Pundit ClaimsAI claims by Gary Marcus and Ed Zitron, with the evidence

Ed Zitron Where's Your Ed At Published

Concentration Risk

We recorded 32 claims from this post. 19 were checked against evidence. 13 can’t be checked. 26 more are held. Read the post at its source.

Claims from this post (32)

In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.

  1. Assessment: UnresolvedSaid

    “Per sources with direct knowledge of the current progress of Stargate Abilene, the AI data center being built by Crusoe for Oracle to lease to OpenAI, there are at most four out of eight buildings functional at the Abilene campus, which started construction some time in 2024.”

    What we tested: At most four of the eight buildings at the Stargate Abilene campus are functional.

  2. Assessment: Can’t be checkedSaid

    “The answer is pretty simple: these people want to stop you thinking about what’s actually happening — that the underlying financials and demand do not make sense, and their cloud software does not remotely justify its alarming costs.”

    What we tested: AI companies talk about AGI to distract from the fact that their financials and demand do not make sense and their software does not justify its costs.

  3. Assessment: UnresolvedSaid

    “I bring this all up because you’re going to hear this term, or variations of this term, a lot in the next few months and years as the AI bubble unravels, because just about every part of the industry involves its own flavor of concentration risk.”

    What we tested: The AI bubble will unravel over the next few months and years, with concentration risk across nearly every part of the industry.

  4. Assessment: UnresolvedSaid

    “Let’s start at the top. Per data from fintech firm Ramp, 80% of OpenAI and Anthropic's enterprise revenues come from 1% of their customers, a number that hasn’t improved over the last three years.”

    What we tested: Per Ramp data, 80% of OpenAI and Anthropic's enterprise revenues come from 1% of their customers, a share that hasn't improved over the last three years.

  5. Assessment: UnresolvedSaid

    “In virtually every case I’ve found, the AI startup “subsidizes” the AI use of their customers, allowing them to burn way more than their monthly subscription in tokens, with the AI startup paying for the tokens at either full or a slightly-discounted price.”

    What we tested: In virtually every case Zitron has found, the AI startup subsidizes its customers' AI use, letting them burn far more than their monthly subscription in tokens, while the startup pays full or slightly-discounted token prices.

  6. Assessment: UnresolvedSaid

    “And let’s be completely clear: OpenAI and Anthropic are financially dependent on these customers to survive.”

    What we tested: OpenAI and Anthropic depend financially on VC-backed AI startup customers to survive.

  7. Assessment: Can’t be checkedSaid

    “With OpenAI only representing 5% of Cursor’s traffic, it’s likely sending billions more to Anthropic this year, a massive underlying exposure that could easily evaporate if Elon Musk decides he doesn’t want to send all that money to competing AI labs.”

    What we tested: With OpenAI only 5% of Cursor's traffic, Cursor is likely sending billions more to Anthropic this year, a massive exposure that could easily evaporate if Elon Musk decides he doesn't want to send that money to competing AI labs.

  8. Assessment: UnresolvedSaid

    “The problem is both that Anthropic and OpenAI’s largest customers cannot afford to pay them and that they desperately need them to keep paying them more every quarter, which means that every single AI startup will need to raise more and more money to do so.”

    What we tested: Anthropic and OpenAI's largest customers cannot afford to pay them, yet the labs desperately need them to keep paying more every quarter, which means every single AI startup will need to raise more and more money to do so.

  9. Assessment: UnresolvedSaid

    “That means that outside of unprofitable AI startups, the vast majority of “enterprises” spending money on AI are tech companies rather than other industries.”

    What we tested: Outside of unprofitable AI startups, the vast majority of enterprises spending money on AI are tech companies rather than other industries.

  10. Assessment: UnresolvedSaid

    “In other words, outside of the tech and AI world, very few companies are willing to pay very much for AI, which is catastrophic on just about every level, with no clear sign as to how you reverse the trend.”

    What we tested: Very few companies outside tech and AI are willing to pay much for AI, and there is no clear way to reverse this.

  11. Assessment: UnresolvedSaid

    “No they won’t. As I’ll get into, the companies that are meant to buy the compute can’t afford it, and nobody else is buying compute at even close to that scale.”

    What we tested: No one else will buy the compute committed to by OpenAI and Anthropic, because the companies meant to buy it can't afford it and nobody else is buying compute at even close to that scale.

  12. Assessment: UnresolvedSaid

    “That being said, another example has emerged — Anthropic and OpenAI’s monstrous compute commitments, which now represent over $1.3 Trillion in revenue for hyperscalers and neoclouds like Google, Microsoft, Amazon, SpaceX, Hut8, SB Energy, Oracle, Cerebras, Nscale and Lambda.”

    What we tested: Anthropic and OpenAI's compute commitments now represent over $1.3 trillion in revenue for hyperscalers and neoclouds such as Google, Microsoft, Amazon, SpaceX, Hut8, SB Energy, Oracle, Cerebras, Nscale and Lambda.

  13. Assessment: UnresolvedSaid

    “On the low end, that means that Anthropic and OpenAI account for over $200 billion dollars worth of expected revenues for Microsoft, Google and Amazon in 2027, which is contingent on their ability to raise venture capital or debt, which is contingent on the continued growth of their businesses, which is contingent on growing AI spend from a small subset of customers, many of whom are funded by venture capital.”

    What we tested: On the low end, Anthropic and OpenAI account for over $200 billion of expected 2027 revenue for Microsoft, Google and Amazon, which depends on the labs raising venture capital or debt, which depends on their continued growth, which depends on growing AI spend from a small subset of customers, many of whom are VC-funded.

  14. Assessment: Can’t be checkedSaid

    “Anthropic and OpenAI’s compute commitments, in my mind, should be seen more as debt obligations than “contracts,” because they (as take-or-pay agreements) function in much the same way, requiring the company to pay whether or not they need the capacity.”

    What we tested: Anthropic and OpenAI's take-or-pay compute commitments should be viewed as debt obligations.

  15. Assessment: UnresolvedSaid

    “As mentioned, this is going to begin in earnest in 2027, and expand dramatically every year following (though I doubt we will make it that far).”

    What we tested: Compute commitment payments will begin in earnest in 2027 and expand dramatically every year after, though Zitron doubts 'we will make it that far'.

  16. Assessment: UnresolvedSaid

    “Next year, at least $200 billion in compute costs are coming due.”

    What we tested: At least $200 billion of OpenAI and Anthropic compute costs will come due in 2027.

  17. Assessment: Can’t be checkedSaid

    “While the consequences might be different — as the scale and damage of the Great Financial Crisis was driven by trillions in speculation — the mistakes are increasingly looking very, very similar.”

    What we tested: The mistakes in AI financing increasingly resemble those that led to the Great Financial Crisis, though consequences may differ.

  18. Assessment: Can’t be checkedSaid

    “And here’s the fun part: Anthropic and OpenAI’s reset wall is actually way simpler, more-concentrated and easier-to-spot if you bother to look!”

    What we tested: Anthropic and OpenAI's compute 'reset wall' is simpler, more concentrated, and easier to see than the subprime mortgage reset wall.

  19. Assessment: Can’t be checkedSaid

    “That spike in costs comes from Stephen Ju of UBS’ estimates, and even if you think that’s a little high, I would estimate that the $250 billion of commitments made by OpenAI alone on Microsoft Azure will likely mean Microsoft is expecting tens of billions more than $52.5 billion in FY27 and beyond.”

    What we tested: Zitron estimates that OpenAI's $250 billion of Azure commitments alone will likely mean Microsoft is expecting tens of billions more than $52.5 billion in FY27 and beyond.

  20. Assessment: Can’t be checkedSaid

    “Then you have to add in another $30 billion from Oracle’s $300 billion, five-year-long deal with OpenAI, which the Wall Street Journal reports is expected to drive $30 billion in revenue starting in 2027, though my own research found that it could be more than $50 billion or $60 billion”

    What we tested: OpenAI's annual payments under its Oracle deal could exceed $50–60 billion from 2027, not just the reported $30 billion.

  21. Assessment: Can’t be checkedSaid

    “If it doesn’t, it means that in 2028 or 2029, its commitments could spike to $300 billion or $400 billion a year.”

    What we tested: If OpenAI's compute spend isn't spread at $250B a year, its commitments could spike to $300–400B a year in 2028 or 2029.

  22. Assessment: Can’t be checkedSaid

    “Let’s be abundantly clear about something: there is no rational or responsible way that Google, Microsoft, Amazon and the various other neoclouds should have allowed Anthropic and OpenAI to sign up for so much compute capacity, outside of the kind of blind faith that always goes wrong.”

    What we tested: Hyperscalers and neoclouds should not have let Anthropic and OpenAI sign up for so much compute capacity.

  23. Assessment: Can’t be checkedSaid

    “Hyperscalers are doing all of this based on the very same logic that led to the massive issuance of subprime (and prime-but-unpayable) mortgages and the resulting overbuild of housing — that the money hadn’t stopped being spent.”

    What we tested: Hyperscalers are extending compute to AI labs using the same logic as subprime mortgage lenders: the money hasn't stopped flowing yet.

  24. Assessment: Can’t be checkedSaid

    “Sidenote: At this point, I really want to use Groundbreaker’s charts, but their numbers are, if I’m honest, total fucking dogshit — Anthropic and OpenAI are very unlikely to have spent over $120 billion on compute in 2026, and I can find absolutely nothing to back them up.”

    What we tested: Anthropic and OpenAI very likely will not have spent over $120 billion combined on compute in 2026.

  25. Assessment: Can’t be checkedSaid

    “These commitments were signed, I assume, with effectively no underwriting, because anyone with a calculator and sentience can see that on paper these companies cannot afford their commitments.”

    What we tested: OpenAI and Anthropic's compute commitments were likely signed with effectively no underwriting, since the companies plainly cannot afford them.

  26. Assessment: UnresolvedSaid

    “In any case, neither OpenAI nor Anthropic actually have the money to pay for their obligations, and have only been able to keep up because of the low cost of signing contracts.”

    What we tested: Neither OpenAI nor Anthropic has the money to pay for their obligations, and they have only been able to keep up because signing contracts costs little.

  27. Assessment: UnresolvedSaid

    “I’m going to dispense with the direct Great Financial Crisis comparisons at this point because I think it’ll get in the way of the analysis, but let’s be abundantly clear about something: either directly or by proxy, NVIDIA’s customer base is effectively Anthropic and OpenAI.”

    What we tested: Directly or by proxy, NVIDIA's customer base is effectively Anthropic and OpenAI.

  28. Assessment: UnresolvedSaid

    “They are the largest direct consumer of AI compute, representing more than 70% of all AI revenues for Google, Microsoft, Amazon, Oracle, SpaceX, Cerebras and Lambda, either through direct contracts or via hyperscalers renting compute (see: Nebius and Microsoft, Lambda and Microsoft/Amazon, CoreWeave with Microsoft).”

    What we tested: OpenAI and Anthropic account for over 70% of AI revenues for Google, Microsoft, Amazon, Oracle, SpaceX, Cerebras and Lambda.

  29. Assessment: UnresolvedSaid

    “The other problem is that NVIDIA’s GPUs are so god damn expensive that nobody — including the largest and richest companies in the world (minus Microsoft) — can afford to keep buying them and building data centers without taking on near-infinite amounts of debt, reducing the pool of potential customers dramatically.”

    What we tested: NVIDIA's GPUs are so expensive that nobody, including the largest and richest companies except Microsoft, can afford to keep buying them and building data centers without taking on near-infinite debt, which dramatically reduces the pool of potential customers.

  30. Assessment: UnresolvedSaid

    “And, fundamentally, NVIDIA’s revenues are dependent on whether hyperscalers keep being paid by OpenAI and Anthropic, because those are the only two companies that could ever hope to justify their trillion-plus dollars of capex.”

    What we tested: NVIDIA's revenues depend on hyperscalers continuing to be paid by OpenAI and Anthropic, the only companies that could justify their trillion-plus capex.

  31. Assessment: UnresolvedSaid

    “Much like the hyperscalers, neither Broadcom nor NVIDIA is going bankrupt as a result of the AI bubble bursting, but Broadcom’s future revenues — estimated at $230 billion in Fiscal Year 2028 (which begins November 2027) — are now dependent on both direct purchases from hyperscalers (justified by Anthropic and OpenAI) and the AI labs themselves, creating, somehow, greater underlying exposure.”

    What we tested: Neither Broadcom nor NVIDIA will go bankrupt as a result of the AI bubble bursting, but Broadcom's future revenues, estimated at $230 billion in FY2028, now depend on hyperscaler purchases justified by Anthropic and OpenAI and on the labs themselves, creating greater underlying exposure.

  32. Assessment: Can’t be checkedSaid

    “However you may feel about me or the greater AI bubble is immaterial to the fact that everything will seem like it’s fine right up until somebody can’t raise money and make a payment to either a neocloud, hyperscaler or AI lab.”

    What we tested: The AI industry will look fine until someone can't raise money to make a payment to a neocloud, hyperscaler or AI lab.

Held from this post (26)

These records did not pass every check, so nothing about them is published. Held is not a finding.