackhole, which some may survive, i.e. bail outs, nationalization... but the $$$ suggest however we get there, there will likely be massive $$$ corrections involved irrespective of adoption.
You keep saying this. It doesn't mean anything to "directionally agree with Zitron" in the context of this Dan Luu piece. All you're saying is "you're skeptical of AI and the AI business model". Bully for you! Lots of people are. Nobody is dunking on you for having that skepticism. They're dunking on Ed Zitron for making a long series of patently risible specific predictions.
This just assumes Luu's piece has good argument that refutes Zitron's thesis when it doesn't. Saying Zitron is wrong because XYZ made $2 instead of $1 is different then Zitron staying XYZ is unlikely to make $10 in time when all signs still point to overperforming at $2 is not enough. It's a stupid reason to dunk.
That's a gross mischaracterization of what Dan Luu demonstrates in this piece as anybody can see for themselves simply by clicking on it. But the radical divergence of our premises (mine: based on the actual article; yours: unclear to me) explains why we're talking past each other.
It's not mischaracterization to point out limits of article is a poor basis to dunk on Zitron because it does not refute Zitron's broader thesis only nitpick what is really minutae/noise that can be explained by trillion dollar companies short term financial engineering / spreadsheet maxxing rosy picture. Even if Zitron short term forecasts/model sucks, it doesn't discount directional validity of his medium/long term thesis.
Someone in deep debt backstopping with maxing credit cards is not dunking on outside observer saying this arrangement ultimately not sustainable. The article is nitpicking over short term micro/liquidity when ultimate macro/solvency. Now maybe there's plenty of credit cards to max out, but systematically someone is going to end up holding the bag, and politically that could be public socializing costs. If folks want to use article to dunk on Zitron short term forecasts, it's whatever, but I think important to point out it doesn't refute his long term thesis around fundamentals, which again does not mean fundamentals cannot be overridden by non market means, but that's also a crux of the long term thesis - in lieu of correction/market clearing, we're going to see non market interventions to save current model from its fundamentals.
"Saying Zitron is wrong because XYZ made $2 instead of $1" is not a reasonable summary of the post we both just read and I don't think there's a point in trying to hash this out further if you disagree with that.
Did you read the article? It paints the picture of someone who does not in fact have a good track record on the 'fundamentals', even if his broad thesis of a bubble may prove correct.
e.g. when he suggested Anthropic may be fudging their revenue numbers / projections - which was actually due to him making some careless mistakes in a spreadsheet
(edited to remove snark) Your comment seems to miss the point that the article does not (necessarily) have a problem with Zitron being insufferable/annoying/smug. It's that his predictions are verifiably wrong. It's one thing to be annoying and right. Zitron is annoying, but not right.
Yes? What happened to FAANG in last 3 years, they cut a fuck load of jobs, the raised rent/prices, then inflation, then experience surge in new category AI. 1 + 2, i.e. squeezing rock has limits. 3 is fundamentally not sustainable, i.e. AI revenue gap order of magnitude relative to spend. This like debt crisis, there's lot of levers to burn to maximize extraction and make ledger look good short term, but is fundamentally not long term sustainable. Articles arguing over minutiae / short term accuracy pointless, market can stay irrational than one can stay liquid blah, blah - I mean its useful for investing - but when talking about long term predictions he's just stating the obvious, the financials don't make sense within the business cycle current players are operating in.
Like one can believe AI is speciation event technology eventually, but still given actual constraints, i.e. literally not enough investors for $$$, not enough hardware, not enough infra over xyz time horizon that these companies carrying stupendous debt and mathematically guaranteed stranded / deprecated compute infra is only digging themselves deeper vs future competitors. Sure AI can eventually capture 30% of GDP and knowledge worker's life time achievement is worth a few $100 of compute or a few pennies in thinking sand. But ultimate winners is probably going to be some future startup that pays pennies for thinking sand not incumbent who paid magnitude more and simply can't operate profitably due to balance sheet.
Luu is pretty specific about the predictions Zitron is making, has taken the time to pull them out and date them, and they're both risible and not rescuable with vibes.
His point isn't that Google or Meta are doing well or have bright futures. Luu is generally critical of tech giant engineering and product culture. He's critical of Google in particular in this very article.
But the point of the article is that it's not enough to have directionally satisfying vibes. If you made concrete forward-looking predictions and they're catastrophically wrong, that matters. If you make backwards-looking predictions that were literally wrong the moment you published them, that matters even more.
"Did you read the article" is a frowned-upon response on HN. The better way to write that kind of response, per the guidelines, is "the article mentions that". So: the article mentions that.
I don't know if directed at me because I didn't ask if one read article.
> it's not enough
It's enough for some of us, like his broad predictions that work on timescale of business cycles seem directionally correct. Even considering we're dealing with fast hardware deprecation cycles it will take years to play out especially with investors and incumbents burning through accumulated war chest. Luu seem oblivious to notion that companies with trillions in market cap can certainly out manipulate fundamental short / medium term market sanity. Part of Zitron's rant I find similarly compelling is the danger of dismissing directionally "satisfying" vibes because $$$ can capture reporting distort reality, which is only going to lead to bigger/more painful correction because directionally "correct" was dismissed as merely directionally "satisfying."
Let’s say it’s fine to give emotionally based arguments the same credence as rational arguments. That’s a huge cede, and yet, it doesn’t change anything, let’s see here:
If my cousin kept ranting about my other cousin was going to go bankrupt and fail and it was 3 years later and their income was up 2x I think I’d stop listening.
I worked at Google from 2016 to 2022 and agree with everything he says and you say, modulo the companies who are 2-3x on revenue and profits are going to 0. I worry that both of you have found a real problem but misattributed it, and insisting emotional arguments are the same as rational prevents you from participating in real fixes (ex. metas problem isn’t AI, it’s that they have a god-king CEO who cannot be deposed and monopoly profits. Imagine a twin of you and Zitron but instead of AI it’s 2020-era VR. If they weren’t focused on how their emotional argument was fine, they’d be your compatriots in noticing something’s off in Big Tech. Instead, we don’t hear about them because that battle was fought and lost years ago, and they lost credibility due to imagining Meta was going to 0)
What if the cousin goes bankrupt in year 5?
Zitron gives timelines, and they don't come true --- in fact, the opposite thing happens. You can't come back to that with "well, it hasn't happened yet". By that logic, no prediction is ever wrong; wait long enough and maybe it'll come true. That can't possibly be the logic you'd hang your hat on here.
Thank you, I have attempted to modify my original reply with one a little less dickish.
> Luu is pretty specific about the predictions Zitron is making
He is not, though. He precisely points to imprecise predictions, decontextualize them so he misses the point of the ones this thread is focused on, analyzes them with even less precise rationales that don't really rebut the prediction, and points suggestively (enough that you seem to have got that suggestion) that this rebuttal destroys the main prediction of every Zitron piece, while saying otherwise several times at the end of the rationale.
Zitron's predictions aren't all very good, but this article isn't either.
Ah I understand what you're saying. Yes I agree that if you pull back to, "We're in a bubble," then you can say that Zitron is correct, at least fundamentally, despite being wildly inaccurate in almost every other prediction he makes.
But Zitron isn't just blogging about how we're in a bubble. The assertions he makes are not minutiae, he basically continuously says that all the big SW firms are walking corpses. He's not having a rational conversation about the long term prospects for companies who invest in AI. There is a population of people who (rightfully) hate Google et al and want them to fail, and he just stokes their anger and frustration.
He doesn't add anything substantial, and (as the article indicates), even when he brings economic figures into the conversation, he's frequently wrong or misrepresents them.
I edited while you were responding with second para. I think his analysis that existing investors are walking corpses (or economically exhausted/weakened) is substantial. You have new companies going into extreme debt and established companies burning war chests may actually is important, and also valid economic argument ESPECIALLY if you think think AI will be economically transformative. Like current players basically spent $1000 on a screw driver to do $10 of work. Some of them went $1000 into debt, some of them drained $1000, which is much of their savings/warchest. The incumbant players rationalize future has $100 or $1000, or of work, but these companies are going to be vs player buying $1 screw drivers, i.e. the compute deprecation curve makes spending $1000 on screwdrivers in the first place very detrimental/terminal vs future competition. Zitrons argument is broadly there even if there is $1000000 work in the future, companies that spend $1000 on screw drivers balance sheet is working on timescale where there is $100 of work, i.e. the economics is not in favor of incumbents. The economics might still be very favorite for future AI... but not for first round of players who has to recover from grossly overpaying.
He makes very specific predictions about specific companies and they are wrong.
You think we are in a bubble and that AI won't pay off for the companies investing in it.
While I'm sure there will be companies that invest badly the problem with your prediction is that the public hyperscalers (Google, Amazon and MS especially) are already seeing returns from their AI investments.
Look at the revenue growth - that is actual dollars coming through the door.
Here's an exercise you should consider doing: instead of your $1000/$10 numbers, use real numbers for the major software companies investing heavily in AI.
Software companies aren't walking zombies for the same reason cabinet manufacturers aren't. Everyone can make their own cabinets, but few do, because they simply don't want to.
> The assertions he makes are not minutiae, he basically continuously says that all the big SW firms are walking corpses. He's not having a rational conversation about the long term prospects for companies who invest in AI.
...huh? How is it "not rational"? He's saying that, based on the financial information available, it appears AI doesn't actually make very much money given the capital investments. To the point that there may never be AI ROI.
I'm not sure how much this or that "prediction" matters. His arguments would be just as strong without them, perhaps stronger because they wouldn't give folks like Luu something to snipe at.At this juncture, the analysis seems sound. AI costs an absolute fortune and appears to make very little money, comparatively.
Is that irrational? IDGI. One needs look no further than Oracle to see a company in dire financial straits.
> One needs look no further than Oracle to see a company in dire financial straits.
Oracle had record revenue and profit in the most recent quarter.
That's quite a long way from "dire financial straits"
I do hope that works out for them. Sincerely, because the alternative is extremely grim for tech, and the economy as a whole.
https://www.theregister.com/ai-and-ml/2026/07/01/oracle-outl...
Hasn't AI been horrible for FAANG fundamentally?
- They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers
- Google Search has to compete with LLMs
- Meta hasn't demonstrated a credible argument on how they're planning to use AI. AI 'friends' would kill their business model. Their saving grace ironically is that people absolutely hate interacting with AIs. Same goes for other AI assistants.
- Hyperscalers have to compete for the same hardware as AI companies, driving their costs up
- AI turned out to be excellent at both porting software to more optimized stacks and deleting the 'prestige' of building these ultra-inefficient microservice containerized stuff. I haven't read a single article about somebody bragging about this stuff. When it comes to tech (which is not AI), usually its about Zig, Rust and going native.
- So if customers really start feeling the heat of rising costs, they have a realistic path of optimizing their compute usage by using AI to rewrite the worst-offending components. I think one of the few things in which AI has demonstrated measurable economic value is rewriting software in Rust to be more efficient
> They've all been compelled to build the same horribly expensive AI infra, to serve similar models that have no ability to lock-in customers
Emphasis added, since having a horribly expensive AI infra allows offering enterprise contracts, which is a form of lock-in and has been pretty lucrative for GCP/Azure/AWS.
>Hasn't AI been horrible for FAANG fundamentally?
No. Net income is up quite a bit and profit margins maintained at Microsoft, Amazon, Alphabet, and Amazon. Meta net income is flat, but they are maintaining profit margins.
Zitron's claim is that much of that boost in profit for microsoft and alphabet and amazon is from only a few customers, specifically openAI and anthropic, and that those companies are buying and promising to buy lots of resources with money from investments from those same companies, and that largely this is unsustainable unless openai and anthropic can find a profitable business model.
He is right about that. Those companies are subsidizing the use of their models and at some point they are going to have to make a profit. It is unsustainable the direction they are currently headed in many people don’t like the messenger of bad news, but someone’s gonna be caught holding the bag stay clear of the blast crater.
And with both OpenAi and Anthropic are announcing record revenue growth to the point where Anthropic is now profitable this seems like it's going to work out fine for them.
Until they go public, no one will know except insiders, and they are not really talking. Do you want to buy a pink elephant?
Would they announce record losses and financial distress?
We'll see when they go public. Until then all these press releases are strategic messaging...
> Would they announce record losses and financial distress?
Of course not, but private investors get to see their books and investors are lining up to invest.
To be fair to Ed, I’d describe his usual argument (at least currently) as saying that Meta, MS, google are “mature” companies trying to be maintain the high valuations and growth of a young company, which they no longer are.
If you take this to be his argument, then dan’s numbers are more consistent ed’s claim.
more consistent with? more consistent than?
Yes, “consistent with”. Thanks.
Are they? These companies have been caught tweaking their numbers. One example, not sure if cited by Zitron, or others, is that they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books. There have been trillions of debt discovered this way. Another issue is the apparently relentless progress of the hardware industry, needed to justify their super-high P/E ratios, measured against the fact, that to lessen the effect of HW amortization, hyperscalers opted to lengthen the depreciation timelines of their GPUs. So there is an apparent contradiction that new hardware needs to be both substantially better, and substantially the same, to make both stories true. I'm not a finance guy, and a lot of it is over my head, but even finance people keep asking the 'who's gonna pay for this' question. We're way past the belief that this is going to produce reasonable returns (as in a value for money kind of way), and hoping we can financially engineer ourselves out of this situation without having to feel the pain.
> These companies have been caught tweaking their numbers... they build data centers through holding companies, who have to absorb the costs and massive capex based financial liabilites, so that the brand-name big-tech companies get to keep their expenses off their books.
This is about as far from "tweaking their numbers" as you can get. It's a standard way infrastructure-heavy industries structure their investments and people would be asking questions if they didn't do this!
> hyperscalers opted to lengthen the depreciation timelines of their GPUs.
Yes and so they should! GPU depreciation timelines used to be 3 years!!
Google is famously still running 10 year old TPUs at 100% utilization, and 10 year old H100s are worth more now on the second hand market than they were when they were bought.
H100 spot prices have only dropped from $5 in May 24 to $3.20 now despite the release of the B200: https://semianalysis.com/gpu-pricing-index/
I have the exact same feeling about him.
He has built a following of people that want to hear his extra skeptical views. And even if he changed his mind about some things, he cannot admit it, as that is not what his followers want to hear from him.
It's rare that people make the news and build a following by saying a very balanced, down to earth opinions... unfortunately.
> It's rare that people make the news and build a following by saying a very balanced, down to earth opinions... unfortunately.
Just gets you disliked by both sides, "certainty sells".
Some folks would prefer a confident wrong/simple answer over a "well it depends/is nuanced" answer.
I almost wonder if it's even possible now that so many of us get our information through algorithmic feeds.
I listened to one Zitron interview on YouTube and my home page was immediately crammed full of similarly foamy-mouthed AI critics. (As well as plenty more Zitron.) And it's suggested some people with un-nuanced pro-AI takes, too. But what the algorithm has never, not even once, given me is a sober voice that calls attention to the nuances.
>It's rare that people make the news and build a following by saying a very balanced, down to earth opinions
Humans are built for fighting and killing the rival tribe, not for pondering whether the other tribe might actually be correct. We are exceptional for even being able to overcome ourselves enough that the outcome of "fighting and killing" can be minimized in the large.
> And even if he changed his mind about some things, he cannot admit it, as that is not what his followers want to hear from him.
I don't think that's true - over the years he's changed his mind from "LLMs are useless slop machines" to "LLMs can be useful when applied wisely".
For instance in "The AI Hater's Manifesto" he says:
> It just came to me — the problem that I have with most people using LLMs is the delineation between outsourcing work and outsourcing thought. Those using LLMs to write little scripts or BQL code on a Bloomberg Terminal are inoffensive. [...] A tool being used as a tool to do tool things — in many cases involving the LLM writing a little 30-line Python script! — is not a problem, though it’s also not a trillion-dollar industry that needed to steal everybody’s art and writing.
Similarly, in "The More You Buy, The More You Lose":
> Sidenote: The only truly useful use case I’ve found is on the Bloomberg Terminal’s ASKB feature, which takes natural language and turns it into BQL code to make requests of Bloomberg’s datasets. It’s genuinely useful!
You can perhaps say that he underestimates what the technology is capable of (or, conversely, that other people overestimate LLMs) - but that's a different kind of conversation.
But even those concessions have been a shift: at every point, he's been as bearish as possible on LLMs, often past credibility.
And if you take it as a given that AI will never be any better than ~~now~~ a year ago, and that anyone who disagrees is an idiot or a liar, then that pretty much demands that the entire AI economy must be as fraudulent as he imagines. Which, while it serves his purpose of serving up AI-skeptic invective slop well, doesn't actually model what's going on, which is speculative investments that have the potential to generate extraordinary returns.
right, and look at current American politics. One side tried to tailor normal, routine and rational POVs.
The other...
EDIT: I do find it amusing when I write these types of comment, then suddenly realize the irrational man childs of the far right nationalist republic ethnostatists think they're the rational ones.
There are plenty of people on the far right whose positions are rational provided that you agree with their views. Conversely, there are plenty of people on the far left whose positions remain irrational despite that you might agree with their views. It is a serious cognitive error both to fail to see the irrationality of those you agree with as well as to fail to see the rationality of those you disagree with.
> I think the worst thing that happened to him was AI skepticism becoming a political position.
It is a political issue in the sense that the discussion around AI can't avoid material and cultural issues. Ed Zitron definitely has an ax to grind and I'm personally turned off by his hyperbole, but I don't think something being a political issue means it's not worth discussing. I've also noticed the pro-AI crowd pivot to accusing people of not having actual reasons for hating AI, being victims of Chinese propaganda, etc as a way to avoid actually talking about specific issues that people have about AI and DCs.
> It is a political issue in the sense that the discussion around AI can't avoid material and cultural issues.
I'm not even sure it's political. I think it might be a religion now. He doesn't think that AI is bad, he believes that AI is bad.
I never said it's not worth discussing, I'm just saying that it becoming a charged issue was bad for Zitron specifically because his style of content fell in demand with the most irrational parts of the crowd.
You're not wrong but for a lot of AI boosters it's also a political position - remember Anthropic and half of SV at this point is run by wide eyed effective altruists.
Ultimately one cannot separate technology or science from politics, it's inherently political
Audience capture is a terrible thing.
I'm not sure I have the force of will to not succumb to it. I think the only way to avoid it is to be so sure of the thing you are doing that the audience reaction is not the key metric by which you measure your success.
"Popular topic-expert" is a really cursed career to exist.
Ideally we would reward expert opinions on track-record, instead of how they make us feel. But we don't. Also ideally, the expert's conclusion wouldn't impact their ability to pay the rent (as long as it's correct), but again, that's not the world we live in.
"Your boos mean nothing, I've seen what makes you cheer"
>one's chosen enemies must be simultaneously terrifyingly powerful and incompetent dunces
I've got some bad news for you.
I really don't find it coherent to call someone who you keep consistently losing to stupid.
That's literally the meaning of the statement "the market can stay irrational longer than you can stay solvent".
Irrational means stupid.
Stupid can win for a very long time, and in the end the "loss" is born mostly by bag-holders.
This isn't about people who just happened to make it big in a market rally, though. You're talking as if I'm speaking about people who just happened to buy some Bitcoin in 2012 rather than leaders of some of the most successful corporations on Earth.
They're not infallible, but modelling them as complete idiots that just happened to get lucky is also... Not really consistent with reality, as far as I can tell. These people might not be good people, but they're good at playing a certain kind of game.
Stupidity has always been terrifyingly powerful.
Not really.
Things can look stupid when we don't understand them, but there has to be some intelligence somewhere at some point even if the arrival of wealth then suffocates it with sycophants. If Musk or Trump or GWB were all *merely* the idiots they're often mocked as being, chances are we'd never have even heard of them. They almost certainly weren't even "merely average".
Now, stupidity that arrives after the bank balance reads a billion dollars, that's terrifyingly powerful.
All those people were born rich, with no chance of losing their money.
Instead, the smarter rich people stay out of the press. And the only reason we hear about them is because they were always very stupid.
1. Trump was born wealthy. There was no "arrival of wealth" that smothered the intelligence you suppose he might have used to earn the wealth, because he didn't earn it.
2. You don't understand. Trump is successful because of his stupidity, selfishness, and vile behaviour. Not despite it. In 2016, the Republican primary field had 20 or so candidates on a wide range of reasonableness. Trump crushed them all, because he most represents the average Republican voter. If he were more intelligent, or if he cared more about anyone other than himself, they would not have voted for him. His arrogance, lack of intelligence and morals is quite literally his strength because it's what makes him so relateable to the American masses.
There are two possibilities. One is that half the country are total idiots and the people leading them, and leading the country, are also total idiots who only got into power because half the country are, again, complete idiots below average intelligence.
The other is that you are in a bubble and have been convinced that the leadership of the world’s premier superpower are below average intelligence, along with 70-80 million voters. The former is not something an intelligent person would believe, you have thrown out serious analysis for political theatre and memes and should rethink how you view the world. Now stop to consider that maybe actually half the country has a totally different worldview, and that their leadership, having reshaped global politics, is actually full of intelligent people who are cold and calculating. I know it’s harder to stomach, but just consider it for a moment.
This is simply a false dichotomy.
Being propagandized into extremism does not require anyone to be a total idiot.
Everyone is susceptible to propaganda and populism.
Because it's not a single data point, intelligence is a wide surface area where you can be smart in some areas and stupid in others. Furthermore whether you are being intelligent is relative to ideals and goals, and not everyone has the same ones.
"Capability to achieve goals" seems to be fairly independent of goals.
"Capability to achieve goals" is not synonymous with intelligence.
I find it difficult to imagine an intelligent person who finds it hard to get what they want. The trope of the oblivious genius who is incredibly competent in a single field of inquiry but completely unable to handle day-to-day life is more a creation of media than how reality works.
you're likely working under an assumption of meritocracy/overvaluing of kinds of intelligence
At first I thought you were referring to Umberto Eco's laws of fascism: "Fascist societies rhetorically cast their enemies as at the same time too strong and too weak."
but it's subtly different, because incompetence is not weakness.
I read it as suggesting that AI models are simultaneously terrifyingly powerful and incompetent dunces.
no, it's the current administration, among others like musk.
That is also very fair.
It is weakness in the long-term.
It's pretty clear in how people talk about billionaires: They must somehow conclude that the people most successful within a system that rewards certain things are not competent because the things the system rewards are not what they think the system should reward (it is fine to believe the system rewards the wrong things, but people walk straight into denying that those people have skill even within the system, or they claim that skill within the bounds of the system does not reflect any "real" skill - totally ignoring that elites tend to stay elites even through, say, Communist uprisings).
Hence how someone can say that Musk is "dumb" with a straight face.
I wouldn't really call cruelty or dishonesty a "skill".
That's a choice, but the universe has no reason to respect it.
> the system rewards are not what they think the system should reward
It's the grown-up version of nerdy kids hating "the jocks" in high school. We're all just a bunch of dumb kids. Maybe obsolete children, but still children when it counts.
That said, Elon Musk celebrated cutting funding that fed starving children and supported cancer research by waving around a chainsaw on stage. The richest man on earth did this because he wanted lower taxes... for himself.
When Anubis weighs his soul against the feather it's likely to completely destroy the scale.
I'm not saying any of the people in charge are good people at all. I'm just saying that they are skilled at achieving their own goals, regardless of the morality or lack thereof of those goals.
I don't even think that. I think half of them accidentally stumbled into success. Elon was kicked out of PayPal with a nice golden parachute so he wouldn't sue.
Regression to the mean is pretty nasty. Stumbling into success can make you a car dealership owner or something like that, but being consistently successful in business requires just about as much skill as being consistently successful in, say, chess.
heh, no. Eco is referring to how the white house casts groups like academics, immigrants, socialists, and trans people.
Audience capture is a bastard.
Ed Zitron’s job is to convince people to pay him money to read what he writes, of course he’s going to preach to the choir, they’re paying him to do that and he knows it.
This is why I always consider the agenda of an author, Ed Zitron’s agenda is to make money from subscribers who read his writing.
That’s level 0 analysis, you’re supposed to go to the next steps and not stop here…
Sometimes it really is sufficient to say "This person is a grifter and from that all else follows".
and sometimes it isn't.
In this case, it is. Zitron does not possess even the most basic knowledge about the issues and practices he complains about. For example: https://www.crisesnotes.com/sigh-no-ed-zitron-ai-bond-issuan...
It’s fine if you do not want to engage with the person‘s work, but source of revenue is just one component to evaluate if someone is grifting
From the article "A more common defense is to say, just in general, people attack Zitron because of Y (usually his style), but they never address his points."
The article "engages with Zitron's work"; the post you responded to merely extended the discussion to speculate on why Zitron might be producing it.
(btw, for the record, I'm an AI-hype skeptic and _also_ an AI-head-in-sand skeptic; as far as I can tell, both sides are full of malarkey.)
he makes a shit ton of money off this - in this attention economy we are doomed, people of every side find that going all in on something, no matter how intellectually dishonest, is much more profitable. Extreme AI bros or Extreme AI doomers seem dishonest. AI is an amazing technology - it is simultaneously not going to replace us in the next 3 years and it's not total garbage - the truth lies in the middle.
"audience capture"
Its pretty clear if you listen to him now he's just (re)playing the hits for his audience. Its like MSNBC/Fox News for people who think they're too smart to fall for that.
I used to think he was just early on some of this stuff but the sheer amount of content he produces its clear he's just cashing a check.
I'm not a huge fan of his style myself but fundamentally he isn't wrong. The whole "growth" so far has been all show and no go. I see people pouring in millions only to end up bankrupt a few months later. Evangelists portray those instances as rare and simply "skill issues" and "they don't know what they are doing but I am". Anyone that's ever had several servers running at home and seen the electricity bill at the end of the month knows it - I do as well. And we are talking about servers that use power, only a fraction of a server running 4x H100s at 100% 24/7. For those of us that have - we are talking servers that have one or two xeon silvers at best, 15% load on average. And I live in a country where the electricity is veeeeeeeeeeeery affordable. I'm not taking into account training, or investment to get it going, just inference.
20 bucks subscription a month, dario, you ain't fooling anyone with above-room-temperature IQ (Celsius). Even the expensive subscriptions - we know that's not the real price. And the limits, bumping up prices every two weeks and so on, just to keep the lights on while draining investors... Zitron's claims are pretty impossible to deny: the moment those companies go public, the real prices will need to come out of the shadows and end up on your monthly bill.
At the same time I fail to see the real world benefit to this, even in software: it's like comparing Lego (before they began their anti-consumer bs) to cheap Chinese toys. The moment you look at them side-by-side, you know which one is a premium product and which one is a cheap Chinese toy. While I have been a big supporter of open source since I was a child, I was never biblical about using open source - if some proprietary piece of software does a better job than the open source one - fine, take my money. Not anymore. I see the abysmal state of cyber-security as a direct consequence of slop. Slop-written code, slop-reviewed code, tests pass(also slop), ship it. Yeah, I'm not trusting you with my data, the hell with that, I'm self-hosting everything, adios. And I sure as hell don't trust the ai-bros for anything either.
And there's another thing: Microsoft was clear about it: github is constantly down because they can't handle the load. App stores are bumping up developer fees. Anyone can slop together a todo app(which was never hard to begin with). It's still a winner-takes-all economy - no one is going to install a todo app and migrate from Google/Apple just because. So the 1000 todo apps released daily will simply be a hole in the pocked of the people who slopped them together and another reason to be paying 500 bucks for 64 gigs of ram and another 500 bucks for a 2tb nvme. Raspberry pi's started off as educational platforms for 35 bucks and their commitment was to keep them at those prices. That aged well, right? If I decide to upgrade my uconsole, I have to pull out another 350+ bucks for a raspberry pi. All thanks to the sloppification. The bubble can't pop soon enough and frankly I don't care what it takes down with it.
No? He's been pretty spot on.
This very submission is about cases where Ed has not been pretty spot on.
but the article cherry picks. the article ignores Zitron’s economic arguments about data center costs vs. future profite.
Are any of those predictions that have been proved right yet?
Ed Zitron has the economics of AI basically right. Most technologies arrive by digging an enormous financial crater, followed by a contraction period in which everyone insists the crater is actually a revolutionary new business model, before the survivors eventually buy up whatever remains.
What likely resonates is AI really does feel like a science experiment. There is clearly real value here. The problem is that the economic value has yet to catch up with the technological value. And yet the claims coming from AI companies have the unmistakable energy of a state-fair entrepreneur standing beside a suspicious knife yelling, “You have never seen anything like this before, it slices it dices...!”
I think Ed goes too far when he compares LLMs to garbage. He’s tried them, had a handful of bad experiences, and apparently decided the entire technology belongs in the round file. But much of what humans do is essentially trial and error with better PR: apply some logic, see what happens, adjust, try again, and continue until you eventually solve the problem.
If you can get an LLM to reliably do that, you can solve certain classes of problems dramatically faster.
I think he's constantly trying to time the peak (of AI improvement, of compute capabilities, of profitability) and keeps having to readjust his predictions every time it's proven wrong. Timing the peak is a fool's errand unless you have extremely hard and unavoidable data that everyone will have to face by a deadline. But contrary to what AI boosters often imply in response to skeptics being wrong, failing to time the peak doesn't mean the peak doesn't exist. So far it has existed for every new technology.
Thanks for putting this together, his writing really aggravates me and it was nice to see all of his predictions put together in one spot.
It's interesting how he has pivoted from denying that LLMs are useful to accusing frontier labs of Enron-scale fraud.
I suppose it's the natural pivot you have to make when your whole business is an anti-AI newsletter that costs $7 per month.
The fraud is there. Whether it surpasses Enron or not will be revealed in the future.
To commit fraud you have to lie, deceive, or conceal. All of this bonkers financing is happening in broad daylight, announced to the markets, and met with rave reviews. I tend to agree with Zitron that the whole thing is a castle made of sand - not because the tech is bad or useless but because the financing, in its scope and structure, is so outlandish - but you can build a castle made of sand as long as you don’t tell anyone it’s made of steel.
So far NVIDIA has been very careful, it’s not actual fraud, at least based on public information. It’s a very unstable and extremely risky bet, that is very likely to blow in the face face of AI companies, but it’s not fraud
I think a lot of people (myself included) would love for it to be fraud. Because even if it's not fraud what is being done between NVidia, OAI, Anthropic, Microsoft, Meta, Musk and Google is funny accounting at the very least. It's hard to take any part of what's going on seriously in the US at this point and I feel like the bigger downside to all of this is that if/when they get away with this, and there are no repurcussions for any of the big names involved, then it erodes consumer trust that much further, pushing us deeper into a state of "doesn't matter anyway, why try".
Yes, you can include me too. I’m aware enough of the details to know we don’t have any proof of anything fraudulent, but that whole situation is just so disgusting
Doesn't this ultimately boil down to: other people are spending their money on things I don't want them to? Which I mean, yeah I feel like this about tons of things all the time. I'm human too. But I know this is a petty part of me not a thoughtful part.
Patrick Boyle had a vid specifically on whether there was Enron style fraud. The conclusion was no, though he thinks things may be a bit bubbly https://youtu.be/NufJ7g63KSY
It's worth considering that it might not be 'Enron-style' fraud, because that's the best comparison have at the moment.
What event did people compare Enron to, before Enron became 'Enron'?
It's probable we're witnessing an entirely new fraud, we just don't have all of the details yet.
Why? If there's no evidence of fraud, why are you imagining some new category of fraud that these companies have independently conjured up?
Suggesting that an entire industry is in cahoots to invent and participate in an entirely new fraud-like scheme, including companies that have lots of wealth and growth and much to lose from such an exposure...seems awfully conspiratorial, don't you think?
There is no evidence of fraud that I have seen beyond complete speculation from the likes of Zitron. He basically just says "Look how big the numbers are! It's so big it must be fraud!"
Zitron himself doesn’t call it fraud and doesn’t compare it to Enron (he said no, with his reasoning when asked in interviews, multiple times)
I was thinking of this article where he compares OpenAI to enron: https://www.wheresyoured.at/what-happens-if-openai-dies/
Do you mean this section?
> If you are going to look at this and say “actually it didn’t” because of its Enrontastic accounting treatment, I also need to warn you — that identical guy in the bathroom is actually a thing called a “mirror,” a reflective surface that is showing you a reflection of you, not another person who is dressed like you and copies everything you do. I can’t imagine how scared you’ve been, and hope this has helped.
That’s his weird writing style, so I’m not 100% sure, but I don’t think he literally means that OpenAI is committing Enron style fraud. More of a stylistic way to say it’s a mess
He also alludes to it here:
>What follows may be an Enron-Lehman Brothers hybrid, one that leaves unbelievable destruction in its wake, an avoidable systemic risk empowered and enabled by a kneecapped media industry and sell-side analysts incapable of seeing further than two quarters in the future.
He also mocks the financial statements from the companies in a way that alludes to them being fraudulent (from the OP):
> February 2025: Anthropic making $34.5B in revenue 2027 is "is laughable on many levels, chief of which is that OpenAI, which made around twice as much revenue as Anthropic did in 2024, barely made a billion dollars from API calls in the same year."
> Oct 2024: OpenAI's forecast of $3.7B revenue in 2024 and $11.6B in 2025 and $100B in 2029 are absurd, "a statement so egregious that I am surprised it's not some kind of financial crime to say it out loud" I'm realizing that he is very good at alluding to gross financial crimes without outright accusing them of it (probably as a hedge against libel or something)He LITERALLY said it is not like Enron. And repeated it.
I was thinking of this article where he compares OpenAI to Enron twice: https://www.wheresyoured.at/what-happens-if-openai-dies/
You're right that he doesn't explicitly say enron-scale fraud, that's just what I came away with from reading the article a while back.
I haven't read every word but I don't recall him saying AI is bad or useless ever either. His refrain is that they cannot keep up with their endless spending on training and they're not reaching new markets.
I look at the rapid rise and decline of OpenClaw and get the impression AI has not really found any foothold among average people.
From the OP:
August 2024: "generative AI is a dead-end technology that has peaked”
July 2024: "Generative AI models aren’t getting more energy-efficient, nor are they getting more “powerful” in a way that would increase their functionality"
Nov 2025: "the fact we're running out of high quality training data and we're hitting the walls of scaling laws, in the training paradigm, these models aren't getting better. What we're seeing today is pretty much what they're always gonna be like"
There are other examples too from his prose of talking about how they are barely useful but I don't want to dig it up
> I don't recall him saying AI is bad or useless ever either.
He does say that pretty often in interviews. That doesn’t change his thesis but that‘s one reasonable reason people dismiss him, he has often said that AI is useless when considering the externalities. And he will sometimes take a shortcut and just say „it’s useless, doesn’t do anything well“, which is of course way too simplified.
Zitron sells anti-hype and AI-hate. AI is not good for a lot of people and he's telling them what they want to hear. He's great at talking and making entertaining facial expressions. That's actually a real skill I admire but it has nothing to do with predicting markets correctly. He's in the business of selling entertainment views not predicting markets. He even admits he doesn't short AI.
Zitron sells AI is in a huge bubble. Which basically everyone agrees with who isn't directly incentivized to say it looks perfectly normal.
Personally, I don't bet in rigged games, which is what all the circular financing is.
How often are people that are paid by their content attracting eyeballs correct? Isn't this a universal thing that people in these roles are constantly stating all sorts of things that never happen. This happens in sports media, politics, tech reporting, stock market predictions, etc.
Shouldn't society have a clever name for people playing these roles by now? Something catchy, insulting and based on truth might help call this out easier. I would throw influencers in there too, they are writing/video-loggin/podcasting for the same money outcome.
How has it taken so long for this to get some proper attention?
I'm not Ed's biggest fan, but he's been pointing out some very important things for quite some time now, regarding the ludicrous over-investments going on around so many companies that are completely and utterly devoid of profits and will likely never have any.
Though the bubble has not popped, I don't see the following discussed in the post: Zitron would probably point out (as have others) that many of the hyperscalers are booking valuation increases in Anthropic, OpenAI as "Other Income", which is substantially increasing their reported revenue and earnings. It's roughly:
- Hyperscalers like Goog, Meta, Msft invest cash in Anthropic, OpenAI, in exchange for equity
- The ongoing investment actually boosts the valuations in the Anthr/OpenAI (new raises are done at higher valuations), so the valuation of the Hyperscaler's existing investments in Anthr/OpenAI increases, which gets recorded as Other Income in quarterly earnings
- Much of that invested cash will itself come back (circularly) to the hyperscalers as revenue since Anthropic and OpenAI spend a lot of money via datacenters etc.
On Other Income phenomenon, see for example, https://www.ft.com/content/be97df0a-76b1-4cb0-9ba4-d1117d8d1...
Also, there's apparently lots of off-balance sheet debt. For example https://www.ft.com/content/a0a07cce-6d19-4b1e-a73b-9855a06ba...
Sorry what is the punch-line here supposed to be? These investments obviously increase correlation coeffs., but these are highly correlated stocks to begin with.
valuation gains on investments are one-offs, not signs of sustained improvements in profitability that would warrant higher market caps
when those valuation gains are in turn the result of circular financing schemes (a bakery giving out money so that people buy bread from it), we're getting to a dangerous situation
Circular financing is an issue if the wealth accumulation stays in the chip -> model provider ecosystem. However it seems like the labs are making quite a lot of revenue from the chips (customers).
Demand for compute is far outstripping what was projected in the initial rounds in which we pearl clutched over 'circular financing' - which is hardly distinguishable even from the classical bill of exchange, the core phenomenon of the money market in Bagehot's day, in which I provide you inputs and you give me a share. I keep reading people saying what amounts to: the primitive bill of exchange was circular!!; if the seller of inputs has reason to lend, so does everyone else etc etc. In fact if the projections about final sales are correct, it is plain all these deals will be fine.
The issue is simply that the posted article begins with a review of recent earnings/ revenues, but fails to discuss that a substantial part of those revenues are investment markups.
Whether it matters we don’t know yet, but it’s a fact worth noting. A better article might have tried to argue why it doesn’t matter
This is basically a bs line of reasoning, and it's easy to verify in 5 minutes (go read some SEC fillings).
Yes the investments do increase GAAP, but these are seperate line items from revenue which is what is listed in the article.
Alphabet is the biggest winner in this department, it's investments gain/losses for the same period as in the article was:
2023: -$1.45B
2024: +$2.24B
2025: +$24.90B
Yes thats a lot, but compared to it's seperate revenue growth of nearly $100B in the same period, it's not that much.
Wait are the hyperscalers booking unrealized gains as income? Or are they selling their positions?
As far as I understand GAAP reporting standards actually require them to report gains on those positions as "earnings". But they do report non-GAAP earnings sometimes excluding them. E.g. Google earnings per share last quater is $9.11 GAAP vs $2.85 non-GAAP (mainly because of SpaceX shares).
https://finance.yahoo.com/news/warren-buffett-decries-accoun...
Useful piece on this from Owen Lamont:
https://www.acadian-asset.com/investment-insights/owenomics/...
A recent Zitron claim is that they’re booking unrealized gains tied to these private labs. Google’s net revenues being a recent example.
It's not a "Zitron claim". it's literally in the filings...
The first section of this post responding to "Meta, Google, and Microsoft are dying" is completely misrepresenting Zitron's arguments in the linked video. Zitron is making essentially an enshitification argument concerning Google and Meta. He's not talking about whether they will be able to squeeze out more revenue in the short run, but how they are willing to abuse their users to ensure that they do. Citing increased revenue for these companies is not arguing against Zitron's point.
Luu also fixates on Zitron mentioning Prabhakar Raghavan, but then proceeds to agree with Zitron's core point that Google has intentionally degraded it's search product to maximize revenue. Maybe Raghavan is not solely responsible, but it seems fair to hold him accountable for trends that accelerated under his leadership.
Same mistake over and over again: zitron job is not "making successfully predictions", he is a content creator.
For him, it's enough to be right once, even in 3 years from now.
Fair enough on Zitron being wrong, but I think the opening argument about Meta, Google, and Microsoft misunderstands his point.
Zitron is saying that the hyperscalers had no genuine growth opportunities, so they're using the AI bubble to achieve growth. The fact that they've continued to grow for a few years doesn't contradict his point, and Meta's steadily decreasing profit margin certainly doesn't look healthy.
Seconding that observation. The IT folks in charge of the compute direction have been quietly raising those concerns for over a decade (“and what happens to those alleged lower costs when their attention diverts to a new industry or pumping margins for shareholders?”), and the major enterprises or customers had all but migrated wholesale into public CSPs - and been eyeing the exit when they finally opened those eye-watering bills IT had kept forwarding to stakeholders. The industry wasn’t going to collapse so much as right-size, and that would turn into an inevitable cycle of churn (higher prices to drive margins, leading to more customers leaving in part or in whole, which would drive up costs higher to continue delivering positive results, ad infinitum).
The current AI build and boom has done wonders to their bottom lines in the immediate, but even Wall Street has its limits, and it sounds like there’s decreasing appetite for such CAPEX builds without associated proven revenue. That might kill some companies outright, but more likely it’ll force the major CSPs into the churn cycle that much faster.
I think lot of people including Ed are mixing 2 things the AI tech itself and the economic viability with the inflated values of companies building it currently. Me personally I am optimistic about the tech itself but don't see the current AI companies valuations being realistic or even the economic systems they are building around AI/LLM. As it will all be comoditised down to cost of compute + cost of electricity in the end.
To me and most other non-West coast Americans its obvious he's right. Which is a good explanation of why SV has the resources and success it has because it can do things no one else believes in. While the rest of the world will always be catching up.
I used to pay attention to Ed Zitron, exactly because he seemed to be someone who did the research, and looked at numbers. Until one day, I realized that seems to only look at numbers as long as it serves his agenda. When it doesn't, he looks away or makes the case for why the numbers are wrong, and shields himself from these "incorrect" numbers - or people who would point to anything suggesting that AI is not a total fad.
In April 2025, Zitron wrote [1] "I am sick and tired of everybody pretending that generative AI is the next big thing." This was at the time when AI coding tools had already gone "mainstream" with devs, and pretty much everyone was using tools like GH Copilot, Cursor, or something similar.
So I replied with this observation, saying how, at least within software engineers, AI is being adopted faster than any technology before [2]. To stay objective, obviously I brought receipts: sharing how, based on an older survey I ran, ~75% of devs in that survey said they used AI coding tools. Zitron made fun of the small sample size (216 people), blocked, and pretended like AI had zero PMF anywhere in the world.
I stopped taking him seriously since then. And I'm wondering ever since: does he deliberately only look at numbers and facts that he can tell the AI doomer story around? Or is it more that he finds that there's not many people who are "informed sceptics", and decided to play this role?
[1] https://x.com/edzitron/status/1916903519594156407?s=20
[2] https://x.com/GergelyOrosz/status/1916906481686921483?s=20
Ed's right about OpenAI being out over its skis, he's right about the numbers for everything being wildly optimistic and he's right about the circular financing/leverage aspect of a bubble. He hates AI though so he can't acknowledge its usefulness, it was pretty clear to see on his DOAC interview, Stephen kept bringing up real wins and clear progress, and Ed wouldn't engage in a substantive way.
Yes, his thesis is pretty much correct, his personal opinions aren’t too relevant or valuable. It’s a mistake to take his predictions as the important thing, it’s pretty much irrelevant, the whole field is very dynamic and complex, and he obviously isn’t an oracle who can predict the future. The only thing that matters is the thesis
I think he deliberately looks at doomer facts. I'm not sure it's cynical so much as a genuine belief that it's all nonsense. But IMO the belief is based on a lack of understanding of AI.
Looking at it from an objective/historical perspective, when he first got on his high horse agents weren’t a thing, MCP was in its infancy at best, and half the code generated didn’t compile from frontier models.
From there everything split into two factions, which I’ll dub as believers and non-believers. From there, it has entirely been a cult following despite the evidence showing that models and agents have legs for software development.
FWIW my post history would show my extreme skepticism, and to an extent I still am. I think the real power of models isn’t the model at all but the harnesses.
Either way I think he lost the plot and runs on vibes himself. I also think this whole AI movement is going to have their 2000/2008 moment before the phoenix rises from the ashes.
I don't agree with the believers vs non-believers dichotomy. That makes this look like a religious war and it shouldn't have to be like that. To me AI is a very useful tool, no more no less, it isn't a 'make a wish' machine and it isn't a silver bullet for all of the issues that have plagued software so far. But when properly applied it's quite useful. "Non-believers" would have to be people that have yet to actually use AI, just like you can probably be a non-believer in peanuts until you've seen them, and most people that I know acknowledge the reality of AI tools and their use cases.
All tools, AI included, have a business end and as long as you point that away from yourself you will be fine. But to properly apply it (rather than as a faster way to make a huge mess) takes discipline and being methodical. It was never different.
what's it with people who think a bubble is literally destined to happen because of some religious belief that history repeats itself? I find it fascinating to understand the theory of mind of such people. So much confidence.
Just speaking from a gambling/odds perspective: the odds that a bubble never pops again in the history of mankind is a 1 out of 100, where the odds of a bubble popping again are 99/100. Your religious finger-pointing cracks me up.
He's part of the professional political / social media class now. He makes his money through engagement. I've stopped trusting people of this ilk. I listen to people who make most of their money not via the media ecosystem.
Examining Dan Luu's predictions would be harder since he doesn't even date his articles.
Was this hit piece prompted by Zitron being mentioned in the tech scene lately?
https://lwn.net/Articles/1091245/
I don't know. If you post walls of text and ramble on like Luu, perhaps you are sitting in a glass house?
the dates of his articles (well, month and year) are all here: https://danluu.com/
Luu kinda has a reputation for knowing his shit, for over a decade now. He's not a checks notes games journalist larping as economist, but he does all right.
He may be a good programmer, but I have never seen any interesting article from him. Also, making predictions is different from being knowledgeable.
It is ironic that Zitron is accused of having a cult following whereas Luu clearly has one, here at least.
This article cherry picks:
Ed Zitron mostly covers the costs of data centers, circular spending, and predictions of large the market for AI has to be to justify the data center expenditures.
I was disappointed this article didn’t really cover Zitron’s main arguments.
Maybe a paid article placement? I don’t know, but I was dissapointed: I read Zitron’s material and I wanted to see good counter arguments to his rants about costs of data centers, circular spending, and predictions of large the market for AI has to be to justify the data center expenditures arguments.
What are the predictions he has made that this article omits?
He is making predictions with specific timelines. No one is forcing him to do that. It is reasonable criticism to say he is make poor predictions.
His biggest error was the blanket rage against "AI" when it should have been focused on LLMs and data centers.
AI is a big field. Hating on AI is like hating food because you don't like broccoli.
Robotics AI that replaces high risk labor and even low risk repetitive stress labor is nothing but a win for humanity.
I knew him personally years ago and he broke my trust, my own opinion is that Ed wants to be popular and make money. He couldn't care less about being a diligent reporter that cares about the subject matter, he's a hype merchant jumping on one side of the band wagon to get clicks.
Says anonymous internet user with a 10 minutes old account.
I made the account to make the comment because I feel strongly about him being untrustworthy. You can take it at face value or assume I'm lying, that's your call.
On the off chance Dan sees this: one of the footnotes ("Some Zitron predictions" > July 2024) is broken. Right now it's showing a little 0 that doesn't actually link to anything if you click it :(
Most surprising thing to me here is tech giants growing 50%+ in 2 years. What's up with that?
I've said this before in here but Zitron is completely captured by his audience at best and a grifter at worst. A couple of months ago he was tweeting that people were crazy talking about _agents_, that they didn't _exist_ and that people talking about them were shills or bots. The responses were full of incredulous software developers saying but but but I use them every day, they're so good they're scary actually...
Zitron is just, like Dan Luu says, wrong about everything and doesn't care anymore, he's in the business of extracting money from his engagement.
> Among programmers and other serious users of AI, I would guess that Willison has a larger audience than Zitron.
You don't say.
This entire genre of pundit is just a person who has figured out that you can sell copium to the masses. Once upon a time this was a decentralized "this is how Ron Paul can win" thing on Reddit, but it was inevitable that slowly it would coalesce around these kinds of engagement bait people. Every subculture has its own such figureheads who DESTROYS opponents with FACTS and REASONING or whatever, but really it's just a reality TV show. The Alex Jones, Gary Marcus, and so on of the world are mostly just selling an entertainment product.
It's just a question of what the entertainment is. Some people feel good about being told "we were being hoodwinked; there are lizard people" and others feel good about being told "you'll be 100x healthier and good looking if you take these supplements" and others feel good about being told "these people are evil demons who are stealing your water" and others feel good about being told "these idiot rich people are going to lose their shirts" and so on and so forth. It's like how I like slice of life shows and hate horror movies and my wife likes horror movies.
In a sense, the misinformation gambit of LLMs did not come fully to fruition in the West (as much as it has in 3rd world WhatsApp forward land) because the locals were already a fertile ground of poor epistemic hygiene and well served by human providers of misinformation. Hacker News itself only has some hundred thousand commenters or so and even this requires a practice of aggressive information curation to prevent unrepentant misinformation repetition nodes from polluting one's belief set.
I’ve come this far without knowing who Ed Zitron is…
Hate on him all you want (he's gotten very repetitive for the sake of subscribers and reads), but the basic premise that the modern AI industry is a circular-dealing, point-of-diminishing-returns grift still holds. The bubble is here and the longer it inflates, the worse the pop will be. Sure the goalposts have moved, but the basic numbers don't math.
The current cross-deals aren't purely circular; quite a bit of revenue is, in fact, flowing into the AI industry from the outside (you know, via customers). What's more notable is the shared risk, as the deals tie multiple companies across the chain to a set of shared bets.
If the frontier labs suddenly found themselves unable to compete with cheap open weight models running on widely available compute, then one might expect the frontier labs to be the only ones exposed to that risk, while a chip-manufacturer like nvidia could thrive in either environment. A partnership or commitment from the chip manufacturers to the frontier labs could change that. Whether that kind of inescapable connection exists is hard to predict without a lot of specific modeling, and at this point I'm inclined to think that neither chip nor datacenter demand is going to drop any time soon, and that the commitments would be unwound before a company like nvidia is threatened.
> The bubble is here
Zitron implied 2 years ago that OpenAI would collapse by now. How's that bubble popping going? All NVDA+memory co+frontier lab numbers are accelerating
The thing about bubbles is that everyone who thinks they’re going to pop look crazy until they pop.
And to be clear, a bubble popping doesn’t mean that AI goes away forever.
What it does mean is that we’ll see some kind of economic crash or recession, and we’ll probably see at least one big company fail or go bankrupt/restructure.
OpenAI is the company in most obvious peril.
I happen to think that Nvidia is in a more perilous position than they appear. Their hardware advancement pace is relatively weak and they’re in a crypto-like hardware bubble where they’re one technology breakthrough away from a complete collapse in demand for their AI data center solutions. They’re also doing a lot of sketchy hardware financing schemes.
Comparing to other bubbles in the past, this one could still have something like 2 years left. Patrick Boyle has a video on the topic, in which he's also very careful to point out he could easily be wrong.
By all means, keep betting on this being a wild success and we'll see who's right in a little while. If you don't think this is a bubble then you're in for a ride.
The market can stay irrational for quite a while.
Look if we are going to raid pensions and 401Ks to prop up the valuation targets of Anthropic and OpenAI longer, then the bubble can stretch further and further, but eventually datacenters have to get built and powered. It's the power generation part that no one talks about. We simply don't have enough power in the United States to scale at the rate that Anthropic and OpenAI need to prop up their absurd valuations. AI is real, but these valuations are not.
TL;DR: Ed is directionally correct, but it's anyone's guess as to the exact timing.
In the meantime I'm not going to complain about subsidized credits from the big labs. :-)
Ed Zitron sells subscriptions to his blog. Whether he’s right or wrong is irrelevant.
Why would any rational person want to pay to read falsehoods?
I feel like just saying "wrong" to some of these feels a bit unconvincing.
e.g.
>April 2025: "It also, at this point, is pretty obvious that generative AI isn't going to do much more than it does today." >>Wrong
Is generative AI really doing much more today relative to 1.5 years ago? Sure there have been sone improvements, but i feel like nothing fundamental has shifted in that time period. Nor would i really expect it to even if the statement was false, but it seems too early to tell.
Zitron reminds me of a lot of people who got oversized reputations after the 2008 financial crash. They predicted it, or could spin past statements as predicting it, and rode off that.
But from that point on they basically assumed this role of what financial punditry call perma-bears, people who constantly predict financial doom. It gets clicks and sells subscriptions, which is probably why they do it. But from that point on their predictions weren't very good. If you constantly predict doom then every now and then you'll look like you were a genius, but it's just survivorship bias. People discount all the other times you were wrong.
I don't know a whole lot about Zitron himself. Didn't he get big calling BS on cryptocurrency stuff that actually was BS?
The problem is that AI isn't cryptocurrency. This is very real.
I do suspect there's some bubbly stuff around it. I think data center construction looks very bubbly, especially the totally ludicrous amount of permitted planned data center construction. I bet no more than 20% of that ever comes online. I'm sure there's some AI companies that won't make it, and a bunch that are overvalued. But AI as a whole is real, not just hot air.
I don't know anything about this guy, but based on the discourse every time he comes up, Ed Zitron is a more polarizing figure for HNers than even Trump. Everyone here loves trying to dunk on the guy, yet he's apparently living rent free in everyone's social media feeds.
I think it's a mistake to make concrete predictions about something like a stock market crash on a given timeline. As they say, the market can remain irrational for longer than you can remain solvent. However, Zitron is directionally correct about a lot.
I will say, the first part Mr. Luu says about big tech not being out of ideas is pure horse shit. Anyone who has worked in big tech knows that leadership at those companies can have no idea what they are doing and still be successful in earnings or the stock market. They are sometimes successful despite themselves.
I knew him personally years ago and can't take a word he says seriously, speaking from my own experience, he is not a trustworthy person. He wants to be popular not accurate. He writes to make bank, not to be a diligent reporter that cares about the subject matter.
Zitron is an AI doomer and a clear fact-distorter. I follow him because even a broken clock is right twice a day and I do think he's a pretty smart guy. I don't read his newsletter (it's basically word vomit these days), but his interviews are marginally interesting. One of the quotes in the linked article is totally correct:
> He found a niche in anti-tech grift, and is now exploiting the niche for all he can.
Ed gets hard because of the love the anti-ai people give him and seeing him as the voice of anti-ai... If you listen to his arguments though he lacks knowledge of what these companies even do. He's been on so many shows discussing the negatives but he admitted to not even using the models for anything
I cannot shake the feeling that his two failed marriages suffuse his extreme negative outlook on everything that is not Ed Zitron, especially AI. His comments about photo shoots* and men resenting his emotional honesty** speak of narcissism and perhaps why those marriages didn't work out. Good luck convincing a narcissist to change their mind about anything, I speak from unfortunate experience.
Or there's this one:
"I also have not taken the route you are "meant to take" to get here...I did not "earn my stripes" in the traditional sense, and those that have believe I did not earn my way here"
And maybe he lived in a van down by the river as well? I can't take this guy seriously, I just can't.
But I get that he speaks to an audience that needs to hear his take and that's their call. I don't have time and I won't make the time for podcasts and sitting through the worldview of anyone for hours at a time, 2 to 5 times weekly. No one is that interesting IMO.
*"I do a good photo shoot, I do a good interview, and I capitalize on events...I believe there are some that would like this level of attention or prestige, but they do not want to do the work to get it, and that chafes"
**"some men don't like me because emotional honesty and introspection are difficult for them."
just give it time, anyone (even those with 115k subscribers) who predicts a crash every day will eventually always be right. might take a decade or two… :)
both ed zitron and dan luu are professional bloggers who earn their living from selling ai sensationalism, zitron using paywalls and luu using patreon. whether the sensationalism is positive or negative, either way it is a very clear conflict of interest.
The first correct, detailed prediction (in print) about the collapse of Fannie Mae and Freddie Mac as a result of the subprime crisis was made by Max Keiser, of Karmabanque, in (Zac Goldsmith's) The Ecologist magazine.
In 2004.
And he'd been talking about it before then.
People thought Max Keiser was a crank; instead he made detailed predictions based on his intuitions, limited insider feedback and cold hard facts. He couldn't say exactly when it would happen; he laid out some horsemen you could expect for the apocalypse and this was one.
The thing about a bubble is everything is fine until it isn't. And it's worth observing that key parts of what Zitron is discussing has been covered in the WSJ and FT.
It's all very well posting numbers to "disprove" him when what he is pointing out is that the AI hype train is delusional and the costs are buried.
But Zitron is directionally correct, I think, particularly with regards to Oracle, where things he has said have literally come true.
Frankly as a Brit I remain amused at how much Zitron winds Americans up just by being himself — sweary, vulgar, rude, catty. And since non-Brits can't read Brits, Luu has to engage in pretty immature character assassination about it.
I've always been suprised with the amount people take him seriously. I think he's someone who makes people who dislike AI "feel good". I don't blame someone who doesn't understand AI or have read what he's written.
But for the bloombergs and other podcasts I would have expected them to do a bit of research. I honestly think with the amount of doubling down he's been doing that he's a grifter.
Obviously Ed is a special case, but let's be honest, pretty much anybody telling you they can predict the future is selling you BS. And that includes all the people confidently predicting he was wrong. The actual situation is, there are genuine unknowns driving things with significant influence, and nobody actually knows what is going to happen. At best, people can talk about risks and likelihoods of outcomes.
This submission has citations on where he was wrong, they aren't predictions.
Mo Bitar over on YouTube does the grumpy AI skeptic routine in a much more entertaining fashion.
His "Unethical guide to surviving AI layoffs" was solid gold: https://www.youtube.com/watch?v=JgVBqcqUGE0
> Now, if your CEO has never heard the phrase Ralph Loop, oh man, you are less than 30 days away from your next promotion. I'm not even exaggerating. Walk into his office, close the door, and say, hey chief, been experimenting with something. It's called Ralph Loops. And I think it could change literally everything. And he's gonna say, what's a Ralph loop? And you will say, give me $18,000 worth of API credits and I'll show you. Now you won't actually do anything, because you can't do anything. Because nobody can, because nobody knows what they're doing. But by the time he figures that out, you'll have a new title, and equity bump. [...]
> Talk about automation constantly. Nothing arouses the slumbering capitalists than the mention of automation. Drop names too, bro. Like talk about specific team members you can automate out of existence. Be like, yo, I automated Gary, bro. Tag Gary in the message. Tag him in Slack in a very public channel. Be like, yo, I just automated @Gary. His function has been Ralph Looped. And tag your CEO in the same message. You think you're getting laid off after that?
This is eerily similar to how a few people at work did some presentations about ralph loop and connecting agents to slack right when management was really pushing unrealistic AI productivity boosts. I was repeatedly asked to speed things up with AI while I was already heavily using AI to do work.
a thorough Fisking, nicely done danluu
the analogy to Ehrlich was strikingly apt
Not about Zitron specifically -- I don't read his study, but I don't know that making some statements in interviews or blog posts is the same as making a "prediction" (into which one would put much more though)
also statements can be interpreted many ways:
"Meta is dying" was countered by "Meta's revenue has increased since Zitron said that". OK, but 1) revenue/profit is only one measure of "not dying"; 2) what's the time scale? Nokia and Xerox were highly profitable companies that dominated their industries, and any prediction that they would go out of business at their height would have been laughed at, and yet, it wasn't too much later that they pretty much did.
He's dead wrong about the usefulness of the technology, but he's dead right about the uncontrolled corrupt circular financing that is driving this crazy over-expansion and market distortion. He fulfils a very useful function as a counterweight to the big tech horse-shit hosepipe that sprays us every day.
Off topic:
> For example, with a style that could be described as the opposite of clickbait, Simon Willison has written what I suspect is the most widely read blog among programmers for the past 3-4 years (in the same way that, at various times in the past, Joel Spolsky or Jeff Atwood or Steve Yegge seemed to be the most widely read programmer among programmers). Among programmers and other serious users of AI, I would guess that Willison has a larger audience than Zitron.
I have no idea Simon Willison is the most widely read blog among programmers. I truly have no idea, and I've been programming for just a decade.
A lot of Simon's blogs posted here are when new LLM models are released, on how good are these LLM models create pelican riding a bike using SVGs. Nothing particularly interesting to me.
I truly have no idea why would people be interested in blogs about LLM creating pelican riding a bike svgs every single time a new model is released. Maybe its a proof of AGI/ASI for some?
I guess to me, Simon Willison will always be the "create-a-pelican-riding-a-bike-using-svg-dude".
I used to read his posts about Django years ago (a little strange in itself as I'm not a Python guy) and it took me a while to realise he was the same person!
Zitron in general is representative of the conspiratorial thinking that has infected all spectra of the political space. Zitron obviously occupies more of the left space.
Good critique of LLMs & the companies behind them is hard to find, and it is harder when people gravitate towards this sort of thinking.
Zitron has staked his bear position and isn't budging, so regardless if he's been wrong and wrong again, he'll be remembered for calling the bubble if/when it pops, if only because so few in the media have done so without equivocation.
Zitron is the opposite of Jim Cramer. No Hype, no sales push, very cynical and conservative.
Saying someone is the opposite of Jim Cramer is basically saying they’re right.
The simplest argument against AI is the fact no public company appears to be making money on it, minus revenue that contributes to AI infrastructure.
Would love to see broken down counter example of public company.
So far Chegg and Duolingo have been devastated. Surely they could cut costs drastically with AI?
I don't know about Chegg, but the fundamental problem with Duolingo is their product does nothing to teach people a foreign language. The nasty reality of that product is if you go through their entire learning tree in a language, you might be at a CEFR level A1 for that language. And, you spent 10x the time and 10x the money you would have spent via something like Lingoda to get the same outcome.
This claim is just not true. And gets tiresome. You roughly end up where those courses claim to be in reading and listening - depending on language it can be over B1. (No course finishes B2, some do have B2 content). I ended up being able to watch some (not all) netflix series in foreign langue and I was in early B1 section. I clearly learned.
You also dont have to pay.
He's been right on the money. People here are mad that he is because they are profiting off of the grift of the bubble.
I just remembered that before AI, I knew Zitron from ranting about IoT and consumer tech. He just appeared one day in my Twitter Timeline, claiming to be the "man on the ground" at CES (or so my memory at least)
So from that standpoint, I guess it would make sense that a personality like that would now have ended up at the AI topic.
I would like to see a comparison with predictions of the pro-AI bubble and their hit rates though. This writing feels as selective as it tries to paint Zitron as.
All of the grifters (and lots of capital) can't wait to jump on the bandwagon because they see it as their chance to clean up. The same happened during the last 4 tech revolutions. (in my life so far: semiconductors, the internet, mobile communications, smart phones, crypto, EVs, probably forgot a few). And of course, as always, the longer term will be more amazing than the short term hype.
zitron is a jester. He knows his audience and plays it well. It is incredibly tiring to listen to his lies, but so are the AI boosters. I think it is net zero
Thanks for this post. Zitron is a prime example of how someone with little background, expertise, or domain experience can establish a grift in the outrage economy. Unfortunately, emotion and illusion when properly marketed can still go a long way in this world.
Easy to claim things as wrong without prodiving any facts.
Can I try?
> But when people bring him up, they're of course not generally citing his anger
Wrong.
> Google has been increasing the relative priority of revenue over the user experience over time
Wrong.
> I'm curious what people do after being on the wrong side
Wrong.
Some of the claims categorized as "wrong" are also completely true, such as training hitting diminishing returns. New models are barely an improvement and most people I know stuck on Opus 4.6 over any newer one for example.
Exact same thing for the claim "the fact we're running out of high quality training data and we're hitting the walls of scaling laws, in the training paradigm, these models aren't getting better. What we're seeing today is pretty much what they're always gonna be like".
If anything, model performance has regressed in actual use (i.e. not benchmarks) for the past half a year.
> Some of the claims categorized as "wrong" are also completely true, such as training hitting diminishing returns. New models are barely an improvement and most people I know stuck on Opus 4.6 over any newer one for example.
OK, but the first instance of a claim of diminishing returns was in February 2024, when GPT-4 was the best model available. Do you really think improvement since then has been minimal?
Yes, since 2024 the improvement has happened only in a few contexts, and the most famous¹ LLMs have also regressed in many contexts.
1 - Their numbers have also exploded, so I have no idea of any general rule.
I personally think improvement has been minimal since ChatGPT was released actually.
That's not defensible.
Only recently came across this guy and if u ignore the standard social media hyper hype hype he has, I dont think he is wrong even his 2024 predictions.
US has 1.5x the money supply since Covid. This means everything has to go up 1.5x to reach the same parity from before. eg inflation. All corporate earnings are going to inflate as 1b yesterday is 1.5b today.
There is no whete for these mega corps to go. They dont know how to grow. meta becoming well meta with the vr crap is case and point. meta blowing billions on a few hyped AI people is the nail.
Other than cloud, microsft/google aimt doing anything. xbox? nope, hardware? nah. It is all attention economy or selling the pick axes for it.
the only mega corp that still seems to be moving the needle is apple which i think speaks volumes.
Eds point is that AI tam or expectations are insane full stop and he admits coding has a use just not as big of a tam. Gen ai in art, music, etc did not take off at all esp compared to code. this makes sense, no one pays an artist 500k/year. their time is worth little compared to coding.
Where he is wrong tho is that this is not new. there is always a hype cycle of nonsense that screws the little people. what is new is the level of polarization. it feels like ai psychosis right now in ways that remind me of crypto but worse because ai is actually useful so people are even more insufferable.
Everything everyone is predicting has almost zero value. Nobody owns a crystal ball. Right now there could be someone working in a garage somewhere that could shake the entire LLM world to the core with a unique insight and innovation.
Think about the world before the 2017 "Attention Is All You Need" paper.
Did anyone predict that paper, what preceded and followed it?
Nope.
Same case now.
Maybe the word "prediction" is the problem; "guessing" would be better.
OK, what the heck. I'll make a prediction too:
You better buy SpaceX stock now. The way things are going in the US, the only way we build AI data centers at scale will be in space. Politicians have turned data centers into punching bags to be used to gain votes. We can't build power plants and people are being led to believe all kinds of things. Regardless of which, if any, are true or not, the rate of construction of AI data centers in the US is and will be seriously constrained by realities on the ground.
Hence my prediction: It's all going to space.
Zitron is providing a service: he's running the train for those who want to believe, or sincerely believe, AI is a bubble. His interviews are apocalyptical one sided rants that confuse what is with what Zitron thinks should be. I'm not sure he's wrong, by the way. As LLM performance is becoming more and more commoditized I fail to see how spend catches up to expectations to keep running this market as it does, but that's beside the point.
One annoying side effect is that YouTube's algorithms will always try to force feed you more of the things you last searched, to amplify your biases and send you down the doomscroll rabbit hole. So if you search for Zitron, next time you visit you'll be flooded senselessly with naysayers, contrarians and skeptics from all courses of life.
I think it would be naive to believe Zitron is unaware of what he's doing.
He's created a huge following (and is presumably making a lot of money) from pushing a hardcore AI-skeptic narrative, and I can't blame him for seeing that opportunity and running with it. We're ultimately all responsible for recognising these people and weighting their advise as necessary.
Additionally, from a public reputational perspective making bad predictions simply doesn't matter. In finance we're all aware of perma-bears who will predict the sky is about to fall, and when it doesn't just argue that the disaster is still coming, but is taking longer than expected, or that some unforeseeable thing happened which has compounded the risk but has for now kicked the can down the road.
So ultimately, it will be very hard to say Zitron is wrong unless he starts time-boxing his predictions, which I don't believe Zitron has done for obvious reasons.
That said I don't listen to him much at all. I've tried to listen to him a few times, but it's become evident very quickly that he doesn't understand the technical details enough to be making the predictions he's making and seems way too emotionally invested in the arguments he's pushing without good reason. I have strong personal filters for low-quality sources like Zitron – if someone raises enough flags I avoid them like the plague.
If anyone who predicts the future was reliably right, they could easily shut the hell up and become a billionaire on stock picks. But they don't do that, because nobody can predict the future. You can say what may happen, but not for certain, and definitely not exactly when. All predictions without insider knowledge are idle musings.
Also consider that the economy isn't rational. Our economy should have tanked several times by now. AI should have fallen apart by now. Meta, Google, Microsoft should have declined. Instead it's record profits. So don't try to make predictions by being rational.
It is funny to see mainstream media finally catching up to how much of a grifter this guy really is. I believe I was the first at least on HN to make a list of his horrible predictions over the time [1]. Since then Kelsey Piper [2] also wrote about it and got some traction.
I knew that somewhere in the future, something has to give because you can't just go around saying anything without losing some credibility. You still have some ardent followers in his cult of a subreddit.
But just to be clear: Ed is part of a bigger problem in tech journalism which is characterised by extreme pessimism and excessive skepticism. It is not correct to view Ed in isolation rather to see it as a part of the culture in which he can thrive.
[1] https://news.ycombinator.com/item?id=48447549
[2] https://www.theargumentmag.com/p/ais-biggest-critic-has-lost...
Great article. I was waiting for someone to eventually do an assessment on this grifter.
I appreciate someone picking apart Zitron in a constructive way. He’s been an easy recommend to folks in my circles who just want to be angry, but there’s a reason I don’t read his stuff on the regular or in detail: I don’t want to be angry, I want to do something.
And I say this as someone who started as a doomer, and is increasingly a pessimistic pragmatist (“LLMs have value as tools, but not nearly as much monetary value as the main players believe they do”).
I get it though: for those of us who grew up alongside the net and tech sector, who loudly decried M$ greed for ME/Vista/8/11 but celebrated them at XP/7/10, who remembered when Google’s “Don’t Be Evil” was spoken with serious reverence, the current era of tech feels toxic and nauseating. Current AI is a prime target for that discontent, as are the companies whose motives very clearly aren’t societal progress so much as reality authoring and authoritarianism. In that vein, Zitron is magnetic because his entire position is “you’re right to be mad and they’re all going to die from hubris without you having to actually do anything”, which itself panders to the human desire for personally preferential outcomes sans individual effort.
Properly picked apart though, and he has as much substance to offer as the ardent boosters: a handful of “trust me bros” with a smattering of distractions to wind you up, but never actually address your concerns or questions.
i relate to zitron cuz of how much he seems to genuinely hate the people in charge of this AI bubble. he, like me, seems to wish that when this all falls apart they get proportionate harm to go.
that'll obviously never happen. it's wishful thinking and venting tbh. that's why i like listening to his stuff.
it's better than reading the wholly AI slop docs my CEO keeps sending out
Posting revenue numbers as an example of a company not dying seems rather foolish. Microsoft's gaming side is floundering and dying and Linux has been growing at an unprecedented rate as a result of Microsoft's decisions. Not to mention the geopolitical aspects at play here as countries make a serious consideration to drop Windows.
These companies are all heavily buoyed by their investments in AI which is essentially an oroboros of money.
Damn the Ed Zitrone AI bots got to number 2. Impressive
I think the most enjoyable part of this is to have written it in the characteristic long-form Zitron wall of text style while still managing to pack almost the whole text with meaning, which is entirely the opposite of Zitron style.
Zitron is just a rage farmer that tells angry people what they want hear while selling them subscriptions.
Maybe he is well meaning, but it's pretty common these types are just milking an audience that they dialed in on with zero regard for integrity or honesty.
As always, shooting down commentary asking for more and more evidence is very simple.
Zitron has a somewhat ranting style. Luu's passage on Google search for example just nitpicks on the person that Zitron allegedly named as responsible for the decline of Google search.
The real issue of course is that search quality clearly has gone down. What does Luu want? A "study"? Everyone can see that. The person is not the issue.
This is a highly selective analysis of Zitron's writings that focuses on a couple of mistakes. People need to understand that any normie will understand the difference between rants, numbers and speculation in Zitron's essays. They are not written for autists who talk of "priors" and "evidence".
"This is a highly selective analysis of Zitron's writings that focuses on a couple of mistakes"
While reading this I was thinking it would be interesting to see just a few examples of Zitron predictions that he got right. Since you appear to follow his work, do you know of any?
The issue is the conspiracy. By pinning the whole problem on a single villain rather than the incentives the larger organization has created he 1. doesnt help solve the problem 2. creates an environment ripe for tribalism. Even if you ignore the racist undertones(fine its a stretch) he's still misleading people about what is happening.
I do think you have to consider predictions in the context of the world around them; he's been incorrect, sure, but has he been more incorrect than the predictions of those opposing him? Being less wrong than others is the same as being more right.
No idea what you're trying to say... he's been directionally wrong for years as the article illustrates clearly.
I want to point out that Zitron is _just a guy_. He’s not a billionaire CEO. He’s not a politician. He’s allowed to say what he wants whether it’s right or wrong, and _he’s just a guy_. He’s not swinging stock values for a group of insiders by tweeting. He’s not using pension funds to pay for a jacked-up IPO. He’s blogging and making a podcast, neither of which is compulsory for you to read.
You don’t have to spend effort proving him wrong. Just don’t read it and move on with your life. Regardless of which “side” of AI you’re on it’s kinda ridiculous how much effort gets spent on screaming gotcha at this one commentator.
He charges people money for a newsletter that reinforces completely detached from reality viewpoints. If he's just making stuff up, that's called grifting, and it's good people call that out.
> if he’s just making stuff up, that’s called grifting
So then we should be calling Dario out every time he opens his mouth, right?