How accurate have Ed Zitron's AI skeptic predictions been?

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.

> 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.

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

> 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....

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’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?

> 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.

> 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.

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 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.

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.

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’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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Do his predictions about the datacenters being a risky and unprofitable business suffer the same fate as the others?

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.

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.

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.

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 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.)

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.

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.

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.

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...

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.

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 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.

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.

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

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?

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.

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.