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Reposted by Ed Zitron

Ed Zitron @edzitron.com · 29/09/2026

Free newsletter: When will the AI bubble burst? When the money runs out. Raising debt for AI data centers is becoming untenable, infrastructure break-even points keep getting further away, and many of VC's AI investments look like dead money. www.wheresyoured.at/dead-money/

wheresyoured.at

https://www.wheresyoured.at/dead-money/

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Ed Zitron @edzitron.com · 2h

Here’s this week’s Better Offline. I walk through Anthropic’s 2025 financials, covering how it spent $2.75 to make a dollar, and how it was, at least last year, a worse business than OpenAI. youtu.be/u4pr23MWMM8?... Linktr.ee/betteroffline

youtu.be

Monologue: Anthropic Lost $8bn In 2025, Was A Worse Business Than OpenAI | Better Offline

YouTube video by Better Offline

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Ed Zitron @edzitron.com · 14h

This is now a sycophancy test. Joking about it I’ll accept, barely, but anyone who even remotely indulges this is a coward

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Ed Zitron @edzitron.com · 19h

I’m gonna come back to it later when I’m I’m not posting mid workout lol

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Ed Zitron @edzitron.com · 19h

Also the price is absolutely not the same via bedrock or vertex if Amazon or Google chooses to discount??

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Ed Zitron @edzitron.com · 19h

I’m gonna repost later, I gotta be more specific about the issues here and I did not cover it right

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Ed Zitron @edzitron.com · 19h

You don’t see the issue with nearly 50% of revenue coming from channel sales from two companies that are selling competing products, one of whom invested $50bn in the biggest competitor?

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Ed Zitron @edzitron.com · 19h

That’s what’s happening except it’s sold explicitly by Amazon and Google at prices set by them through bedrock and vertex

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Ed Zitron @edzitron.com · 20h

It makes Anthropic’s direct sales seem materially larger than they are.

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Ed Zitron @edzitron.com · 22h

except it isn't annual revenue! it's annualized

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Ed Zitron @edzitron.com · 23h

genuinely useless to give this number without defining A) what run rate means and B) what period it refers to

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Ed Zitron @edzitron.com · 29/09/2026

Per Reuters, Anthropic has $252 billion in non-cancelable compute obligations across Microsoft, Google and Amazon, and $161.2 billion in Broadcom TPU lease obligations that are "largely non-cancelable". Truly insane. $413 billion in non-cancelable contracts. www.reuters.com/business/ant...

The company said it plans to spend at least $111.1 billion with Alphabet's (GOOGL.O), opens new tab Google, $110 billion with Amazon (AMZN.O), opens new tab and $31.4 billion with Microsoft (MSFT.O), opens new tab under long-term infrastructure service obligations over the next seven to 10 years "regardless of ⁠usage."
Anthropic is separately carrying about $161.2 billion of Broadcom (AVGO.O), opens new tab-related equipment lease obligations that are largely non-cancelable, according to the prospectus. Anthropic filed for an IPO confidentially with the Securities and Exchange Commission in June but its paperwork has not been publicly disclosed.

Anthropic did not immediately respond to a request for comment about the filing.
The company said it committed to pay Google between April 2026 and July 2033 and Amazon between May 2026 and April 2036.
"If our actual spend falls short, we must pay Google the difference," the company said, adding that similar terms apply to its Amazon agreement.
It added its commitment with Microsoft of $31.4 billion between November 2026 and May 2033 "is non-cancelable except in the event of Microsoft's uncured material breach."

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Ed Zitron @edzitron.com · 29/09/2026

On Friday, I'll publish a premium that explores the wider economic impact of generative AI to date and what happens when the bubble pops. To read it, sign up for a paid subscription. Prices start at $7-a-month. edzitronswheresyouredatghostio.outpost.pub/public/promo...

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Ed Zitron @edzitron.com · 29/09/2026

Anthropic's numbers are as bad as my worst expectations, and it's impossible to see how it manages to make good on its spending commitments. OpenAI and Anthropic are toxic companies with rotten economics, and should not be allowed to go public. www.wheresyoured.at/dead-money/

In any case, these numbers are as bad as I’ve always thought they’d be, if not a little worse. I don’t see how this company becomes one that can afford its $518 billion in compute commitments, nor do I see how it magically works its way out of the economic equivalent of septic tank.

This company will, if allowed to go public, likely lean on the very same junk-grade/high-yield debt that AI data centers and neoclouds like CoreWeave currently need, and it will do so at volumes of somewhere between $50 billion and $100 billion a year for a company with few assets, endless losses and a CEO with the grace of a drunk elephant.

Anthropic is not the future of technology, nor is it the next Google, nor is it the next Microsoft, nor is it, to quote Reuters, capable of “[transforming] the global economy more profoundly than industrialization, electricity and the internet.”

It is impossible to rationally argue that the economics of OpenAI and Anthropic make any real sense. To claim that this is “just like Uber” or “just like Amazon Web Services” or “just like the Dot Com Bubble” is to bury one’s head in the sand or, on some level, want to know less about the world. This is serious, dangerous, and should not be seen as “business as usual.”

We must treat OpenAI and Anthropic as what they are: economic disasters waiting to happen.

To do anything less is to directly invite danger to the door of every investor that’s allowed to believe that they’re funding the next industrial revolution.

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Ed Zitron @edzitron.com · 29/09/2026

Anthropic's leaked IPO prospectus showed that it spent $2.75 to make a dollar in 2025, making it a worse business than OpenAI. It lost $8bn on $4.6bn in revenue. Boosters will say 2025 doesn't count - or, put another way, to ignore your lying eyes. www.wheresyoured.at/dead-money/

This, shockingly, means that Anthropic was a worse business than OpenAI in 2025, when it spent $34 billion to make $13.07 billion (per my own exclusive reporting of its audited financials), or $2.60 to make $1.

While things could change in 2026, it’s important to note how many people said that Anthropic was “a better business” that would “be profitable faster than OpenAI,” which is, until we are able to see both of their audited 2026 financials, somewhere between a myth and an outright lie.

So many people told me that Anthropic was more-profitable! So many people assured me that this company had worked it all out, when in fact Dario Amodei’s horrid son was just as obese as Altman’s, a rotten, unprofitable carcass.

Boosters are already boiling their copium kegs, angrily oinking that 2026 “will be better” and that “Anthropic has been more profitable.” At this point I have less than zero interest in anything that hasn’t gone through an auditor, because it’s very clear that, through either misinforming investors or the media, Anthropic has intentionally obfuscated the full horrors of its economics.

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Ed Zitron @edzitron.com · 29/09/2026

The AI bubble bursts when the money runs out. That could be when AI startups and model labs can't raise like they used to, or AI data center developers balk at 11% interest on their debt. Or, perhaps, the growth just slows and the party ends. www.wheresyoured.at/dead-money/

Every single day — even on the weekends — someone asks me either how or when all of this breaks, and my answer is simple: when the money runs out.

Eventually, AI data center debt is going to become untenable for those raising it, because 11%+ rates on already-meager margins makes the maths a little impossible. Once this happens, there will be a fundamental reevaluation of the value of all AI data center debt, which may lead to a sell-off of the underlying bonds and associated debt, which will make any investor deeply entrenched in the GPU credit business extremely nervous and, in some cases, unable to exit their positions in anything short of an embarrassing fashion.

This isn’t likely to happen due to moral or ethical reasons, but as a result of creditors realizing that they’ve got way too much risk tied up in projects that regularly make the news for not getting built. At some point these projects become too risky for even the most mold-poisoned private credit fund or brainless Japanese bank to stomach, and the timeline will accelerate based on either Treasury rates or further data center developments facing cashflow or construction problems.

On the venture capital side, it’s unclear how much dry powder actually remains, how much of it could be deployed into AI startups, and whether it’ll be a case of ‘running out of money’ so much as a moment where everybody gets spooked about AI and stops investing entirely. This would be accelerated by any cashflow issues across any major AI startups, any downrounds (IE: raising at a lower valuation), or failed acquisitions, such as when Anthropic walked away from buying Decart for $6 billion earlier in September.

And really, the biggest sign is the most obvious one — the deceleration of Anthropic and OpenAI. If they aren’t going to pay those $1.3 trillion in compute bills, the jig is up for AI data center demand.

The signs are already there that something is up.

Per Irrational Analysis, Anthropic’s record-breaking “$65 billion in annualized revenue run rate” from July 2026 may have been calculated in the single-most-deceptive way I’ve ever heard a startup do so:

Last month, there was a whole kerfuffel in AI/semis/finance circles on Anthropic July ARR. Two numbers were going around. I don’t remember the numbers and frankly it does not matter. You will see.

One ARR number was the traditional “trailing 28 days * 13” number. Personally I hate this venture-capital clown metric but whatever a lot of people use this.

The traditional ARR number was bad and implied deceleration in growth. So the people massively long Anthropic came up with a new ARR number that was July 31st * 365 days.
That’s right folks. If Irrational Analysis is right, Anthropic’s revenue on July 31, 2026 was $178 million, and because the other calculation — 28 days times 13 — created a lower number, the company chose to go with something that should, at a minimum, have investors hiring lawyers and demanding real, tangible answers about how run rate is calculated. Every single reporter with any Anthropic source that can speak to run rates should be screaming at them for clarity, because this is some sub-Enron bullshit.

Even if you don’t trust that analysis, another from TickerTrends surfaced by Callum Williams of The Economist shows Anthropic’s annualized run rate plateauing since, it seems, the beginning of June, and as Williams said, if this is even broadly correct, it’s really, really bad.

Williams also another TickerTrends chart showing OpenAI’s revenue growth had continued to climb…but was showing the initial signs of a slowdown.

Neither of these companies can afford to slow down, in part because of their massive compute obligations, and in part because their massive valuations are based on them being able to pull in, at least in Anthropic’s case, between $190 billion and $200 billion in annual revenue within the next two years.

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Ed Zitron @edzitron.com · 29/09/2026

And for what? I estimate that since 2023, around $800bn in venture investments have gone to AI companies, with around $226bn going to Anthropic and OpenAI. Most AI companies have overinflated valuations that make an IPO or M&A impossible. www.wheresyoured.at/dead-money/

I estimate that since 2023, there’s been around $800 billion in global venture capital investment in AI companies, with at least $266 billion of that going to Anthropic and OpenAI.

Of those investments, I expect at least $300 billion of that equity to be dead money, because, for the most part, AI companies are wrappers or layers built on top of Anthropic and OpenAI’s models, holding very little IP of their own and being burdened with ever-growing opex that mostly flows to the two AI labs that constantly want to compete with their customers. These businesses are fundamentally built on reselling tokens from the large AI labs at a loss, which is why companies like Harvey and Perplexity have to raise hundreds of millions of dollars every few months.

These startups’ continued existence is entirely a function of venture capital, as all of them are deeply unprofitable. This means that before the bubble bursts, these companies will continue to sap the venture capital world of billions more dollars, all with little chance of an acquisition and a near-zero chance of an IPO considering their ugly economics. These economics are also load-bearing for OpenAI and Anthropic, representing around 80% of their revenues, meaning that once they die, the AI labs’ underlying revenues begin to decay.

This also means that these AI startups are, in general, not actually renting AI GPUs, choosing instead to rent them by proxy by using Anthropic and OpenAI’s models. Though some of them talk a big game about building or training their own models, doing so is enormously expensive with little chance of a payoff, especially given the massive advantage in compute, capital and talent held by the labs.

There really is no clean “out” for any AI startup not named Anthropic or OpenAI. Cognition, valued at $48 billion in its latest funding round, is allegedly worth nearly as much as Ford ($59 billion market cap), yet generates a mere $1 billion in ‘annualized run rate,’ which could mean anything, all while losing $800 million. Ford, by comparison, had $187.2 billion in revenue in 2025, with a net loss of $8 billion attributable in part to a massive writedown of its electric vehicle portfolio ($12.5 billion in Q4 2025 alone).

In 2025, Ford sold around 2.2 million vehicles. Cognition, by comparison, makes yet another AI coding agent.

What, exactly, does Cognition do from here? Who buys Cognition? Does it go public? How? It loses tons of money and has a commoditized product!

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Ed Zitron @edzitron.com · 29/09/2026

It doesn't help that Oracle's largest SVP debt deal has now entered distressed territory — which will, no doubt, set the tone for other similar debt deals, raising the cost of borrowing at a time when costs across the board are skyrocketing. www.wheresyoured.at/dead-money/

So, let’s talk about the $18 billion in debt behind Oracle’s New Mexico-based Project Jupiter data center, starting with ZeroHedge’s diagram of the structure:

Oracle borrowed $18 billion from a syndicate of financial institutions including BNP Paribas, Goldman Sachs, and two Japanese banks — MUFG and SMBC — that have been in effectively every major AI data center deal, including multiple CoreWeave debt facilities, every Stargate/OpenAI/Oracle data center, and even SoftBank’s bridge loan that it used to fund OpenAI’s 2025 funding round. Additionally, funds related to Blue Owl (who is also invested in multiple different Stargate and CoreWeave facilities) kicked in $3 billion in equity to make sure the debt actually got raised.

This kind of labyrinthine structure is how basically every off-balance-sheet and SPV-based data center debt deal is capitalized — a few billion dollars of equity investment, usually from one of a few private credit funds (EG: Blue Owl, Blackstone, BlackRock) that then raise debt from many of the same investors, something I covered at length in my Enshittifinancial Crisis piece from the end of last year. I also went into detail about the SPV structures a few months ago here.

The reason I bring all of this up is that this kind of SPV is the template for data center debt, and the associated investors are a large chunk of the capital funding it, which means that their ability to continue feeding the beast of AI data center debt is what’s holding up this industry.

And now one of their largest data center debt deals, as mentioned, has entered “distressed” status, which means that any further SPVs they’re involved in will price based on the current state of Project Jupiter, which will be priced both based on the project’s health and the current state of Oracle, which is being dragged down by the questionable health of its many, many data center debt deals, all of which are contingent on OpenAI’s ability to pay it $300 billion over five years.

This means that the price of any debt associated with AI data centers is now skyrocketing, at a time when the price of the goods that debt is buying are skyrocketing, at a time when the underlying construction needed to pay back that debt is taking forever.

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Ed Zitron @edzitron.com · 29/09/2026

What makes matters worse is that the more money spent, the more expensive AI infrastructure becomes, meaning that hyperscalers have to raise more debt, which in turn becomes more expensive. AI data centers are an inflationary force unlike any in history. www.wheresyoured.at/dead-money/

And a little under a month later, NVIDIA would bump its prices by more than 15%, partly as a result of memory costs, and partly because it has the entire tech industry by the balls.

So, as more AI data center debt gets issued, said debt becomes more expensive, because the larger the amount of debt any one thing takes up, the more competition it faces, and the more risk an investor carries by holding it. Once the debt is issued, it immediately flows into buying GPUs and associated hardware, slowly growing the cost of memory and hardware, all while increasing the competition for the specialist labor and materials needed to build data centers, such as spiking the cost of Copper, increasing the cost of construction by billions in the process.

In other words, the more you buy, the more you lose. The more money you raise, the more money you need. The more money you need, the more expensive that money becomes. And once you spend that money, everything you spent it on becomes more expensive, including raising more money in the future.

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Ed Zitron @edzitron.com · 29/09/2026

Oracle's November $25bn in 2025 bonds would be 41.5% more expensive if raised today, adding $6.89bn in extra interest. Coreweave's 2025/2026 short-dated debt would be 35.8% more, adding $1.2bn in interest. Both of them need billions more in debt in 2027. www.wheresyoured.at/dead-money/

Across the board, Oracle’s spreads between US Treasuries have effectively doubled, and its new yields range from a bad-yet-manageable 6.73% and 6.91% on its five and seven-year-dated bonds to astonishingly high 8%+ yield across anything longer than 10 years.

On a strictly cash basis, this means that Oracle’s debt would, if issued today, cost it another $6.89 billion in interest.

Last year, CoreWeave was already borrowing at ridiculously-high coupons of over 9%, but if that debt was repriced today, it would be paying at the very best rates between 11% and 13.22% — the kind of numbers you’d associate with a personal loan.

As you can see, repricing CoreWeave at today’s rates would increase its costs by 35.8%, adding $1.2 billion to the lifetime cost of the bonds for a company that already pays $640 billion a quarter in interest.

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Ed Zitron @edzitron.com · 29/09/2026

Despite this economic mismatch, hyperscalers are doubling down, and are expected to borrow $400bn next year, all as Treasury yields spike and debt markets sour thanks to Oracle's "Force Majeure" on its New Mexico data center. It only gets more expensive. www.wheresyoured.at/dead-money/

Per Morgan Stanley, AI-related debt issuance should be around $570 billion in 2026, with around $250 billion of that coming from hyperscalers, and the rest various different forms of high-yield debt shoved into either asset-backed securities or dodgy SPVs for AI data centers.

Things are only set to increase next year. Per Goldman Sachs, hyperscalers will fund more than a third of their AI investments with debt in 2027 — around $400 billion — with Jeff Pu of GF Securities putting the number a little higher at $419 billion, against estimated capital expenditures of around $1.14 trillion, specifically referring to Meta, Google, Amazon, Microsoft, and Oracle.

If we assume that other AI-related debt stays flat on the year, that puts us at $739 billion in AI data center debt in 2027, and if we assume growth matches hyperscaler debt issuance growth (around 67.6%), the number grows to around $939 billion in debt.

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Ed Zitron @edzitron.com · 29/09/2026

AI companies would need $725 billion in annual revenue for them to have both 10% operating margins and hyperscalers to have a 10% ROIC. We are not even close. None of the economics make sense for either side of the coin. www.wheresyoured.at/dead-money/

Yet the part that really worries me is about the so-called “application layer” — the companies paying the hyperscalers for AI compute — and how much revenue they’d need in totality to be able to justify that hyperscaler capex.

The answers are extremely grim. For hyperscalers to break even on their capex through 2027, their AI customers would have to make around $425 billion in annual revenue, and that’s if they had an operating margin of 10%, a number that includes training costs for OpenAI and Anthropic.

To be explicit, this chart measures how much revenue AI companies would need to have specific operating margins and for hyperscalers to have a specific ROIC. In other words, AI companies would have to make $725 billion in annual revenue to have both 10% margins and for hyperscalers to have a 10% ROIC.

For some context about how far we are from these numbers:

OpenAI estimates it will have $36 billion in revenue in 2026.
Through the first half of 2026, Anthropic had around $16.3 billion in revenue, and if we assume that it’s growing faster than OpenAI, that puts its annual revenue around $40 billion for 2026.
Cursor allegedly hit $4 billion in annualized revenue ahead of its acquisition by SpaceX, but that most decidedly does not mean $4 billion in revenue.
Perplexity is allegedly sitting at around $750 million in annualized revenue, but was at $250 million at the start of the year, making its annual revenues likely somewhere in the $350 million range.
Cognition recently hit $1 billion in annualized revenue ($83 million a month) as of September 25, 2026, but never defined what that meant. Considering that The Information had it at around $900 million a month beforehand, I think it’s likely that its revenues sit at around $300 million to $400 million.
The Information also notes that Cognition expects to burn $800 million this year.
Per The Information, OpenAI and Anthropic represent 89% of all AI startup revenues.
Even if Anthropic and OpenAI doubled their revenues and every single one of these “annualized” figures represented the true annual revenue of the companies, we’d be sitting at an embarrassing $157 billion, or roughly $268 billion short.

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Ed Zitron @edzitron.com · 29/09/2026

Data from Goldman Sachs shows that hyperscalers aren't even breaking even on their current and future spending from 2026 and 2027, let alone making a modest profit. Without Anthropic and OpenAI, they barely scratch $100bn in annual AI revenue. www.wheresyoured.at/dead-money/

Last week, Goldman Sachs’ Ryan Hammond got a little more specific, noting that hyperscaler capex estimates were now over $1.1 trillion in 2027.

These revised capex plans also came with a new and deeply-worrying analysis, taking the average of estimated AI capex for 2026 and 2027, and calculating how much annual AI revenue hyperscalers would need to break even on their capital expenditures for just those two years.

To just break even, hyperscalers need $308 billion in annual AI-specific revenues, and for a 10% Return On Invested Capital (calculated based on estimates of depreciation and operating expenses), they’d need $417 billion.

As discussed above, they are — including Anthropic and OpenAI — currently $124.2 billion short of break-even, or $243 billion short of break-even without their revenues, or $233.2 billion to $351 billion short for a measly 10% ROIC.

Now, keep in mind that A) the 2027 capex has yet to be spent and B) that, at least in theory, Anthropic and OpenAI will spend more next year…if hyperscalers are able to build the capacity necessary for them to do so, and they’re able to raise the money to pay them.

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Ed Zitron @edzitron.com · 29/09/2026

Goldman Sachs says that hyperscalers need $308bn in annual AI revenue to break even on their 2026/2027 capex. I estimate that Oracle, Microsoft, Amazon, and SpaceX have AI revenues of $183bn, of which nearly two-thirds come from Anthropic and OpenAI. www.wheresyoured.at/dead-money/

To put that in perspective, Microsoft had around $34.4 billion in AI revenue in fiscal year 2026, of which 70% was OpenAI’s compute spend. Per Barclays estimates, Amazon will have $31.6 billion in total AI revenue in 2026, 73% of which will come from OpenAI and Anthropic, and per UBS estimates, 54.3% of Google’s AI compute sales come from them too, with an undefined amount of Vertex AI model sales coming from Anthropic on top, for a total of around $65 billion in AI revenue, which sounds a little high.

Adding all those together gets us to around $131 billion in AI revenues for Google, Microsoft and Amazon, of which $82.2 billion (62.7%) are from Anthropic and OpenAI.

As of its latest quarter, SpaceX had (when you strip out Twitter’s ad revenues) around $2.194 billion in AI revenue, or $8.7 billion on an annualized basis, but I’ll bump that up to $25 billion on the year to include its full $1.25 billion a month from Anthropic and $920 million a month from Google, though I’ll add that both have 90 day outs. If we assume that Anthropic’s discounted compute for that quarter meant that it accounted for only $500 million of SpaceX’s AI revenue, this puts us at approximately $32.8 billion in AI revenue for SpaceX, with (as I believe Google will rent the compute directly to Anthropic) 79.3% of that coming from Anthropic.

While we don’t know Oracle’s actual AI revenues, it disclosed in its last quarter that its CPU and GPU revenues were at $6.5 billion for the quarter, or around $26 billion a year in revenue. Because I’m feeling nice, I’m going to say that Oracle has approximately $20 billion in annual AI revenue, but due to a lack of information it’s tough to say how much of that is OpenAI, though I’d imagine we’re looking at at least $8 billion or more given the progress of Stargate Abilene and the (as confirmed with sources) H100 and H200 GPUs currently rented to the AI lab. As a result, I think it’s fair to say at least 50% of Oracle’s AI revenues are from OpenAI.

This puts us at $183 billion in annual AI revenue for Google, Microsoft, Amazon, Oracle and SpaceX, with $118.2 billion, or at least 64.3%, coming from Anthropic and OpenAI.

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Ed Zitron @edzitron.com · 29/09/2026

The AI trade is speculative, depending on the survival of two unsustainable AI labs, themselves dependent on unsustainable startups for revenue. And now multiple banks have estimated that hyperscalers need $3 trillion+ in annual AI revenue to justify their capex. www.wheresyoured.at/dead-money/

I’ll admit it’s vindicating to see so many people suddenly jump on the “how much money do hyperscalers need to justify their capex?” train, even if not a single one of them bothers to give me credit. Per Callum Williams of The Economist, Google, Amazon, Meta, Microsoft, Oracle, and SpaceX will need somewhere in the region of $1.29 trillion in annual AI revenue to get a 10% return on invested capital for their capex through the end of 2027, with the amount rising to $2.87 trillion if this farce continues through 2030.

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Ed Zitron @edzitron.com · 29/09/2026

This customer concentration is a big problem for OpenAI and Anthropic, with the 80% of their revenues coming from 1% of customers — most of those being, themselves, unprofitable AI startups subsidizing their users' token spend. Without VC, it all tanks. www.wheresyoured.at/dead-money/

And that’s absolutely what’s happening, suggesting that the “AI boom” is more like five or six large companies (hyperscalers) feeding money to two companies (NVIDIA and Broadcom) so that they can feed money to two companies (Anthropic and OpenAI) who then feed that money back to them whenever capacity comes online. I estimate that there’s around $22 billion of global, non-Anthropic/OpenAI compute demand, and an indeterminately-large chunk of that is coming from AI startups that can only afford to pay for the compute as long as venture capital continues to fund them…

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Ed Zitron @edzitron.com · 29/09/2026

This all comes back to a point I've been making for a while now: We've treated NVIDIA's chip sales as reflective of big AI demand, when in reality $200bn+ of the GPUs are in storage, and those that are installed are mostly rented to Anthropic and OpenAI. www.wheresyoured.at/dead-money/

In other words, the talking point that NVIDIA’s GPU sales are proof of actual demand for AI services or, indeed, that hyperscaler growth is a result of all those capital expenditures is a complete lie. In reality, at least half of all those chip sales — and I’d add in Broadcom’s TPU sales too (see my Hater’s guide for more) — are being made years before anything actually happens with the chips, making the trillion-plus dollars spent on capex so far seem somewhere between optimistic and utterly incoherent.

Microsoft, Google, Amazon, Meta, Oracle, and far too many other companies have been hoarding hundreds of billions of dollars of AI chips that they either (to quote Microsoft CEO Satya Nadella) can’t plug in or simply want to have in supply for reasons that I find tough to imagine.

venture capitalist that “...some companies are hoarding colossal amounts in case they come to a point at which they don’t have enough chips to provide the computing capacity,” as if there’s been any shortage of NVIDIA chips, outside of the illusory one created by hyperscalers buying them years in advance.

So, we’ve got a situation where Microsoft, Google, Amazon, Meta, SpaceX, CoreWeave, and every imaginable neocloud is sitting on hundreds of billions of uninstalled GPUs (and increasingly TPUs). Whenever more capacity comes online, it’s immediately sold to OpenAI or Anthropic, who make up anywhere from 70% to 80% of all AI revenues and compute demand, creating the illusion that revenue growth is “coming from demand for AI compute” rather than said demand coming from two companies that have been fed over $217 billion in the last nine months, with the vast majority of it coming from Google, Amazon, Microsoft, and NVIDIA themselves.

As I discussed last week, If “demand is outstripping supply” because of millions of customers begging for AI compute, that’s very different to “demand outstripping supply” because two or three (including Meta) customers are taking up most or all of the capacity. Not to repeat myself, but…

Similarly, if “demand is outstripping supply” because lots of capacity is coming online and a diverse subset of customers is buying it, that’s vastly different to if capacity is coming on slowly, and the vast majority of it is being given straight to OpenAI, Anthropic, or Meta.
And that’s absolutely what’s happening, suggesting that the “AI boom” is more like five or six large companies (hyperscalers) feeding money to two companies (NVIDIA and Broadcom) so that they can feed money to two companies (Anthropic and OpenAI) who then feed that money back to them whenever capacity comes online. I estimate that there’s around $22 billion of global, non-Anthropic/OpenAI compute demand, and an indeterminately-large chunk of that is coming from AI startups that can only afford to pay for the compute as long as venture capital continues to fund them…

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Ed Zitron @edzitron.com · 29/09/2026

Last week, Fidelity published a report that said the AI trade had become "dead money," with GPU leases and token spending flat or down, and the FT's Bryce Elder reported research that said that 50% of the GPUs sold in 2026 and 2027 wouldn't be installed. www.wheresyoured.at/dead-money/

Last week, Fidelity Director of Global Macro Jurien Timmer said that “the [AI trade] has been dead money for more than three months,” citing that both token expenditures and GPU lease rates were all “flat to down,” citing specifically rental rates for H100 and A100 GPUs. While the counterargument might be that Blackwell GPU rental rates aren’t included, as I discussed last week, it’s questionable how many B200, B300, or other Blackwell chips are actually available for rent, as it appears that anywhere from $200 billion to $300 billion of NVIDIA’s sales since 2022 are sitting in warehouses or unplugged in data centers waiting for power.

The Financial Times’ Bryce Elder took the ball and ran with it, and found research that backed up what I’d been saying, emphasis mine:

Morgan Stanley measured the gap earlier this week by estimating the shortfall in available power, concluding that more than half of the GPU servers sold between 2026 and 2028 might not have anywhere to be plugged in.
Yet Elder makes the point, based on research from Jefferies, that there’re far more problems than simply not having enough power:

In the longer term, power availability is still the bottleneck — along with labour. And transformers. And cooling equipment. And backup generation. As Jefferies says: “The gap between planned capacity and physical execution remains the central issue.”

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Ed Zitron @edzitron.com · 29/09/2026

wheresyoured.at

https://www.wheresyoured.at/dead-money/

If you liked this piece, you should subscribe to my premium newsletter, and you can subscribe on the following links: $70 a year, $18 a quarter, or $7 a month. In return you get a weekly premium…

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Ed Zitron @edzitron.com · 29/09/2026

it's that there have been some stories that the company has somehow become profitable in some ways except it was in a quarter it got a discount from Musk for two months (Q2), then the next one had an "adjusted operating profit," which means it's a loss lol

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Ed Zitron @edzitron.com · 29/09/2026

how does that reduce operating expenses

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Ed Zitron @edzitron.com · 29/09/2026

but why are OpenAI's economics so much worse? something doesn't line up!

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Ed Zitron @edzitron.com · 29/09/2026

How did they materially turn around their costs so suddenly? The product they sell must have suddenly - in the space of mere months - both accelerated its revenues while massively reducing its costs in a way that doesn't seem possible given 2025. I guess we'll find out

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Ed Zitron @edzitron.com · 29/09/2026

I need to ask: do you not find these numbers somewhat concerning?

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Ed Zitron @edzitron.com · 29/09/2026

what chips, be specific

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Ed Zitron @edzitron.com · 29/09/2026

and when is the cost of compute coming down exactly

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Ed Zitron @edzitron.com · 29/09/2026

Anthropic has also circulated in the press for years that it was the "more profitable" and "more financially stable" competitor to OpenAI when the literal opposite was true for years. I think it's necessary - even if you love LLMs - to be extremely skeptical of the company.

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Ed Zitron @edzitron.com · 29/09/2026

It makes the magnitude of the losses worse

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Ed Zitron @edzitron.com · 29/09/2026

So it increased, what does that change about the point about it’s shitty economics

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Ed Zitron @edzitron.com · 29/09/2026

Correction: this is likely now meta and cursor

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Ed Zitron @edzitron.com · 29/09/2026

That’s not true, it had $4.6bn in revenue

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Ed Zitron @edzitron.com · 29/09/2026

Anthropic fans don’t even try and defend the company anymore they just look at you like this

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Ed Zitron @edzitron.com · 29/09/2026

Nothing to do with it!

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Ed Zitron @edzitron.com · 29/09/2026

So far the only retort from the AI boosters appears to be “2025 doesn’t matter” and I’m not kidding

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Ed Zitron @edzitron.com · 29/09/2026

Based on my own reporting on OpenAI's audited financials from 2025, it appears that Anthropic was a worse business (at least in that year), spending $2.75 make $1 versus OpenAI spending $2.60 to make $1. So many people told me this company was "more profitable"! www.wheresyoured.at/exclusive-op...

OpenAl Lost $38.5 Billion In 2025
2025 — OpenAl Had $13.07 Billion In Revenue, $34 Billion In Costs and Expenses, and $20.92 Billion In Losses, with a net loss attributable to the company of $38.53 Billion
• Revenue: $13.07 billion
• Cost of Revenue: $7.5 billion
• Research and Development: $19.18 billion
• Sales and Marketing: $5.73 billion
• General and Administrative: $1.57 Billion
• Total Costs and Expenses: $34 billion
• Loss from Operations: $20.92 billion

The Al lab spent $7.33 billion on compute and infrastructure last year, a threefold surge from 2024, accounting for more than half of its
$12.65 billion in total operating expenses.

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Ed Zitron @edzitron.com · 29/09/2026

If you have the Anthropic S-1, please message me at ezitron.76 on signal, i will protect your identity

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Ed Zitron @edzitron.com · 29/09/2026

yeah i was gonna say lol

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