Widespread financial fraud which was legitimized and in some cases directly backed by EAs! Surely there are no parallels!

Zitron’s analogy is excellent because the bubble is multifactorial and the analogies that we can make are factor-to-factor. Here’s some things that caused the dot-com bubble; people were overly optimistic about:

Ed has also been clear there are a few factors that make this bubble worse (for the economy and the general public) than the dotcom bubble. For one, Ed is strongly convinced that GPU lifecycles are much shorter and worse than fiber optic life cycles. You build fiber optic infrastructure and it will last for decades. Meanwhile, GPUs used constantly at max load have life cycles of 3-5 years. The end result of the internet is also much more useful and less of a double-edged sword than the slop generators which churn out propaganda and spam.

I am a pretty big fan of Ed’s work, so I’m going to hold my nose and read Kelsey’s work thoroughly enough to do a line by line debunking:

Over the last two years, he has called the top repeatedly:

Well yes, but he has also explicitly said that the bubble peaking and popping would be a multiyear process. I’ve only kept up with his every article for the past year, but in the past year, his median guess for the bubble pop becoming undeniable was 2027. I guess making timelines with big events in 2027 and hedging on the median number is only for the rationalists? Also, we are already starting to see the narrative fray as Anthropic and OpenAI experiment with price hikes and struggle with getting ready for IPO, which would count as meeting his predictions for the start of the bubble pop.

In 2026, the focus is much more on alleging widespread, Enron- or FTX-tier outright fraud.

This is basically an admission that he can’t make the case in terms of the economics anymore.

??? Ed has been making the case for circular financing and investors being deceived because he thinks there are circular financing deals and investors being deceived. Ed has slightly softened on his position on exactly how useless or not LLMs are, but he is still holding to his economic case that the amount they cost isn’t worth the value they provide, extremely blatantly so once consumers start paying the real cost and not the VC-subsidized cost.

By almost every metric, AI progress from 2024 to 2026 has been much faster than AI progress from 2022 to 2024.

And she is quoting a rat-adjacent think-tank for proof that AI improvement has been exponential. Even among the rationalist, the case has been made that the benchmarks are not reflective of real world usage/value and that costs are growing with “capabilities”.

It can no longer argue that costs aren’t falling; they are.

Even accepting the premise that real costs have fallen, Kelsey fails to address Ed’s case that the costs LLM companies charge is massively subsidized. If real costs are 10x the current subsidized costs (which have already been pushed up as far they can be without losing customers), and model inference prices miraculously drop 5x (which Kelsey would treat as a given, but I think is pretty unlikely barring some radical paradigm shifts), that is still a 2x gap.

It is a straightforward crime to claim $2 billion in monthly revenue if you mean that you are giving away services that would have a $2 billion market value.

Yes, exactly. Technically OpenAI and Anthropic play games with ARR and “gross” revenue (i.e. magically excluding the cost of training the model in the first place), but in a just nation it would straightforwardly be a crime. Why does she find this hard to believe?

Epoch AI has an in-depth analysis of the same financial questions from the same public information

(Looks inside the Epoch AI article):

So what are the profits? One option is to look at gross profits. This only considers the direct cost of running a model

Ed has gone into detail repeatedly about why excluding the cost of training the model is bullshit.

(More details from the article)

But we can still do an illustrative calculation: let’s conservatively assume that OpenAI started R&D on GPT-5 after o3’s release last April. Then there’d still be four months between then and GPT-5’s release in August,22 during which OpenAI spent around $5 billion on R&D.23 But that’s still higher than the $2 billion of gross profits. In other words, OpenAI spent more on R&D in the four months preceding GPT-5, than it made in gross profits during GPT-5’s four-month tenure.24

Oh that is surprising, the Epoch AI article actually acknowledges the point that these models are wildly unprofitable once you account for the training cost! Of course, they throw away their point in the next section by just magically assuming LLMs will prove to massively valuable in the near future! (One of the exact things Ed has complained about!)

He’s found too many grounds for dismissing all the financial information we have as dishonest or irrelevant to seriously engage with what any of it would imply if it were true.

He has shown in detail how the companies use barely technically not lying obfuscated bullshit metrics like gross profit or ARR to inflate their numbers and if you try un-obfuscate them the numbers look a lot worse.

Kelsey goes on to try to claim how much value LLMs provide

Making them more productive is a big deal, and in 2026, AI makes them more productive.

Zitron can’t really contest this with contemporary data, so he cites 2024 and 2025 studies of much weaker AIs with much weaker productivity impacts.

Two years to… 4 months ago! Such outdated information! In the first place there has been very few rigorous studies of how much of a productivity boost LLM coding agents actually provide, and one of the few studies with even a passing attempt at rigor (while still below good academic standards), was METR’s study (and keep in mind they are a rat-adjacent think tank and not proper academics), which showed programmers thought they got a productivity boost but actually got a net productivity decrease!

From this set of beliefs, you could, in fact, defend a delightful bespoke AI bubble take: that AI would have been a catastrophic investment bubble, but the AI companies were saved from their mistakes by the determined NIMBYs of America killing off the excess data center build-out.

But that’s not Zitron’s stance. He seems to account “the build-out is too aggressive” and “the build-out is not happening as planned” as both independent strikes against AI — both things that show it’s bad, and the more of those he finds, the more bad it is.

It could in fact be all 3! The hyped-up build out, such as that indicated by OpenAI’s and Oracle’s 300 billion dollar detail was completely insanely too aggressive (for it to pay off, Ed calculated LLMs would have to drastically exceed Netflix+Microsoft Office in terms of ubiquity and price point), not achievable given realistic build times for data centers (Ed has also brought the numbers here), and even at the reduced actually rate of build out, still not actually financially viable (is simply because the LLM companies aren’t charging enough). So yes, both things are bad, and one type of badness partway mitigates the other, but it is still all bad!

I advise being very cautious about consuming Zitron’s posts

He has got a dramatic and vitriolic style, but as dgerard says, he has also dug through the numbers. I see lots of criticism of Ed’s style, but not nearly so substantial criticism about the hard numbers he has come up with. The LLM companies put out contradictory and obfuscated numbers, and taken naively they seem to contradict Ed’s numbers, but as Ed has shown, many, many times, when you start trying to un-obfuscate them they start looking really bad for everyone betting on LLMs.

Many coders are using chatbots, but I don’t know of evidence that it makes them more productive

So more and more coders are coming around to “actually AI code is okay”… but as we’ve seen repeatedly with LLM generated content, it is very easy for people to “Clever Hans” themselves and convince themselves LLMs are contributing more than they actually are, so I am not going to trust anecdotal reports.

Even used as a way to honestly disclose how sure you are about a hot-take… it is still a term used to frame hot-takes. And the term “Epistemic Status” feels like cult jargon compared to “here’s how sure I am about this stuff”

(Written quickly for Inkhaven, I hope someone someday makes a better case for this than I will here)

Inkhaven: write at least one bad hot-take a day!

I wouldn’t give him credit for a full admission. He isn’t acknowledging that “biased left-wing experts” means expert like psychologists with a basic understanding of psychometric validity and geneticists with the basic understanding that popular notions of race don’t have a genetic basis and biological determinism is false.

I am somewhat surprised by the number of upvoted comments pushing back. But most of that push-back is in the typical rationalist style loaded with jargon, full of charitability to what habryka must have really meant or how they may not be understanding him right, and altogether not nearly close enough to a cleanly stated: “no, wtf is wrong with you”. So I’m still disgusted and annoyed. And it is still a highly upvoted article, so nah, I’m not giving any of the lesswrongers any credit on this one, even the ones trying to push back.

It has already worked out that way: https://www.reddit.com/r/singularity/comments/1snbv4m/white_house_moves_to_give_us_agencies_anthropic/

So you aren’t even being paranoid, this seems like a straightforward calculation for Anthropic to have made.

The security blog I linked the other day has more criticisms of Anthropics mythos cybersecurity claims:

-Apparently Opus 4.6 may have found the FreeBSD Anthropic has made a huge deal about Mythos finding? And Anthropic didn’t clarify that there older model had found the bug as well: https://www.flyingpenguin.com/freebsd-cve-2026-4747-log-suggests-mythos-is-a-marketing-trick/

-More explanation about why Anthropic’s entire approach with Mythos and cybersecurity is more oriented around marketing than good (or any) cybersecurity practices. Also, the author makes the point that if you did have a tool that could rapidly refactor code into other languages, the solution to the vast majority of bugs and vulnerabilities Mythos found isn’t bug hunting one by one with Anthropic’s (much more expensive) LLM, it is to refactor code into a memory safe language and to make some boilerplate counter-approaches cheaper to implement. (I think the author is too credulous of LLM coding agents code quality here, but given those assumptions I think there point is correct.) https://www.flyingpenguin.com/how-sans-mythos-marketing-disappoints-defenders/

-Bonus, MCP (model context protocol, a standard for tools for LLM agents Anthropic has developed and tried to push) is insecure by default and Anthropic has refused to fix it! Which is really hypocritical given that many of the “vulnerabilities” Mythos found are small things that aren’t actually properly exploitable under most conditions. https://www.flyingpenguin.com/ox-security-report-anthropic-mcp-is-execute-first-validate-never/

Habryka defends colonialism, straight out, no qualifiers: https://www.lesswrong.com/posts/w3MJcDueo77D3Ldta/let-goodness-conquer-all-that-it-can-defend

Ok, fine, I’ll go even further. I am glad about the colonization of North America. The American experiment was one of the greatest successes in history, and of course, it was a giant fucking mess. But despite it all, despite the Trail of Tears, despite smallpox ravaging the land, despite the conquistadors and the looting and the rapes — it was still worth it. America is worth it. Democracy was worth it.

A surprisingly high number of comments push back, but Habryka’s post is still highly upvoted, and the push back is in the typical rationalist jargon filled, assume-charitably mess.

Hey Eliezer is very mad about being quoted as saying to bomb them! (He’s made very clear that he wants them destroyed with air strikes!)

A detailed analysis of why Anthropic’s claims about Mythos’s cybersecurity implications are bs: https://www.flyingpenguin.com/the-boy-that-cried-mythos-verification-is-collapsing-trust-in-anthropic/

And a followup post about why Anthropic’s Glasswing project violates cybersecurity community norms and is an attempt to form a cartel: https://www.flyingpenguin.com/cartel-or-not-anthropic-mythos-is-a-curious-case/

Eliezer complaining about vigilante actions is really ironic considering one of his main themes in Harry Potter and the Methods of Rationalist was about “heroic responsibility” and complaining about how ordinary people default to doing nothing. I guess what he actually meant was for right-thinking people (people that agree with him) to take the actions he approves of.

they fail to grasp the real social reaction

side-note… I wonder what the overlap is between rationalist that showed up to their stupid “march for billionaires” and AI doomers?

LLMs generate the next most probable token given the previous context of tokens they have (not an average of the entire internet). And post-training shifts the odds a bit further in a relatively useful direction. So given the right context the LLM will mostly consistently regurgitate content stolen from PhDs and academic papers, maybe even managing to shuffle it around in a novel way that is marginally useful.

Of course, that is only the general trend given the right^tm prompt. Even with a prompt that looks mostly right, one seemingly innocuous word in the wrong place might nudge the odds and you get the answer of a moron /r/hypotheticalphysics in response to a physics question. Or a asking for a recipe gets you elmer’s glue on your mozarella pizza from a reddit joke answer.

if they took the time and energy to curate it out the way they would need to to correct that they wouldn’t be left with a large enough sample to actually scale off of

They do steps like train the model generally on the desired languages with all the random internet bullshit, and then fine-tuning it on the actually curated stuff. So that shifts the odds, but again, not enough to actually guarantee anything.

So tldr; you’re right, but since it is possible to get somewhat better than average internet junk with curating and post-training and prompting, llm boosters and labs have convinced themselves they are just a few more iterations of data curation and training approaches and prompting techniques away from entirely eliminating the problem, when the best they can do is make it less likely.

Eliezer joins the trend of condemning “political” violence with confidence on the far end of the dunning-kruger curve: https://www.lesswrong.com/posts/5CfBDiQNg9upfipWk/only-law-can-prevent-extinction

I’ve already mocked this attitude down thread and in the previous weekly thread, so I’ll try to keep my mockery to a few highlights…

He’s admitting nuke the data centers is in fact violence!

It would be beneath my dignity as a childhood reader of Heinlein and Orwell to pretend that this is not an invocation of force.

But then drawing a special case around it.

But it’s the sort of force that’s meant to be predictable, predicted, avoidable, and avoided. And that is a true large difference between lawful and unlawful force.

I don’t think Eliezer has checked the news if he think the US government carries out violence in predictable or fair or avoidable ways! Venezuela! (It wasn’t fair before Trump, or avoidable if you didn’t want to bend over for the interest of US capital, but it is blatantly obvious under Trump) The entire lead up to Iran consisted of ripping up Obama’s attempts at treaties and trying to obtain regime change through surprise assassination! Also, if the stop AI doomers used some clever cryptography scheme to make their policy of property destruction (and assassination) sufficiently predictable and avoidable would that count as “Lawful” in Eliezers book? If he kept up with the DnD/Pathfinder source material, he would know Achaekek’s assassins are actually Lawful Evil

The ASI problem is not like this. If you shut down 5% of AI research today, humanity does not experience 5% fewer casualties. We end up 100% dead after slightly more time.

His practical argument against non-state-sanctioned violence is that we need a total ban (and thus the authority of state driving it), because otherwise someone with 8 GPUs in a basement could invent strong AGI and doom us all. This is a dumb argument, because even most AI doomers acknowledge you need a lot of computational power to make the AGI God. And they think slowing down AGI (whether through violence or other means) might buy time for another sort of solution that is more permanent (like the idea of “solve alignment” Eliezer originally promised them). Lots of lesswrong posts regularly speculate on how to slow down the AI race and how to make use of the time they have, this isn’t even outside the normal window of lesswrong discourse!

Statistics show that civil movements with nonviolent doctrines are more successful at attaining their stated goals

Sources cited: 0

One of the comments also pisses me off:

Which reminds me about another point: I suspect that “bomb data centers” meme causal story was not somebody lying, but somebody recalling by memory without a thought that such serious allegation maybe is worthy to actually look up it and not rely on unreliable memory.

“Drone strike the data centers even if starts nuclear war” is the exact argument Eliezer made and that we mocked. It is the rationalists that have tried to soften it by eliding over the exact details.

how do we ensure that no-one builds it?

Eliezer made a lesswrong post yesterday where he explains that since anyone could build it, lone acts of violence are obviously ineffective and the only solution is the right and proper (“Lawful” as he calls it, because he has been stuck on DnD since writing Planecrash) state violence which can enforce a worldwide ban (which you may recall Eliezer has put at the absurdly low 8 2024 GPUs).

or is there more going on?

One idea I’ve read about (heavily developed by Ed Zitron, but also a few other news sources and commentators have put it forward) is that SaaS (Software as a Service) businesses were heavily over invested in expectation of basically infinite growth over the past decade. SaaS growth was “exponential” in its early days, but then various needs of the market were basically saturated, so SaaS companies squeezed more growth out cutting cuts or upping how much they charged, and now it is finally catching up to them.

The AI hype means almost everyone tries to interpret everything the lines of AI causing it. The recent price correction in many SaaS companies was (mis)interpreted as the threat of vibe-coded replacements forcing them to cut costs. The SaaS companies trying to cut costs and going through layoffs is being misinterpreted as AI successfully replacing junior devs.

The Zvi post really pisses me off for continuing to normalize Eliezer’s comments (in a way that misrepresents the problems with them).

This happened quite a bit around Eliezer’s op-ed in Time in particular, usually in highly bad faith, and this continues even now, equating calls for government to enforce rules to threats of violence, and there are a number of other past cases with similar sets of facts.

Eliezer called for the government to drone strike data centers, even of foreign governments not signatories to international agreements, and even if doing so risked starting nuclear war.

Pacifism is at least a consistent position, but instead rationalists like Zvi want to simultaneously disown the radical actions, but legitimizes the US’s shit show of a foreign policy.

Another thing that pisses me off is the ahistorical claim by rationalist that such actions are ineffective and unlikely to succeed. Asymmetric warfare and terrorist tactics have obtained success many times in history! The kkk successfully used terrorism to repress a population for a century. The black panthers got gun control passed in California and put pressure on political leaders to accept the more peaceful branch of the civil rights movement. The IRA got the Good Friday agreement. The US revolution! All the empires that have withdrawn from Afghanistan!

Overall though… I guess this is a case of two wrongs making a sorta right. They are dangerously wrong about AI doom, but at least they are also wrong about direct action and so usually won’t take the actions implied by their beliefs. (But they are still, completely predictably, inspiring stochastic terrorists).