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

How accurate have Ed Zitron's AI skeptic predictions been?(danluu.com)

843 points by jatins 1 day ago | 1012 comments

achompas 1 day ago |

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.

coldtea 20 hours ago | |

>You can do that, but then you’re no longer discussing his predictions. You’re discussing your predictions, and your own positioning.

Depends if you care about the "prediction" part or if you care about the assessment of the situation (regardless of date).

If someone in 2000 said "the subprime mortgages market is a bubble and will blow no later than 2003", they got the prediction wrong, but their assessment would be right.

unsupp0rted 19 hours ago | | |

Predicting things 5 years too early is often as useless as not predicting anything.

You can say "AI will be able to _____" and be right 99.9 times out of 100, but the question is when.

You can say "The AI market will go to 0" and be at least directionally right eventually.

But none of it matters if you get the timing wrong.

RandomLensman 19 hours ago | | |

The subprime market changed quite a bit in size and how much was securitized in the run up to 2007, so not sure a prediction in 2000 for a 2003 event would have been easily transferred to what happened later. Would really come down to what specifically the prediction was based on for it to be a bubble in 2000.

qnpnpmqppnp 11 hours ago | | |

> If someone in 2000 said "the subprime mortgages market is a bubble and will blow no later than 2003", they got the prediction wrong, but their assessment would be right.

It doesn't make sense to split it though. Their assessment is that it's a bubble AND that it will blow no later than 2003. It's a single statement.

And it matters, because if all you're doing is saying there's an AI bubble then it's harder to prove you wrong but you also don't stand out and won't get a lot of credit for it. A very large number of people are saying the same thing as you, so who cares.

People like Zitron stand out because they go further than others and make detailed statements. Which happen to be wrong.

Zsfe510asG 19 hours ago | |

Zitron predicted the downfall of Oracle as someone mentioned below. He also predicted that the overhyped data center construction plans (Project Stargate, repeated vague Nvidia pledges) would not materialize.

If he got MSFT's cloud revenue growth wrong for this year, how much of that is selling shovels to OpenAI and how much is circular?

rtpg 1 day ago | |

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.

scared_together 1 day ago | | |

> The prediction was early, overestimated how long of a tail RIM would experience, but how wrong was it? Was the prediction of some utility?

Wrong enough that the utility is seriously diminished. Predicting a specific quantity dropping to a specific level at a specific date is a lot more valuable than saying “those guys are cooked”.

And even if some minuscule utility existed: why should predictors be so coddled by their observers? We should be demanding more rigour from predictors rather than looking for new and creative ways to forgive them for their folly.

threatripper 1 day ago | | |

Being early is the same as being wrong. Being lucky is the same as being right.

braiamp 13 hours ago | |

Ok, I was thinking that probably they were saying that he was accidentally right, but missed the timing. It's not that. It isn't that he was accidentally right in a certain scenario also. It's that "I reinterpret the prediction to make it fit my own vision of the world"... that's not how prediction works. Hell that's not how anything would work.

Here's an actual prediction I made about a year ago: LLMs have to demonstrate that they make productivity gains that explain the costs or economics will make this problem solve itself, via higher energy cost and loss of business/productivity.

That prediction is unbound in the time horizon but it's bound by conditions that explain the triggers and how they will behave. Such prediction is useful. Hell, I could even make a prediction on why the timeline can't be bound while making a prediction on the timeline: I predict that in the next 3-5 years this will have to solve itself, because there's a limit on how much money irrational actors can pour onto something that have limited value. 7-10 years is way too much. I at least hope their coffers are that deep... if this drags on long enough, at some point people are going to want a change

leoc 20 hours ago | |

In general I have about zero enthusiasm for trying to find defensible interpretations of things that Ed Zitron said, and I generally agree that the name of Zitron just largely needs to stop coming up in anti- and anti-anti-AI arguments since, it seems, he's just not a particularly insightful or reliable voice on the subject. That said, one or two of the specific assessments in Luu's article seem dubious as well, especially this one:

> August 2025 https://www.wheresyoured.at/how-to-argue-with-an-ai-booster/ : "These models have clearly hit a wall where training is hitting diminishing returns"

> Wrong

It was my understanding—and I'm no expert, so if someone does know better please correct me!—that indeed by the second half of 2025 training, and also post-training reinforcement-learning stuff, both hit seriously diminishing returns, and the thing that is continuing to scale well or pretty well is inference. See eg. https://www.tobyord.com/writing/mostly-inference-scaling . And in fact in the quoted and linked article https://www.wheresyoured.at/how-to-argue-with-an-ai-booster/ Zitron comes up with something which looks like a recognisable explanation of this:

> Because model developers hit a wall of diminishing returns, and the only way to make their models do more was to make them burn more tokens to generate a more accurate response (this is a very simple way of describing reasoning, a thing that OpenAI launched in September 2024 and others followed).

> As a result, all the "gains" from "powerful new models" come from burning more and more tokens.

AFAICT the other drivers of recent progress in LLMs have been: ploughing in lots and lots of specialised training data custom-made at piecework websites https://www.youtube.com/watch?v=4pG3SJQPAwk ; and work on harnesses and the like. AFAICT neither of those makes false the claim that "[t]hese models have clearly hit a wall where training is hitting diminishing returns" either. Similarly, even if some big new advance does cause training or post-training to start scaling like gangbusters again in 2027 or 2028 that wouldn't make the quoted statement clearly wrong: Zitron would clearly like you to infer that there won't be any further big advances soon in LLM training, but the quoted statement doesn't clearly make that claim. (Even if he had made that claim, and it did turn out to be wrong, it would be a relatively forgivable error, more on the "cloudy crystal ball" than "misstates currently known facts" end of the spectrum.)

So: it seems that Luu took a fairly specific, objectively judgeable claim from Ed Zitron; and that claim was ... correct?; and Luu instead rated it "Wrong" without further elaboration. It seems that Luu interpreted the quoted claim as saying something like "model progress has ceased"; but it seems that's not what that specific claim (as opposed to whatever other things Zitron has said at other times and places) said.

jefftk 20 hours ago | | |

>> August 2025 https://www.wheresyoured.at/how-to-argue-with-an-ai-booster/ : "These models have clearly hit a wall where training is hitting diminishing returns"

>> Wrong

>It was my understanding—and I'm no expert, so if someone does know better please correct me!—that indeed by the second half of 2025 training, and also post-training reinforcement-learning stuff, both hit seriously diminishing returns, and the thing that is continuing to scale well or pretty well is inference.

I'm not an expert either, but while I do think for a bit it looked like ~all the improvement was inference-time scaling, it hasn't stayed that way. Mythos/Fable is likely a very large model (ex: it knows many things without searching) and this is probably part of its high level of capability, and the companies have started doing very large amounts of RL (which in OpenAI's case led to the HF attack).

square_usual 17 hours ago | | |

> and the thing that is continuing to scale well or pretty well is inference

No, the models are just more intelligent. GPT 5.6 Sol can do more in fewer output tokens than any model from late 2025. Test-time compute isn't the only lever the labs have for scaling. This is among the two major things Ed has gotten laughably wrong in his technical predictions (that TTC was the last resort to make models better, and that synthetic data wouldn't help)

ssalbiz 19 hours ago | | |

My understanding is that RLVR, synthetic data generation and a slew of other post-training techniques are what have driven many recent advances in models more so than manual data providers. The economics of that are for sure worse than just scaling pre-training but it is incorrect to think that test time inference scaling and manual data entry are the only ways in which models are advancing.

emp17344 1 day ago | |

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.

mrweasel 1 day ago | | |

Years back John C. Dvorak talked about predictions. He's was being ridiculed for his comment that there was "no evidence that computer users would want to use a mouse" (which was sort of true at the time). One of his point was that he had made a crazy amount of predictions on various topics, some came true, many didn't. People just remember the one you got right, and the ones you got horribly wrong.

Ed Zitron is just one AI crash away from being known as the guy who saw this coming. Everything else he has said can be completely wrong, he just needs to be somewhat correct on a minor crash.

frereubu 22 hours ago | | |

I think it's fair to say predictions that Altman and Amodei make should never be taken at face value, as well as Zitron. That's fine. But that doesn't have any bearing on Dan Luu's claims. This feels like an example of what he talks about in the article when saying that people respond to his claims by pointing at something entirely different. That is to say, whether AI enthusiasts make silly predictions doesn't mean that these companies aren't going to be profitable, or that any of Zitron's predictions are any good either.

aetherson 1 day ago | | |

What else would his repute be based on? Maybe telling retrospective truth? Per the article, he does terribly by that metric as well.

retsibsi 16 hours ago | | |

Isn't that pretty much his whole thing, confidently telling us what will happen? Of course his reputation should suffer if his predictions are wrong, as should those of the others whose correctness : confidence ratio is too low. (But if their reputation/power/relevance mainly comes from things other than their punditry, we can't really stop 'taking them seriously' altogether.)

fulafel 1 day ago | | |

I thought in the post Ed was being evaluated based on all his predictions, and it turned out all of them were wrong.

Most people will read the post as going over all the falsifiable predictions and none of them panning out, since after the chronological prediction list it says "After this point, most further predictions that I saw were either non-falsifiable or resolve in the future".

If Dan is reading maybe he can clarify?

zahlman 21 hours ago | | |

Because Zitron is specifically making a name for himself as a critic making bearish predictions; Altman and Amodei may have made unreasonably bullish predictions, but they've also done other relevant things like e.g. being involved in the actual development of the models.

mvdtnz 1 day ago | | |

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.

jrflowers 22 hours ago | |

This is an article that only cites Zitron’s opinions about subjective model quality. You’re tisk-tisking people to be objective about a bunch of words saying that the author’s opinions are better opinions than the guy he’s talking about OP

Some guy wrote that he’s grumpy because he couldn’t sleep and decided to dunk on an internet personality he doesn’t like, it’s not the ceremonial placement of the ur-kilogram

Aerolfos 22 hours ago | | |

> This is an article that only cites Zitron’s opinions about subjective model quality. You’re tisk-tisking people to be objective about a bunch of words saying that the author’s opinions are better opinions than the guy he’s talking about OP

Oh it's not just the author's opinions. They're the opinions of a bunch of LLMs he checked, too. Much better.

johnbarron 22 hours ago | |

>> 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.

Dan Luu did not engage on anything more, than a disorganized wall of text, ranted like a teenager using toxic personal attacks, while obsessing over calendar errors and a placeholder in a spreadsheet. If this is what passes here for a smart engineer...Lets analyze his post in a more logical and analytical way:

- His entire argument is based on the naive logic that because LLM execution speeds or benchmarks marginally improved over the last 24 months, the entire trillion dollar investment cycle is justified. A short window of venture subsidized chip buying...tells you absolutely nothing about the multi decade debt structures, physical infrastructure depreciation, and power grid constraints that dictate whether a capital heavy business model survives.

- While he whines about Zitron numbers, fails to provide a single! macro level equation to address the real financial threat. NYU finance professor Aswath Damodaran for example, explicitly warned that the current AI build out is an asset heavy, debt funded run up backed by private capital markets. Unlike the dotcom boom which was equity funded and contained to tech shareholders today AI infrastructure burdens companies with a massive $80 billion in CapEx per gigawatt, meaning a monetization correction will trigger widespread systemic debt distress and loan defaults across the real economy.

"Aswath Damodaran: Big Tech Has No Idea How AI Pays Off" - https://news.ycombinator.com/item?id=49229981

- Luu and this HN crowd, today in a mob mood...completely ignore the highly unstable plumbing of the sector growth metrics. Patrick Boyle is a quantitative finance professor and former hedge fund manager, and has meticulously mapped out the mutual dependence the entire AI boom. Big Tech companies are pouring massive venture pools into AI startups, which are then contractually bound to hand that cash right back to the hyperscalers to buy cloud compute. Analysts have identified more than $800 billion in these arrangements:

"Why Wall Street is ignoring big tech's debt" - https://news.ycombinator.com/item?id=49230630

- The worst of Luu logical failure, is ignoring ( on purpose? ) were Zitron numbers come from! They come from some very disciplined institutions, which Luu completely ignores. Citigroup quantitative analysts project cumulative global AI CapEx hitting $9 Trillion through 2030, with maximum global AI revenues ( not profit...) covering less than 30% of that expenditure.

- To break even on the physical infrastructure currently under construction, the AI sector needs to generate over $2 Trillion in annual end user revenue by 2030. Total actual revenue generated across the ENTIRE global AI sector today sits at a fraction, around $150 billion.

- Anthropic in a hysterical push, to make it to public markets, before the bubble bursts, recently claimed their addressable market is 30 trillion... the whole of US economy. Are we getting a post from Luu on that? This of course this ignores that MIT Professor and Nobel Laureate, Daron Acemoglu, mathematically proved that while 20% of all labor tasks are exposed to AI, only about 5% can be automated profitably due to upfront enterprise systems integration and the high financial burden of constant human in the loop verification.

"A new look at the economics of AI" - https://mitsloan.mit.edu/ideas-made-to-matter/a-new-look-eco...

- Dismissing the AI bubble thesis, because you found a spreadsheet typo in a newsletter, and ignoring the other voices who are aligned with Zitron core premise, means you are also dismissing the research of a Nobel Laureate in economics, the Dean of Valuation, veteran hedge fund managers, Barclays, S&P Global, and Citigroup. Arguing that "the models are hitting benchmarks" while ignoring that the physical balance sheets and enterprise budgets cannot support a multi trillion dollar infrastructure build out, is exactly the type of Dunning Kruger this corner excels at....

Ed Zitron is correct, despite the clumsiness or unpleasantness of his message delivery, and this community reaction, will be an historical record of the AI bubble crowd madness.

It took years to take down Maddoff, and more to take down Bear Stearns. It will take maybe 5 - 10 years of "Ed Zitron is wrong posts here" until Anthropic and OpenAI have to be bailed out by the US government, but the day of reckoning will come. The end of this universe is all tax payers will own a piece of AI and will pay for it with increased interest rates for the next 25 years...

velox_neb 17 hours ago | | |

> the naive logic that because LLM execution speeds or benchmarks marginally improved over the last 24 months, (...)

"Marginally improved"? Are you really going to sit there tell me that an appropriate way to sum up the difference between the AI we had access to in Sep 2024 and the AI we have access to now, is "the benchmarks marginally improved"?

RandomLensman 21 hours ago | | |

What do you mean by "take down Bear Stearns"?

Btw., projections are just that - projections and I am not sure Acemoglu proved things mathematical (as in a mathematical proof) but rather within the context of a model/assumptions.

That financial markets/innovation can outpace the actual innovation is also not some new insight, but that alone doesn't necessarily make for a useful prediction.

scared_together 13 hours ago | | |

The post is titled “How accurate have Ed Zitron's AI skeptic predictions been?” not “How accurate will Ed Zitron’s AI skeptic predictions be in the future?” or “Is the entire AI industry build out justified?”

If Patrick Boyle, Aswath Damodaran, and Daron Acemoglu have more accurate reporting and predictions about the upcoming decline of the AI industry, maybe those are voices who should be elevated over Zitron.

qnpnpmqppnp 20 hours ago | | |

If Ed Zitron was merely saying that there is a AI bubble on the markets that will ultimately collapse even if we're not exactly sure when and how, then such prediction would be less interesting but also much harder to disprove.

But that's not what he's saying. He's making very specific claims that are indeed proven wrong. You can't honestly say he's correct, and the burst of an AI bubble will not be a reckoning.

tccole 17 hours ago | | |

You maybe right, but why don’t you put your prediction in Metacalculus or a prediction market. Thats what they are for.

mschuster91 21 hours ago | | |

> It took years to take down Maddoff, and more to take down Bear Stearns. It will take maybe 5 - 10 years of "Ed Zitron is wrong posts here" until Anthropic and OpenAI have to be bailed out by the US government, but the day of reckoning will come.

Unfortunately, the market can stay irrational (far) longer than you can remain solvent.

In any case... I doubt Anthropic, OpenAI and xAI have any kind of moat that can justify a bailout. There is nothing truly unique either of these three possess, and certainly not against the free competition mostly from China or from Facebook that anyone can self-host.

Who will get the bailouts instead is the pension funds and other investment vehicles that have been force-fed crap AI stock like foie gras geese.

overfeed 1 day ago | |

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.

dyarosla 1 day ago | | |

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

TulliusCicero 1 day ago | | |

I mean if his personal work is incompetent or dishonest...?

One of the easy ways to evaluate this is: how has he taken being incredibly wrong about his extremely confident predictions over and over and over?

Typically with people like this, they completely shrug off being super wrong. It's barely even a blip on their radar, and even bringing it up is a good way to get them to immediately attack you to deflect attention from how bad their predictions or assertions were.

If you're constantly making predictions on Topic X, and said predictions are consistently, wildly wrong, and you never actually grapple with that or acknowledge how wrong you were in the past, then that's, at the very least, intellectually dishonest.

But by all means, someone link us to his blog posts where he goes over his wrong predictions without excuses or deflections. I'd be happy to change my mind.

dosisking 1 day ago | |

AI companies will never go to zero because AI is part of the Military Industrial Complex now. All the money is coming from the military and government for surveillance and power and war.

wmf 1 day ago | | |

Speaking of wrong predictions... the entire US military budget would have to be spent on OpenAI/Anthropic to keep the bubble from bursting.

simianwords 1 day ago | | |

Every conspiracy theory has an escape hatch

yousif_123123 19 hours ago |

Things in general I think he's right about:

1. Revenue if anthropic and openai is unlikely to grow to the high levels they need to pay for their commitments. Many of their heavy users (coding) will eventually offset a lot of usage to more efficient and cheaper open weight models. I know of people in a company I was at that spend thousands of dollars a month on tokens. I am sure that what they're using it for can be substituted in large part by way cheaper models.

2. A lot of corporate AI usage is being pushed by management that doesn't really understand the extent of its useful, and just wants to call themselves an AI-first company.

3. If this datacenter build-out proves to be beyond the actual demand, there might be a big economic crisis as to how much of the financial system is getting tied up with it (insurance money, private credit).

Whether openai and anthropic actually die, I'm not sure. But I don't think they'll be the next big tech companies. I think eventually they'll be absorbed by others.

The whole thing I think, can be summarized as: LLMs will be commodity like. And it's price will go down and eventually will run locally, it's not at all clear that this will bring AGI and that it's worth infinite amount (or trillions) of investment ahead of the actual demand or the AGI level do-it-all-for-you AI being reached.

layoric 1 day ago |

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.

th0raway 1 day ago |

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

simonw 1 day ago |

> 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.

minimaxir 1 day ago |

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.

kbelder 1 day ago | |

>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.

polski-g 1 day ago | |

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.

DiogenesKynikos 23 hours ago | | |

One thing I've noticed is that since LLMs came out, scientific papers with poor English have essentially disappeared. Just one of the many ways that AI is changing the world. People are using AI in all kinds of fields.

swiftcoder 1 day ago |

> 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....

pinkmuffinere 1 day ago |

> 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.

pinkmuffinere 1 day ago | |

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.

janalsncm 21 hours ago | |

Oh nice, I came here and made a very similar comment. I like the Easter eggs that reward readers who are paying attention.

janalsncm 21 hours ago |

> February 2025: "I will keep writing this stuff until I’m proven wrong." Wrong (Zitron continues to write despite repeatedly being proven wrong)

This was a good one.

wccrawford 19 hours ago | |

Hilarious, but he never actually said he'd stop writing, just that he'd continue writing until proven wrong.

And provably, he did. He wrote until then, and continued after. Since he never stopped writing, he met the challenge.

He's now free to stop writing whenever he wants and still not fail that statement. ;)

spiderfarmer 19 hours ago | | |

Are you a software tester?

root-parent 21 hours ago | |

The doctor said I was sick...but I did not die on Tuesday, so checkmate!

You are confusing an imprecise prognosis with a false diagnosis. And The funniest part is that "he keeps writing, therefore he was proven wrong" contains no actual proof that he is wrong.

adroitboss 21 hours ago | | |

Imprecise and incorrect are the same thing when it comes to an exact science. His predictions include dates and that makes them binary. You can only be right or wrong. Being close is still incorrect, and he's not even close.

janalsncm 8 hours ago | | |

It’s more like if Zitron was a doctor his prognosis would be “you’re going to die on Tuesday” and you come back on Wednesday (after not dying on Tuesday) and he defends it by saying “everybody dies”.

aspir 1 day ago |

> 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.

supern0va 1 day ago | |

>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.

alephnerd 1 day ago | |

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.

DonsDiscountGas 1 day ago |

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.

GaryBluto 1 day ago |

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.

mawadev 17 hours ago | |

Exactly, he is monetizing the dramaslop. A sack of rice falls over and suddenly the world is on the brink of collapse. A fun exercise to see how lunatic this pattern of fear is, you can look for an echo chamber you know nothing about, maybe games or music or DIY or kitchens or whatever on youtube and suddenly you will see the same patterns play out. It is quite sad to see people do this for a living, but it is what it is. The kitchens are funny to me, because apparently there is a grand conspiracy of kitchen companies forming a monopoly funded by whoever and basically thats why you will never be able to cook like you used to be able to back in the day and basically its over. Just typing this out made me smile.

IMO Ed is entertaining and I don't believe much in LLMs, but I personally don't really care what happens next with it or what happens at all, the world will continue to spin.

philipwhiuk 20 hours ago | |

Or Trump/Fox saying the Iran special military operation will be over in X days? Or Putin/Russia saying the Ukraine special military operation will be over in X days?

Let's not pretend they didn't get it from somewhere.

q23lk 1 day ago |

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.

hydrolox 1 day ago | |

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.

strange_quark 1 day ago | |

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.

vehemenz 1 day ago |

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.

torginus 1 day ago |

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.

scared_together 1 day ago | |

I can agree that the Gemini usage number is a marketing number NOT to be taken at face value. And so does Dan Luu, in the "Some reactions to Zitron" section of the article:

> BTW, a funny thing about Gemini hitting 500M users being "so unrealistic that someone at Google should have been fired, and that someone is Sundar Pichai" is that Zitron has also (incorrectly) said that Google doesn't know how to grow, and that as a result they're shoving AI everywhere. Dennis Snell pointed out that, if Zitron takes his own statement seriously, Google can make Gemini's user numbers go to any number it wants by doing the exact thing Zitron said they would do, sticking AI everywhere.

> You can't actually take Zitron's statement about Google's lack of growth leading to AI desperation seriously and also take it seriously when he says that Sundar is committing some kind of gross malpractice by naming a number like 500M users.

Other than the Gemini usage numbers, which are the marketing numbers being taken at face value?

aesthesia 1 day ago | |

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.

delis-thumbs-7e 1 day ago |

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.

randomImmigrant 1 day ago |

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.

drayfield 22 hours ago |

I used to be a fan of Zitron after listening to an old podcast of his, and also subscribing to his newsletter. Something weird happened after Taylor Lorenz guested on his show; a week later I received a welcome email to Taylor's own newsletter. This was especially strange because I definitely hadn't signed up to hers, and use individual masked emails in Fastmail per different service so I was sure that this was the email address originally used for Ed's newsletter. I tried to contact Ed to no avail, and since that day I never could shake the feeling that he just gave Lorenz his subscriber list. I can't prove it for certain, but there was definitely something "off".

aurareturn 21 hours ago | |

Ed Zitron is a grifter. Period. I highly doubt he believes any of the stuff he writes himself. He plays a role in society which is the role that tells people AI is going to fail so those who don't participate in or benefit from AI feel better. They sign up to his subscriptions and pay him money to confirm their own bias.

If you look at the sub reddit r/betteroffline where these people gather and worship Zitron, most people there are economically motivated. Most of them want AI to collapse so they can invest in stocks when it's cheap or they hope AI doesn't take their jobs.

thoughtpeddler 15 hours ago | | |

Doesn't it say something about our society that (a) it's known (at least among smart people, however 'smart' is defined) that AI is going to take away jobs, and (b) the way its treated is that people gather to online discussion forums to worship someone saying the thing that will replace their jobs isn't going to do it (but in actuality, eventually will)? In other words, who's actually doing anything to help the people out who will lose their jobs??

tolugenius 1 day ago |

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.

amoorthy 1 day ago |

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.

manlymuppet 1 day ago |

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.

teekert 1 day ago |

Ah well, people love hearing what fits their world view. So if you hate LLM assisted development or vibe coding, Ed is predicting the future you want ("Don't be afraid, it's going away soon!"). As with any sudden change, there are people that tap the brake instinctively. And people like Ed thus get popular.

That, and he has a nice way of speaking like everyone's gone mad but you and him ;) Have to admit I have enjoyed his rants, and there are certainly true things about them, here's another nice one for you lovers and haters alike! [0]

[0] https://www.linkedin.com/embed/feed/update/urn:li:ugcPost:74...

thelastgallon 1 day ago | |

I like this version:

AI Economics for Dummies: https://www.mcsweeneys.net/articles/ai-economics-for-dummies

sfblah 1 day ago |

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.

rawgabbit 1 day ago |

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.

bravetraveler 22 hours ago | |

> assume everyone else on Hacker News does

Eh, not to be rude/crass... but that would be inaccurate, if not hopeful. Myself and others don't, despite mandates; in fact, I aim to see this 'left behind' promise we heard years ago. Short of writing the at-will employment paperwork for HR myself, I'm not seeing it.

Escalations continue to fill my days. Turns out, people are somewhat correct: results matter. I'd say moreso than the tools we 'choose' (or skip, in this case). My null on the token scoreboard remains unnoticed/inconsequential, the work I've done has not.

All to raise a bit of timeless advice from Wu-Tang: diversify.

mustaphah 1 day ago |

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.

BeetleB 1 day ago | |

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.

emp17344 17 hours ago | | |

Everyone is always throwing darts at a dartboard when making predictions. I don’t know why you think this is a critique that applies exclusively to Zitron.

enraged_camel 1 day ago | |

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.

autaut 1 day ago |

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?

george_max 1 day ago | |

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.

reticulates 1 day ago | | |

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.

baron816 1 day ago | |

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

tkel 23 hours ago | |

Yeah, the three tables just looking at revenue and profit YoY is pretty laughable financial analysis.

qw2817 1 day ago |

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?

ai_critic 1 day ago | |

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.

aksj5Hg 1 day ago | | |

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.

tomjakubowski 1 day ago | |

the dates of his articles (well, month and year) are all here: https://danluu.com/

socalgal2 1 day ago |

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.

1970-01-01 1 day ago |

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.

iLoveOncall 1 day ago | |

> but the test results are evident, empirical, and hold up to hard scrutiny

Sorry which test results? The gamed benchmarks?

1970-01-01 1 day ago | | |

https://x.com/victormustar/status/2094901703468306626

torvin92 22 hours ago |

Zitron pretty much called the rise of AI content farms and the ensuing SEO spam. His takes on practical AI limitations were spot on.

psvv 1 day ago |

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.)

janpeuker 20 hours ago |

To be fair not predicting accurately doesn't necessarily mean they are wrong - Michael Burry is the perfect example here, a market may actually just be so fraudulent (AI companies being funded by AI companies etc) that it can defy common economics for a while.

qnpnpmqppnp 19 hours ago | |

You're right or wrong in relation to a given statement.

If your point is just that there may be an AI bubble, then yes the fact that it hasn't popped yet does not prove it wrong. But that's not what Ed Zitron is saying; he's making very specific statements that happen to be wrong time and time again.

As many said in the comments, it's common for doomers to keep predicting a crisis, every month and every year and so on, until inevitably a crisis does occur and they claim they were right. That's not how it works.

gradus_ad 15 hours ago |

If we look at the demand side:

1. Conversational AI - this is ubiquitous now, but not sure it's increasing at any significant rate. At least my personal usage has leveled off. Also probably not a significant driver of per token demand relative to code gen. More a driver of subscription revenue.

2. Code Generation - this is the big killer app, which I suspect has driven most if not all of the last year's revenue growth for Anthropic and to a lesser extent OpenAI. Now, I doubt we can extrapolate that growth given 1) how quickly and completely CC has been adopted by the industry and developers and 2) how corps are reigning in spend

3. Image and Video Generation - this honestly strikes me as more of a trifle/novelty than anything else. Granted I'm not a visual artist but I don't see it being a killer app anywhere to the extent of code generation.

4. Physical AI - this is the wildcard for me, but also beyond my ability to conceptualize its effects on demand. I suspect a proliferation of self driving and autonomous robotics would be a huge driver of compute demand but who knows how close we are to proliferation?

xbmcuser 1 day ago |

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.

solid_fuel 1 day ago |

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.

PowerElectronix 23 hours ago |

Unless they find a way to make money on this, Zitron will eventually be right.

throwawayqqq11 1 day ago |

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.

fyredge 1 day ago |

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.

rsynnott 10 hours ago |

> "Sam Altman deputizing Orion from GPT-5 to GPT-4.5 suggests that OpenAI has hit a wall with making its next model, requiring him to lower expectations" > Wrong (GPT-5 was a substantial improvement over GPT-4.5)

… I mean, this feels slightly irrelevant? Orion _does_ seem to have been demoted from 5 to 4.5; that they later released something they felt they could reasonably call gpt5 feels slightly beside the point there.

raincole 1 day ago |

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.

pcstl 1 day ago |

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.

rrrx3 17 hours ago |

I was a fan of his writing for a long time, but it's clear that the guy has fallen down the "build an audience that's only here for baying for blood on one particular topic" hole and won't be able to escape it.

He used to be really thoughtful and funny about the topics he took on. And I realize that's pretty standard for a critic. But now he just keeps digging deeper and deeper, getting more things wrong post after post. His posts have grown to probably 3x the frequency and 3x the length of when he was talking about stuff like Google tanking their Search business by bringing in the Ad guys.

He really used to be a "little extreme" with some really grounded viewpoints. Now it's more like he's performing the "angry british guy" in order to maintain his impression count and audience.

It reminds me a LOT of that Eli Schiff guy in the design world. A mediocre designer who couldn't get untangled from one specific design style, who figured out that anger drives clicks. Schiff became a "design critic" who eventually fell down the alt-right pathway and ended up becoming a pariah. I'm not saying Zitron is gonna turn into some right wing nutjob, but he's falling down the nutjob path right now in real time by consistently staking out the worst ungrounded takes and continually doubling down on them.

truelson 1 day ago |

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.

ACCount37 1 day ago | |

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.

elictronic 1 day ago | | |

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.

tavavex 1 day ago |

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.

djabatt 14 hours ago |

Ed and his class of people are entertainers that get confused at experts for journalists. None of them toil at the prompt sorting things out directly. The media entertainment class frustrates me. They often spread sound bites that are off by big margin and shift markets. I find podcasters that are curious about a subject are better at finding the truth about a tech subject then finance wonks that chatter about sounds bites.

nowittyusername 1 day ago |

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.

ddp26 15 hours ago |

Even though these predictions turned out mostly wrong, we should not castigate people for publicly forecasting! That is virtuous, and more people should do it.

Thank you Ed!

serioussecurity 1 day ago |

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.

jrflo 1 day ago |

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.

onemoresoop 1 day ago | |

The fraud is there. Whether it surpasses Enron or not will be revealed in the future.

arctic-true 1 day ago | | |

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.

dgellow 1 day ago | | |

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

tim333 1 day ago | | |

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

jrflo 1 day ago | | |

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!"

brikym 1 day ago |

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.

elictronic 1 day ago | |

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.

AlexCoventry 12 hours ago |

I think the most likely way for Zitron to find vindication is through the world war we seem to be shambling into. That could easily put a stop to AI improvements, because the supply chain is so fragile. But that would have nothing to do with his ostensible reasoning.

kif 19 hours ago |

It is a curious exercise to look at the predictions of AI companies/their CEOs, too.

Frequently we'll hear from Amodei that AI is 6 months or 12 months out from replacing Software Engineers. Or we'll hear that their model is safe when regulators step in, but suddenly it's too dangerous and hacked its way towards its goal when other companies claim the same.

What they have in common with Ed Zitron is that they are both trying to sell you something.

anonymous_user9 1 day ago |

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.

stego-tech 1 day ago | |

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.

zippyman55 12 hours ago |

I really like reading him. I do wish is posts were a lot shorter. I get tired of all the 60/40 percent forecasts that have enough wiggle room the forecaster never thinks he is wrong. I certainly dont get that from Ed!

rr808 1 day ago |

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.

eaglelamp 1 day ago |

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.

brawnAgain 1 day ago |

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.

fwipsy 1 day ago |

> 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.

mark_l_watson 1 day ago |

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.

chipgap98 1 day ago | |

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.

hyperbole 1 day ago |

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.

bawolff 1 day ago |

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.

mattbrewsbytes 1 day ago |

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.

jsrozner 1 day ago |

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...

eqqn 18 hours ago |

It is nice to see an attempt of sorts to discredit, and indeed Ed is not always right. But the bigger picture is debt fueled AI buildout frenzy, regulatory capture, monopolising and gating models, tokens/compute is still losing money compared to observable revenues from customers. Otherwise we would not need inventive accounting practices, SPV's, theatrics on distillation, stopping frontier development and so on.

But taking claims from Sundar about 750M gemini users in 2025 at face value is disingenuous. This basically includes everyone who owns an android phone and opened a Gmail and Google search, translate. Congrats, you are gemini user now. Every product has received AI "feature", like your android assistant offering to listen to you while the screen is still locked by default. Dan's only sources are press releases of the AI companies. As I'm reading this, he dedicates at least 3 paraghraphs showing how Ed is wrong. And keeps coming back to it again and again. Okay so we are both refuted and proven wrong, but is that really the extent of AI use? Is this the revolution? Replacing existing function with inaccurate AI sourced from reddit posts?

I've read a number of both blogs. I'm not gonna watch Diary of CEO video. Yes, models have gotten crazy good in 2 years. Still the same failure modes. Dan's writing here comes across as same type of gish gash he rails against, minus the entertainment value.

huurtehoog 18 hours ago |

Every transaction in the financial market is a bet with two sides with opposite beliefs.

I don't get why people make such a big deal off bears and bulls. Everyone is on one of these sides at every investment they make or liquidate.

knaeckeKami 17 hours ago | |

Zitron does not seem to put his own skin in the game by going short though - He sells bearishness via his substack, podcasts and media appearances.

huurtehoog 6 hours ago | | |

My point is not that putting your money where your mouth is or shut up.

My point is: all analysis is contingent, there is no point in saying bulls or bears are chronically wrong or that they should beat the market to merit being listened to.

thimble_io 1 day ago |

Zitron's takes on AI hype vs. reality look pretty prescient. My coding job is definitely safe, still.

dannersy 23 hours ago |

I find it bizarre that this blogger can make sweeping claims of someone being wrong, quoting specific values that are admittedly speculative, and then just using them as gotchas for being wrong. The then ignore the conclusion that those "wrong" yet close values mean in the grand scheme of Zitron's point, even when the margin of error was inconsequential.

For example, one of his first big criticisms of Ed is Ed's claim that Meta has a dying product and its a dying company. Do I really need to look at the numbers here? Or should we look at the companies actions and history WITH the numbers included?:

- Metaverse was a complete and total disaster and forced upon the company by a CEO who is clearly completely out of touch but infallible within the company.

- Facebook is a bot riddled, AI slop haven, used only for special cases and is basically unanimously hated by the next couple generation of users. Users who are critical for revenue if the serving ads to bots scam ever implodes.

- Meta's successes seem to be solely on knowing who to buy and have failed for a decade to innovate anything.

"Dying" is not the same as "dead". As someone else has said, but I have forgotten who it was, Meta is a "mature" company trying to be young and sexy again when they should focus on their existing products.

How does anyone come away from all this with a business, where we hear all of the horrible things about their internal culture, that an AI pivot to be anything but a trend following desperation move? Then the author addresses but shrugs off entirely the fact that they now hide their Monthly Active Users. I think all of this context is pretty fucking important to think about with the numbers, especially since Meta is trending down when we get the totals for the year. Zitron's point, again, still tracks because you can list a portion of "profit" but it is too early for 2026 since they intentionally use misleading numbers. I would be very interested to see what the first half of 2024 and 2025 profit numbers were before the total year calculation. Either way, Meta's dump into AI is a huge gamble from the company that must pay off.

I don't know. I think this guy does not like Ed Zitron, which is fair. I see a man pointing fingers at someone while doing the same things he is criticising: Taking the speculative and sensational as literal and using it as some sort of gotcha to be speculative and sensational themselves.

makingstuffs 17 hours ago |

> February 2025: "I will keep writing this stuff until I’m proven wrong." Wrong (Zitron continues to write despite repeatedly being proven wrong)

This did give me a good chuckle

bensyverson 16 hours ago |

In case you find this site difficult to read:

    document.getElementsByTagName('main')[0].style.maxWidth = '39em';

mwkaufma 1 day ago |

The lady doth protest about the lady doth protesting too much, too much.

andai 1 day ago |

Most surprising thing to me here is tech giants growing 50%+ in 2 years. What's up with that?

cryzinger 1 day ago |

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 :(

arjie 1 day ago |

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.

vb-8448 1 day ago |

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.

mppm 23 hours ago |

I have stopped reading Ed Zitron quite a while ago because of his long-winded and polemic style. But counting his failed predictions is maybe not that useful, in the sense that his core thesis is really just the AI Bubble. While it hasn't burst, all of his predictions remain wrong; when (if) it does, he'll have been right. Trying to guess the exact time or failure mode (whether it's open models or corporate sticker shock or a bond crisis) is a fool's errand when there are so many powerful actors all-in on keeping up appearances. Exposing the financial and corporate shenanigans of the AI world is nonetheless useful. I just wish someone would do it in a more level-headed way.

PaulRobinson 17 hours ago |

Here's where we're at:

Tech companies invested in AI: AI is amazing (so good, it might kill us all, help?), and the ROI is going to be amazing.

NVIDIA specifically: We will allocate cash in strange deals that makes it looks like we're making investments but actually we're buying sales from those companies as they'll spend the money back with us, and everyone seems to think that's OK because the share price is going stinkers.

Cynics: AI is a scourge on society, and the fiscals are circular and a scourge on the economic stability of the planet.

The more nuanced argument I take is that Zitron is right about the circular finances and hyperinflation of valuations, and wrong about the utility of AI to help people. The Tech companies are just outright wrong about the finances, but right about everything else. And, NVIDIA's time will come, and it won't be pretty.

None of this requires me to believe that if Ed says something it must be true or false. It's just another data point, and he does uncover information I can't find myself that checks out. The fact he is wrong about the functional utility of AI or that he's getting super focused on hyperscalers when the real issues are in Oracle and NVIDIA, I can live with.

contubernio 1 day ago |

AI is clearly of great utility for defense/military/security. That alone guarantees continued support financially.

12sag15 1 day ago |

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".

simonw 1 day ago | |

"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?

HDThoreaun 1 day ago | |

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.

nozzlegear 1 day ago |

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.

tkel 23 hours ago | |

Yeah for real, an AI critic being popular is making everyone here lose their minds and try to come up with ten "Well Akshually..."

6510 4 hours ago |

My take would be that people have no idea what is going on today, as time expires history drifts further away from clueless to the absurd... and now you want to do the future? Whatever you say, we should at least completely ignore what your audience wants to hear. Whatever is left could be correct but only by accident. This is what the future will be like... or wait...

gregdoesit 1 day ago |

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

projproj 14 hours ago |

I had an interesting experience after I stopped reading HN comments for two weeks. I think it had to do with not reading the doom and gloom on here, which I tend to agree with. But after two weeks of reading neither the hype nor the doom about LLMs, I realized how amazing (though not perfect) this tool is. My point isn't whether LLMs are good or bad, but just how I didn't realize how much my consumption of other people's opinions infected my own outlook. It was like the opposite of rose-colored glasses.

BTW, the tool I used to block HN is called Foqos, which, of course, I heard about right here on HN. Based on my screen time reports, I got back about 2 hours per day average after blocking all my favorite sites.

eutropia 1 day ago |

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

Ekaros 1 day ago | |

Fundamentally someone at some point needs to pay for them. And this should mean by actual end customer payments. Now to get size of those payments and how much collectively needs to be spend start to look to me rather questionable. It is big number to spend.

noobermin 21 hours ago |

750 comments but I can't believe how bad this article is. The paragraph on MAU says similarweb is untrustworthy but then cites "most estimates"...which? Sorry, I can't read this without thinking you're biased against Ed Zitron.

The best part is the spreadsheet, which makes him sound like he's just sloppy, but danluu specifically says he's being deliberately misleading elsewhere, like the opposite of hanlon's razor now? So is he being deliberately sloppy in his spreadsheets or is he just incompetent? I suppose both is a better read but you need more proof for the "deliberately misleading" line and the spreadsheet frankly is danluu's best evidence beyond the list of failed predictions which is less striking in my mind.

While I think he's probably wrong on the timing, which clearly has been wrong since 2024, it doesn't really address the greater critique, which is that ai companies and nvidia and memory manufacturers need revenues collectively in the trillions to make their investors whole. That is still unsustainable such that it's been called out by other investors and financial journalists.

ersatz-matty 13 hours ago |

> I don't benefit in any particular way if AI does well, except insofar as anyone who holds broad index funds benefits, but I do care about accuracy.

Does Dan Luu still work at Nvidia?

> I had ChatGPT give me a list of predictions (with no attempted tilt towards correct or incorrect predictions) and then I skimmed/read the posts that ChatGPT linked to.

yeah alright

> If I really thought about it, I probably could've found something better to do with the time

Extremely likely.

> And yet, it would seem that my fact checking process is a lot more thorough than Zitron's.

Dan says in his post he fact checked with Chat-GPT and Claude, so: lmao.

dofm 1 day ago |

> Among programmers and other serious users of AI, I would guess that Willison has a larger audience than Zitron.

You don't say.

ashkankiani 20 hours ago |

This isn't a serious analysis of the actual thesis or any of the predictions in any meaningful way. I learned almost nothing from this shallow wall of text. It seems overly focused on "predictions" instead of the ideas behind the predictions, i.e.

- the existence and severity of the financial AI bubble

- the claimed efficacy of AI in terms of its utility vs the actual observed utility

- whether the net good provided by AI outweighs its very heavy costs

I find the section of listing a bunch of selected "predictions" and just saying "Wrong" to elucidate very little. Not that a sentence is sufficient to provide explanation, but Dan stops even doing that bare minimum partway through and just saying "Wrong" full-stop. The reasoning is left up to the reader I guess?

How is it wrong? What was the actual thesis behind it? Is the underlying idea wrong or just the specifics on execution? Was there undetermined factors that mled to the wrong prediction? What can we learn from those factors in order to update our model?

We saw that even though the underlying financials in 2008 were trash and lots of people knew they were trash, things didn't quite collapse in the time frame or way we expected, because an unknown part is how much shenanigans companies can do to extend the runway.

As an example, credit ratings agencies didn't drop ratings to match reality because of customer relation incentives, which is a factor that is not easy to account for and strongly affects the timing of the collapse.

I find the positive reactions to this blog to be confusing. I feel like I learned nothing at all, which makes sense considering under "why write this?" he says "I got four hours of sleep and my brain wasn't good for much of anything and I saw someone posted a screenshot of a reddit post dunking on Ed Zitron's prediction record."

lr1970 12 hours ago |

Ed Zitron is providing his assessment and prognosis strictly on financial basis. But AI has national security and geopolitical dimensions as well. US government is fully committed to keep the AI lead for as long as possible. And they use all sorts of tricks to affect the market in AI's favor. Financial analysis alone is not enough. The government will do anything to prevent AI bubble from bursting.

kshri24 1 day ago |

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.

WesolyKubeczek 15 hours ago | |

Don't you think those companies are mostly correcting for their massive covid overhiring + zero rate bonanza coming to its end?

Also, back when elon had bought twitter and had been firing people left and right, it was prophesied that with such inept management the company was going to collapse very soon. I thought it was obvious it would collapse. But that has not happened (yet, but it's been quite some years), and the service seems to be holding up after some initial shakiness.

kshri24 14 hours ago | | |

I would partly agree with you in so far as Twitter not collapsing and working well. I'll go so far as to say it was the right move by Elon to downsize the company as you really don't need so many people to run a social media site. However, I don't think Twitter can be compared to the scale at which Alphabet/Amazon operate. Alphabet/Amazon run hundreds of businesses (on the scale of X) within their parent umbrella organization. So even if one collapses it won't affect the other as much as it should. But since they are removing workforce by the thousands, I am wondering how much of it will have an impact on their bottomline in the coming years. I mean... they will be under pressure by their own stakeholders to put their money where their mouth is and remove workforce if AI has reached levels where workforce can be replaced. If they don't do it then they are tacitly admitting that we haven't reached that technical breakthrough needed. The only way forward for these companies is to make it happen one way or the other. They are heavily invested in it and cannot back out now.

raynr 1 day ago |

I am currently surrounded by hyperventilating corporate and country level leadership who are fully swept up and captured by the AI craze.

I have seen some wild failure modes from people who are outsourcing their thinking to LLM. Amendments to clauses that don't make English sense. Multi-paragraph long replies in emails that say nothing specific to the issue at hand. Responding to questions with "AI says this" (but I asked you, not the LLM). Leadership wants us to embrace AI but there is no product for the layperson, it feels like everything is front end + generic prompts + $LLM_API_key. People want to make customer service bots that have access to personal data.

I feel like software devs are so lucky in that at least people in your field can see an LLM for what it is and harness (no pun intended) it appropriately. As a lay user, no such luck. Leadership and purse strings are far removed from IC work and don't understand why an AI product wouldn't work, they've heard otherwise in their circles, you had better make it work so that they can claim to have delivered an AI transformation this year.

Enter Zitron.

Zitron is a woo-pushing grifter (his product: his stance on AI). Even without examining his reasoning or the accuracy of his predictions, Zitron is hard to listen to. Mostly, he shouts out a constant barrage of bare assertions that his research is thorough and irrefutable and the doom is coming and ever "AI booster" who disagrees with him is an idiot, all the while without actually spending time arguing his point.

But Zitron feels like one of the few people actually pushing back against this craze.

I would very much like a better argument for a position that I support, please and thank you.

taklimakan 1 day ago |

Ed Zitron sells subscriptions to his blog. Whether he’s right or wrong is irrelevant.

otterley 1 day ago | |

Why would any rational person want to pay to read falsehoods?

g-unit33 1 day ago |

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

api 1 day ago |

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.

arthurbrown 1 day ago |

The author asks "How can people take this seriously?"

I would reply the same regarding this article. Nearly all of these refutations are unconvincing.

The claim: "I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be."

The rebuttal: "Zitron's argument at the time was that hallucinations were as good as they were going to get, which meant that AI performance is capped at 2024 levels. Both the overall prediction and the mechanism were wrong. This one seemed wrong at the time, in that I noted here in 2024 that you can make AI code halfway decently by just putting it in a loop and having it run until the code compiles and tests pass"

Putting an LLM in a loop, burning tokens, and thrashing against a compiler and test suite is a ridiculous way to say that hallucinations have been "solved". Please. This is absurd.

dofm 1 day ago |

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.

dvt 1 day ago |

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.

marcus_holmes 1 day ago |

I read all Ed's posts, and enjoy them, and I like AI as a tool and use it every day.

I think it's really, really, really important to have a contrarian opinion out there, even it's a voice howling in the wilderness. Even if most of his predictions are wrong. Even if he swears a lot and gets a bit ranty at times.

Personally, I think he's going to be mostly right in the long term about the AI bubble, but mostly wrong in the long term about the effectiveness of AI (i.e. I think it will have a net-positive effect in the long term).

I always keep in mind the Gartner Hype Cycle [0] is true, and we're still on the initial slope up to the Peak Of Inflated Expectations.

[0] https://en.wikipedia.org/wiki/Gartner_hype_cycle

WarmWash 1 day ago |

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.

borzi 1 day ago |

I agree that Zitron is not honest and a denialist regarding the usefulness of AI, but the "profit" chart is just completely misleading as most of these companies have made large investments in OpenAI/Anthropic and list the gains in their share price as "profits" - so yes, while the asset prices are rising, that's typical in any financial bubble. Google is actually cash flow negative for the first time in history (which imo should be what measures profitability: income from products and services - costs to produce them) so Zitron's core thesis that there are no returns in AI is playing out as far as I can tell...

thelastgallon 1 day ago | |

circular financing, layers of financial engineering: https://news.ycombinator.com/item?id=48424983

Also, Google's recent profits are boosted from including SpaceX. $94.18 billion.

https://finance.yahoo.com/markets/stocks/articles/google-par...: On Aug. 6, Alphabet filed its 13F with regulators covering its second-quarter trading activity. Given that SpaceX went public on June 12, Google's parent company is now required to include its SpaceX holdings in its quarterly 13F.

bjornnn 1 day ago |

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.

browningstreet 1 day ago |

I’ve come this far without knowing who Ed Zitron is…

unreal37 17 hours ago |

I think cable news channels like CNN and CNBC like to have a "counterpoint" on to make their coverage seem balanced. There's always a guy saying the stock market is about to crash. There's always a guy saying oil will hit $200 per barrel. There's always a guy saying AI is a bubble.

Zitron is never right but he exists so that media can claim to be balanced.

lz400 1 day ago |

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.

asveikau 1 day ago |

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.

tim-star 21 hours ago |

what i would do for some formatting on this piece.

whogehrhr 16 hours ago |

Edward Benjamin Zitron (born 1986/1987) is an English author, podcaster, and public relations specialist.

So why do we carr exactly?

casey2 15 hours ago |

I don't see any evidence of Facebook's growth in high value regions specifically, all we see is them burning through money on failed project after failed project and getting into legal trouble.

g8oz 1 day ago |

Mo Bitar over on YouTube does the grumpy AI skeptic routine in a much more entertaining fashion.

simonw 1 day ago | |

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?

nateglims 1 day ago | | |

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.

sarjann 1 day ago |

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.

zmmmmm 1 day ago |

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.

minimaxir 1 day ago | |

This submission has citations on where he was wrong, they aren't predictions.

ourcat 1 day ago |

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.

amazingamazing 1 day ago |

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?

sfblah 1 day ago | |

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.

watwut 1 day ago | | |

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.

AdAstraSucked 20 hours ago |

99% of these comments are bots.

That’s what HN sells these days. Fake bot comments to prop up wannabe celebs and startups

“You pay, we spray”

jimmoores 1 day ago |

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.

locallost 20 hours ago |

Thank you. It's difficult to call Zitron right or wrong because he is merely grabbing the attention and clicks of AI sceptics and people afraid of any change. Patrick Boyle is another example with his constant stream of everything is broken videos, from AI to EVs.

I am not all in on AI, but the discussion requires nuance. Zitron does not have it because he is interested in attention and not discussion. The article deconstructs his antics really well. So again thank you. I really appreciated this part

> To make the case that these things are dying, he pulls on minor issues that are not positioned to cause the very large changes he suggests are about to occur. For Meta, he cited some kind of alleged MAU drop for Facebook. Rather than use Meta's own MAU figures or any kind of revenue or profit numbers, he seems to have used numbers from Similarweb. My experience with 3rd party tracking numbers like this is that they're quite inaccurate and generally useless for anything other than a rough order of magnitude comparison, making the Zitron's cited decline meaningless. FB stopped reporting MAU publicly in December 2023, but most estimates have FB MAU increasing over time and the numbers Meta does report show generally increasing usage over time for their products; Zitron cherry-picked an outlier low estimate to make his point.

Yes he is a classic cherry picker.

keybored 21 hours ago |

> No good reason, really. I got four hours of sleep and my brain wasn't good for much of anything and I saw someone posted a screenshot of a reddit post dunking on Ed Zitron's prediction record. When I wrote this review of futurist prediction accuracy, I tried to make sure that I didn't bias what I was reviewing in any way. It's not obvious from the post if the redditor who reviewed Zitron's predictions was pulling predictions in an unbiased fashion or if they were biased in some way (since AI has become a culture war issue, it wouldn't be surprising if someone pulled biased predictions), so I decided to read some Zitron in my spare time while poking at agents to get them to do an unrelated task I wanted them to do. For the futurist post, I read multiple entire books to pull predictions and generally only stopped when someone was being repetitive and kept saying the same thing over and over again. In this case, all Zitron does is be repetitive, so the methodology in the futurist review would mean that I review a few predictions and then stop immediately. To overcome this, I had ChatGPT give me a list of predictions (with no attempted tilt towards correct or incorrect predictions) and then I skimmed/read the posts that ChatGPT linked to. There were some cases where I thought ChatGPT's reading of the post was incorrect (these were generally cases where it flagged a prediction that would be incorrect if its reading was correct, but I disagreed with its reading) and (discussed further below) I also removed predictions which weren't falsifiable or seemed pointless because they were tautological (I noted something similar to this in the futurist post).

No reason really. Just very sleep deprived and want to multitask in between agentic feedback.

Some people obviously want AI to fail. Some people obviously want The Magic Machines to win.

croes 21 hours ago |

Did he add the trillions of off balance debt to his revenue/profit overview?

https://247wallst.com/investing/2026/08/17/alphabet-meta-and...

faragon 22 hours ago |

Accurate or not, there are many risks other than those that could bring AI companies value to 0. E.g., systems not requiring passing over all the data continuously, but in small regions running at L2-L3 cache memory speed. Once someone figures out that, the need for high bandwidth memory would end.

ChoosesBarbecue 1 day ago |

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.

nalekberov 23 hours ago |

I don’t know much about Zitron, but YouTube somehow pushes these “experts” onto my feed. This guy is full of crap, he doesn’t even care, because that doesn’t matter, what matters is view count.

psychanarch 1 day ago |

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.

copemaxxxing 1 day ago |

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".

dcminter 1 day ago | |

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!

AnodicElegy 1 day ago |

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.

vasco 1 day ago |

> I suspect he's relying on people's eyes glazing over when they see numbers and just not thinking about what the numbers mean.

This is one of the most important learnings one can make from working in professional environments.

brianpbeau 17 hours ago |

Now let's do the same analysis for the stuff that easily flows from the mouths of AI CEOs

insane_dreamer 1 day ago |

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.

josefritzishere 1 day ago |

Zitron is the opposite of Jim Cramer. No Hype, no sales push, very cynical and conservative.

platevoltage 1 day ago | |

Saying someone is the opposite of Jim Cramer is basically saying they’re right.

VCFundedGenYer 1 day ago |

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.

hypfer 1 day ago |

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.

jacquesm 1 day ago | |

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.

cobbzilla 1 day ago |

a thorough Fisking, nicely done danluu

the analogy to Ehrlich was strikingly apt

BatchJob 1 day ago |

The AI doom is actually a happy path scenario.

Collapse of entire economies will result on a scale that will eclipse the great depression. And it wont be because AI revolutionized anything. AI will become a dirty word to never be uttered by anyone in the human race after.

baggachipz 1 day ago |

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.

elendilm 21 hours ago |

The whole article reeks of paid propoganda hit peice.

The author attempts to virtual signal as impartial but fails horridly.

bdangubic 1 day ago |

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… :)

rustystump 1 day ago |

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.

Marciplan 1 day ago |

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

whateveracct 1 day ago |

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

Mawr 14 hours ago |

Decisively declaring long-term predictions wrong only two years later seems a little premature?

E.g. a company of the size of Meta/Google/Ms may very well be dying and still producing numbers that look like growth for the next few years.

---

Also, how in the world is a Jan 2025 prediction that "I believe we’re at peak AI" getting a simple "Wrong"? How are we deciding what "peak AI" is here?

---

Or, "July 2025: I am not trying to be dramatic, but it's pretty easy to come to the conclusion that Cursor is going to die" -> "Wrong (Cursor gets a $60B exit)"

So Cursor can't die once its been acquired? See https://news.ycombinator.com/item?id=49486172

---

"August 2025: These models have clearly hit a wall where training is hitting diminishing returns" -> "Wrong"

I guess this is just trolling at this point? This is like a research paper tier question, "wrong" doesn't cut it.

---

Very unimpressed with this analysis. Extremely poorly done, and pretty clearly not impartial at all. Shameful. Like, the guy does sound wrong to me, but the analysis is terrible nonetheless.

flyinglizard 1 day ago |

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.

mvc 20 hours ago |

C'mon anthropic. Give him a job! :-)

0xbadcafebee 1 day ago |

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.

dofm 11 hours ago |

Now do Sam Altman, Dario Amodei and Elon Musk.

eunice 22 hours ago |

zitron just saw the next frontier in culture war grifting and went all in on it

robomartin 1 day ago |

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.

formvoltron 18 hours ago | |

Have you chatted with Ai about the economics of space vs terrestrial?

Even if you believe they can get cost to launch 1KG down to 100 bucks... (current falcon heavy is $1550) you still have the problem with all those solar panels.

1GW of space AI requires... 1 GW of solar to power it.

Current manufacturers of space solar is 1-2 MW &.. space solar aint cheap. $100 per watt. They estimate each spacex will be 250 kW. So.. $25M just for the solar for each satellite. Yeah you can use less efficient / cheaper solar, but then your weight goes up.

Also... Ground AI datacenters haven't nailed down how quickly GPUs depreciate. Accountants claim 6 years while CRWV says it's longer and most realists say it's shorter. It's based on how quickly GPUs will improve. Which is QUICKLY.

In space you'll have to depreciate GPU, all supporting hardware including the satellite, electronics, solar panels, and launch costs. On the ground it's just the GPU & you can even sell the old one down.

ground based AI needs power. $FRVO is an interesting ticker if you believe in their technology. Just announced a deal with google yesterday.

robomartin 14 hours ago | | |

It isn't going to be easy, of course. Yet, I do believe they will make it work.

One correction: SpaceX makes their own solar arrays. The cost is nowhere near what you quoted. Source: I worked for SpaceX for a few years.

Also, you can generate a lot more power in space per unit area due to not having the limitations created by our atmosphere and weather. It's continuous generation at 30 to 40 percent higher per-unit-area radiation. Generation on earth is roughly an inverted parabola (on a good day without clouds and weather) that, at best, if you integrate the area under the power curve, delivers 66% of the total equivalent energy say, a nuclear reactor, could deliver during the same period. So, once you increase radiation from about 1,000 W/m2 (impossible to achieve on earth due to weather and other realities) to 1,400 W/m2, 24/7, no weather, etc. The scenario quickly becomes vastly different.

Geothermal is very interesting, thanks for the ticker, I'll look into it.

All that said, I think the US (and Europe, if they care to survive) needs to have, as a top national priority, a massive program for the construction of nuclear power plants.

A few years ago, I ran through an analysis of power generation needs to convert our entire fleet of vehicles to electric power. That required at least doubling our power generation capacity. This was the equivalent of having to build 1,200 nuclear power plants, each producing 1 GW 24/7.

This is impossible to achieve with solar, or wind, or the combination.

So, even if we decide not to care one bit about AI data centers, we need to double our power generation capacity (and infrastructure to deliver it).

Add AI data centers to that equation and the number could easily climb another 600 nuclear power plants.

Here's the problem that a naïve conversation with an LLM will not uncover: Humanity and Politics.

Could we embark on such a massive energy-generation project? Yes, absolutely.

Is it realistic? Nope. Not even close.

In other words, we can do it but it is impossible...which sounds like an oxymoron until you consider that we have lots of examples of projects that are absolutely plausible that, once they contact political and government reality, quickly become impossible. The best-worst example I always grab is the California high speed train disaster.

kypro 1 day ago |

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.

stego-tech 1 day ago |

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.

simianwords 1 day ago |

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...

frozenseven 1 day ago |

Great article. I was waiting for someone to eventually do an assessment on this grifter.

AdAstraSucked 21 hours ago |

AI slop is eating the world

fzeroracer 1 day ago |

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.

iLoveOncall 1 day ago |

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.

aesthesia 1 day ago | |

> 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?

marcosdumay 1 day ago | | |

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.

iLoveOncall 1 day ago | | |

I personally think improvement has been minimal since ChatGPT was released actually.

arthurlockman 1 day ago |

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.

VirusNewbie 1 day ago | |

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.

arthurlockman 1 day ago | | |

> 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?

badatnames 1 day ago |

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.

Planktonne 1 day ago |

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.

flockonus 1 day ago | |

No idea what you're trying to say... he's been directionally wrong for years as the article illustrates clearly.

Planktonne 21 hours ago | | |

Zitron's predictions have often been wrong; they've still been less wrong than those of the people who disagree with him.

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.

What we find is sobering. Submission volume has risen by 42% since November 2022. At the same time, submission writing quality also began to decline at the end of 2022, with Flesch Reading Ease (a standard measure of writing quality) 1.28 standard deviations (SD) lower in January 2026 relative to January 2021. Submissions that are heavily AI-generated account for nearly all of these trends. The quality of reviews has also dropped sharply since November 2022, driven by an increase in heavily AI-generated reviews. These reviews, in addition to being of worse quality, are also narrower in their emphasis, focusing more on theory and less on data. In short, more research is being submitted, with more AI writing that is lower in quality—not better.[1]

Peer review is unpaid work that we do (often on nights and weekends) because peer review on our own work is so valuable. Spending hours going through a submission and then realizing that there are hallucinated citations is infuriating as it is a waste of our time! If you haven’t spent enough time with your work to even get the references correct, then a.) why should we spend time reviewing it for you, and b.) what are you hoping to accomplish with the submission in the first place? Learning from reviews requires reflecting on your work, and you need to spend time with your work in order to do this.[2]