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AI Is Slowing Down

▲ 332 points 364 comments by crescit_eundo 7h ago HN discussion ↗

Pangram verdict · v3.3

We believe that this document is fully human-written

0 %

AI likelihood · overall

Human
100% human-written 0% AI-generated
SEGMENTS · HUMAN 6 of 6
SEGMENTS · AI 0 of 6
WORD COUNT 2,021
PEAK AI % 0% · §1
Analyzed
Jun 8
backend: pangram/v3.3
Segments scanned
6 windows
avg 337 words each
Distribution
100 / 0%
human / AI fraction
Verdict
Human
Pangram v3.3

Article text · 2,021 words · 6 segments analyzed

Human AI-generated
§1 Human · 0%

If you liked this piece, you should subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5,000 to 18,000 words, including vast, detailed analyses of NVIDIA, Anthropic and OpenAI’s finances, and the AI bubble writ large (updated to version 3.0 last week). My Hater's Guides To the SaaSpocalypse, Private Credit and Private Equity are essential to understanding our current financial system, and my guide to how OpenAI Kills Oracle pairs nicely with my Hater's Guide To Oracle.Over a three week period in May, I published an exhaustive three-part guide to how the AI bubble might collapse, the events that might trigger it, and the consequences. For something lighter, check out last week’s premium, where I re-introduce you to the antagonists of the AI bubble (and their fatal weaknesses) in caustic, slightly sweary terms. Subscribing to premium is both great value and makes it possible to write these large, deeply-researched free pieces every week. Last week I went on Bloomberg and discussed the state of the AI bubble with a clarity that rattled even the sweatiest boosters, mostly because I spoke with clarity about an investment frenzy whipped up through hype, deceit and mythology. Some were equal parts frustrated and angry that I don’t have money in the market, or, as they’d put it, “skin in the game.”I get it! When your entire worldview is dictated by what a series of venture capitalists and psuedo-journalists on Twitter want you to believe, it must be difficult to imagine someone having “morals” or “beliefs” or that one might hold a position that wasn’t entirely based on greed or tribalism. It must be confusing — upsetting, even! — to hear that somebody is willing to accurately and vociferously tear into a tech industry largely controlled by people with no regard for their users or workers, who are willing to bathe their products in mediocrity all because it’s the thing that everybody else is doing.This is a hysterical era perpetuated by liars, cowards, imbeciles, craven boosters and the easily-fooled.

§2 Human · 0%

Those excited about generative AI are either the victim or the perpetrator of a con centered around a technology to ingratiate at the highest cost possible.AI Cannot Afford To Slow Down — It Needs $3 Trillion Or More In Revenue By End Of 2030 To Sustain Its Existence I also think that everybody is a little flippant about what has to happen for me to be wrong.If we take Sightline Climate’s data from February at face value, there are 190GW of data centers planned. If we take NVIDIA CEO Jensen Huang’s statement that data centers will cost $80 billion to $100 billion a gigawatt at face value, this means that said data centers will cost anywhere from $9.5 trillion to $15 trillion. Bloomberg incorrectly states that this is a “$3 trillion” buildout.This money will have to come from somewhere. The Financial Times reported in May that banks are concerned they might “choke” on data center debt when I estimate there’s barely $250 billion a year being issued. They will, to actually make these data centers happen, have to start issuing anywhere from $500 billion to a trillion a year.Jensen Huang has also said that NVIDIA projects a trillion dollars worth of revenue through the end of 2027. 54% of NVIDIA’s revenue comes from three clients, which means that NVIDIA’s future largely depends on three unnamed companies — likely Taiwanese ODMs building servers for Microsoft, Google and Meta — and their counterparties’ ability to raise debt on a near-perpetual basis, as the number of firms that can afford to buy thousands of $7.8 million racks of Vera Rubin GPUs is dwindling.Even then, every part of this puzzle requires more and more debt or at the market dumps like Google’s $85 billion equity sale or Meta’s planned multi-billion dollar dump. The fact that hyperscalers are doing equity sales is, as economist Paul Kedrosky raised in our conversation on my show last week, a sign that debt is becoming harder to acquire.

§3 Human · 0%

Anthropic has made $330 billion in compute and chip commitments between Google, Amazon, and Microsoft, another $30 billion with CoreWeave and another $15 billion with SpaceX. To pay for this compute, Anthropic must meet its projected revenue of $174 billion a year by 2029.Anthropic has raised $95 billion across rounds in February, April (from Google and Amazon), and May. These funds will be insufficient to cover Anthropic’s costs, as will Anthropic’s cash flow, meaning that it will have to raise at least another $200 billion in the next year.OpenAI has projected to burn at least $852 billion through the end of 2030, and has made over $770 billion in compute commitments across Microsoft, Amazon, CoreWeave, Cerebras, and Oracle. The $122 billion funding round from March will be insufficient to cover these costs, and it will require, at the very least, another $250 billion in funding by the end of the year.Whatever obtuse fantasies you have about the current state of generative AI are irrelevant to a much larger problem: that the infrastructure being built and compute commitments being made are being done so at a level that demands that generative AI and AI compute generate over $2 trillion in annual revenue by 2030. When I say that, I mean it absolutely has to do that otherwise none of the data center capex makes sense, and neither Anthropic nor OpenAI can pay their commitments.OpenAI expects to spend $50 billion on compute in 2026, and I wouldn’t be surprised if Anthropic spends anywhere from $30 billion to $50 billion. Between them, Anthropic and OpenAI represent the vast majority of all AI compute demand — at a minimum 70%, if not 80% to 90%. Put another way, there’s barely a few billion dollars of demand outside of two companies that lose billions — or tens of billions — of dollars a year.

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Let’s break down these numbers a little further:190GW of data center capacity assuming a PUE of 1.35 suggests a critical IT load of around 140GW, which, charged at around $12.5 million per megawatt, works out to around $1.75 trillion in annual revenue.If we assume that half of that gets built, that’s still $875 billion in annual revenue that will be needed to keep these data centers from running out of money as their margins are atrocious and they’re all paid for with onerous debt.OpenAI and Anthropic project to make $184 billion and $174 billion in revenue in 2029, for a total of $358 billion in annual revenue. While Anthropic claims it will be profitable by then, I do not believe it will be, nor is it profitable at this point outside of financial engineering. At present, there are no other major purchasers of AI compute outside of NVIDIA, hyperscalers (who are selling it to Anthropic and OpenAI, or they’re Meta, which has no AI strategy), OpenAI, and Anthropic. None. I can’t find a single one outside of Jane Street spending more than a few hundred million. We need a few hundred billion.That’s already a huge problem, but the other problem is that we also need companies to spend dramatically more on AI services than they already do. While journalists are currently gooning over OpenAI and Anthropic making $6 billion or $10 billion in a given quarter, that’s just not enough! Both Anthropic and OpenAI need to be making $10 billion or more in monthly revenue by Q1 2028, or their growth rates aren’t going to support their compute commitments.This is not hyperbole! Every single thing I have stated here precisely maps to the projections and promises of the AI industry. No matter how horny or flaccid you are for the potential of AI, it must grow at an astonishing, unstoppable rate from here until the end of time to be anything close to worthy of its costs.Actually, sorry, let’s put judgments aside for a second, because this isn’t about judgment, but rather the promises that have been made by the software and hardware companies associated with AI.

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NVIDIA’s place atop the stock market and its ridiculous projections depend on both the continued flow of data center debt and the continued belief that AI services will have the revenue to back it up. AI cannot, under any circumstances, slow down. In a year, Anthropic and OpenAI’s businesses have to be roughly twice the size they are today, and then double again basically every year until 2029 or 2030. In that time period, they must also both raise hundreds of billions of dollars or, alternatively, turn deeply unprofitable businesses into profitable ones while also doubling their revenues. Alternatively, both must severely reduce their costs…except if they do that, they won’t have any need for all that compute capacity, which will deprive Oracle, Google, Microsoft, SpaceX, Cerebras, CoreWeave, TeraWulf, Cipher, and Hut8 of the $1.1 trillion in remaining performance obligations.Also, if OpenAI can’t afford — or doesn’t want — its compute, Oracle will simply run out of money. It is spending anywhere from $340 billion to $700 billion (depending on whether you believe Jensen Huang in September 2025 or May 2026) on the 7.1GW of data centers it’s building for OpenAI. These, again, are not hyperbolic statements, but the actual costs associated with Oracle’s massive buildouts in Michigan, New Mexico, Wisconsin and Texas. I didn’t agree to do this! Larry Ellison did! Sidenote: Larry Ellison has also got at least $21 billion in loans collateralized by his Oracle shares, and any doubts around Oracle’s ability to pay for its debts or OpenAI’s ability to pay Oracle for its compute will threaten massive margin calls. I wrote about this here. It’s really bad!Whatever Everybody Is Spending On AI Right Now Is Insufficient, and We Need At Least Two Other OpenAIs To Justify The Compute Being BuiltApparently, Salesforce is planning to spend $300 million on Anthropic in 2026, to which I say “that’s not nearly enough”! Everybody has to be spending even more than that in the next few years, without fail, no ifs, ands, or buts.

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It is non-negotiable. Anthropic needs to be making over $100 billion in two years or it can’t afford its commitments, so you filthy token-hogs better slurp up your slop this instant, or Dario Amodei gets made part of the permanent underclass!But seriously folks, the combined compute demand of every single AI company in the world doesn’t currently reach $100 billion — and it needs to be ten times that by 2030 or all those data centers got built for no reason! And for that to happen, both Anthropic and OpenAI need to be making about $400 billion a year in annual revenue, which means there needs to actually be that much demand for AI services! Right now, Anthropic and OpenAI’s combined projected revenues for 2026 sit somewhere in the region of $60 billion — so, you know, they only need to grow by 496% by the end of 2029! To make matters worse, it doesn’t seem like anyone else in the AI industry is going to help with the whole “demand for AI services or compute” thing. As The Information reported a few weeks ago, OpenAI and Anthropic make up 89% of all AI startup revenues. We could include hyperscaler revenues, but that wouldn’t help very much. Microsoft’s $37 billion in AI annual run rate — these fucking cowards never share actual AI revenues! — is predominantly made up of OpenAI’s compute, with the rest of it (maybe $8 billion in annual revenue at best) from Microsoft harassing its permanently-abused customer base into installing Copilot. Ah, shit, there’s another problem with Microsoft — Microsoft AI CEO Mustafa Suleyman just said that Anthropic’s models were too expensive, and he intended to reduce Microsoft’s use of them to zero! You can’t do that Mustafa! We need every cent of demand, otherwise everything falls apart! Sidenote: Amazon and Meta barely have AI stories. Mark Zuckerberg just said he “thinks” Meta has a use for the vast amount of compute it’s bought or is developing, if you’re wondering how great things are going over there.