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

Ed Zitron Where's Your Ed At Published

Where're All The AI Chips?

We recorded 35 claims from this post. 17 were checked against evidence. 18 can’t be checked. 41 more are held. Read the post at its source.

Claims from this post (35)

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: Can’t be checkedSaid

    “It has claimed again and again that it has brought gigawatts of capacity online for the best part of a year, all, in my opinion, with the intent of misrepresenting the scale of an AI data center buildout where I believe most of the GPUs, to quote Satya Nadella, are now “sitting in inventory that [they] can’t plug in.””

    What we tested: In Zitron's opinion, most of Microsoft's GPUs are sitting in inventory uninstalled and its capacity claims are intended to misrepresent the AI buildout.

  2. Assessment: UnresolvedSaid

    “Today’s newsletter is about a cruel truth: that NVIDIA’s revenue growth is almost entirely the result of speculative purchases by hyperscalers and neoclouds that take years to install its GPUs.”

    What we tested: NVIDIA's revenue growth is almost entirely the result of speculative purchases by hyperscalers and neoclouds that take years to install the GPUs.

  3. Assessment: Can’t be checkedSaid

    “In other words, I think everybody is completely wrong about data center capacity, and it’s going to be a nightmare to untangle once they work it out.”

    What we tested: The author thinks everybody is completely wrong about data center capacity, and that it will be a nightmare to untangle once they work it out.

  4. Assessment: Can’t be checkedSaid

    “Everybody wants AI to be just like the Dot-Com Bubble, when I fear that GPUs may end up like the millions of unsold copies of Atari’s ET found buried in New Mexico.”

    What we tested: The author fears that GPUs may end up like the millions of unsold copies of Atari's ET found buried in New Mexico.

  5. Assessment: Can’t be checkedSaid

    “While I cannot say the exact rationale for making these statements, I can find no way to interpret them other than being an act of deception.”

    What we tested: The author cannot say the exact rationale, but can find no way to interpret Microsoft's FY26 earnings-call statements about adding a gigawatt of capacity a quarter other than as an act of deception.

  6. Assessment: Can’t be checkedSaid

    “This is a huge scandal.”

    What we tested: It is a huge scandal that Microsoft buys GPUs it has nowhere to put while saying it is bringing gigawatts of capacity online.

  7. Assessment: UnresolvedSaid

    “In other words, Microsoft is warehousing anywhere from $50 billion to $100 billion in GPUs, and has barely gotten $50 billion worth installed in the last four years.”

    What we tested: Microsoft is warehousing $50–100 billion in GPUs and has installed barely $50 billion worth in the last four years.

  8. Assessment: Can’t be checkedSaid

    “If Microsoft is struggling, everybody’s struggling, and we may have a very inconvenient truth: that NVIDIA has potentially sold hundreds of billions of GPUs years in advance.”

    What we tested: If Microsoft is struggling, everybody is struggling, and it may be true that NVIDIA has potentially sold hundreds of billions of GPUs years in advance.

  9. Assessment: Can’t be checkedSaid

    “And if the truth — and this very much seems to be the case — is that NVIDIA has sold hundreds of billions of dollars of GPUs years in advance, that materially changes everything about the AI bubble and the AI data center buildout.”

    What we tested: If NVIDIA has sold hundreds of billions of dollars of GPUs years in advance, which very much seems to be the case, that materially changes everything about the AI bubble and the AI data center buildout.

  10. Assessment: UnresolvedSaid

    “It’s very clear that Microsoft is playing silly buggers with the term “capacity,” which makes me believe this is an industry-wide problem.”

    What we tested: It is very clear that Microsoft is playing silly buggers with the term 'capacity', which makes the author believe this is an industry-wide problem.

  11. Assessment: UnresolvedSaid

    “I don’t even have a clear answer as to what’s going on here, other than that we don’t have much (if any) clarity around how much data center capacity is even being built.”

    What we tested: There is little if any clarity about how much data center capacity is actually being built.

  12. Assessment: UnresolvedSaid

    “Hyperscalers are getting increasingly worse at turning their capex into operational capacity.”

    What we tested: Hyperscalers are getting increasingly worse at turning capex into operational capacity.

  13. Assessment: Can’t be checkedSaid

    “Hyperscalers have a spending problem.”

    What we tested: Hyperscalers have a spending problem.

  14. Assessment: Can’t be checkedSaid

    “It’s also clear that Microsoft, Google, Amazon, Meta, SpaceX, and every neocloud are purchasing NVIDIA GPUs tens of billions at a time under the implicit knowledge that it will take years to build the capacity and connect the power to them, creating what amounts to the largest pre-order campaign in the history of capitalism, but also a material misrepresentation of the current AI buildout.”

    What we tested: It is clear that Microsoft, Google, Amazon, Meta, SpaceX and every neocloud are buying NVIDIA GPUs tens of billions at a time, implicitly knowing it will take years to build the capacity and connect power, which amounts to the largest pre-order campaign in the history of capitalism and a material misrepresentation of the current AI buildout.

  15. Assessment: UnresolvedSaid

    “In any case, that’s a shit ton of undeployed silicon, and a very, very, very different picture to the one that both NVIDIA and the hyperscalers have been telling investors.”

    What we tested: The large amount of undeployed silicon contradicts the picture NVIDIA and hyperscalers have given investors.

  16. Assessment: UnresolvedSaid

    “For the most part, hyperscalers have been given credit for their capital expenditures because overall revenues have grown, with everyone saying that their “AI bets have paid off,” when it’s clear that the AI bets in question have barely started to come online.”

    What we tested: Hyperscalers have mostly been credited for their capex because overall revenues grew, with everyone saying their 'AI bets have paid off', when it is clear those AI bets have barely started to come online.

  17. Assessment: Can’t be checkedSaid

    “This, by the way, is the problem with hyperscalers not explicitly breaking out their AI revenue, because in doing so they create the (I’d argue deliberate) illusion that AI capex is creating revenue growth, which both tricks investors into buying their stock and tricks developers into building AI data centers, believing that capex quickly translates into revenue.”

    What we tested: By not breaking out AI revenue, hyperscalers create an arguably deliberate illusion that AI capex drives revenue growth, misleading investors and developers.

  18. Assessment: UnresolvedSaid

    “I’ve seen estimates of 12GW, 15GW, and as much as 20GW of capacity coming online in 2026, but based on everything I’ve talked about today, I think it’s farcical to believe that more than five to ten gigawatts of operational AI data center capacity actually exists.”

    What we tested: No more than five to ten gigawatts of operational AI data center capacity actually exists.

  19. Assessment: UnresolvedSaid

    “Right now, capacity is coming on very, very slowly, and nobody really wants to talk about it.”

    What we tested: AI data center capacity is coming online very slowly.

  20. Assessment: UnresolvedSaid

    “All of this is to say that, for the most part, AI data center projects get announced and funded all the time, that the press willingly or otherwise engages in laundering the scale and completion of the projects, and everybody on the outside is deceived into thinking the AI buildout is faster and more effective than it really is.”

    What we tested: For the most part, AI data center projects are announced and funded all the time, and the press, willingly or otherwise, launders their scale and completion, so outsiders are deceived into thinking the buildout is faster and more effective than it really is.

  21. Assessment: UnresolvedSaid

    “This means that the $290 billion in AI data center debt issued this year (outside of hyperscalers) will go towards building capacity at whatever rate it can, which is a problem because the vast majority of these deals are project financing-based, meaning that they’re funded out of the revenues of a customer who may or may not exist.”

    What we tested: The $290 billion of AI data center debt issued this year outside hyperscalers will go towards building capacity at whatever rate it can, which is a problem because the vast majority of these deals are project-financed, funded from the revenues of a customer who may or may not exist.

  22. Assessment: Can’t be checkedSaid

    “In all honesty, the best case scenario would be if NVIDIA stopped selling GPUs, or AI data center debt stopped being issued, because every single time a data center is funded and breaks ground, it increases the severity of the overbuild scenario.”

    What we tested: The best-case scenario would be for NVIDIA to stop selling GPUs or for AI data center debt to stop being issued, because every time a data center is funded and breaks ground it makes the overbuild worse.

  23. Assessment: Can’t be checkedSaid

    “Most of NVIDIA’s sales are sitting in warehouses, and that is a significant disclosure that NVIDIA should have already been forced to make.”

    What we tested: NVIDIA should have been forced to disclose that most of its sales are sitting in warehouses.

  24. Assessment: UnresolvedSaid

    “the “demand” cycle for these chips, or really any AI chip, is entirely manufactured as a result of four or five large customers buying so many and Huang making statements about revenue generation that do not reflect reality.”

    What we tested: The 'demand' cycle for these chips, or really any AI chip, is entirely manufactured by four or five large customers buying so many and by Huang making statements about revenue generation that do not reflect reality.

  25. Assessment: Can’t be checkedSaid

    “Perhaps this doesn’t rise to the level of SEC action, but every single journalist and analyst should be asking Jensen Huang and every hyperscaler executive buying GPUs the following questions:”

    What we tested: Journalists and analysts should press NVIDIA and hyperscaler executives on how many GPUs are actually operational and generating revenue.

  26. Assessment: UnresolvedSaid

    “NVIDIA’s perpetual quarterly revenue growth, which is branded, once again, as insatiable demand for AI compute, when it’s actually almost entirely-speculative purchases based on potential revenues, with said potential mostly driven by the compute spend from OpenAI and Anthropic, two unprofitable and unsustainable AI labs.”

    What we tested: NVIDIA's quarterly revenue growth, branded as insatiable demand for AI compute, is actually almost entirely speculative purchasing based on potential revenues, and that potential is mostly driven by compute spending from OpenAI and Anthropic, which he calls unprofitable and unsustainable.

  27. Assessment: UnresolvedSaid

    “Demand for NVIDIA GPUs — and those from Broadcom, AMD and other semiconductor companies — is driven by speculative capital believing that the AI industry will become magnitudes larger than it is today, largely driven by the fact that everybody believes there’s far more demand for compute capacity than actually exists.”

    What we tested: AI chip demand is driven by speculative capital that overestimates real demand for compute.

  28. Assessment: UnresolvedSaid

    “In other words, I believe we are now in an inevitable overbuild situation, one with no neat, tidy Dot-Com Bubble-style exit story.”

    What we tested: The author believes we are now in an inevitable overbuild situation, with no neat, tidy Dot-Com-style exit story.

  29. Assessment: Can’t be checkedSaid

    “Everybody celebrating Anthropic’s (entirely fictional) plans to have 5GW of capacity by the end of 2026 should know that this company is inspiring one the largest misallocation of capital in the history of capitalism.”

    What we tested: Anthropic's plan to have 5GW of capacity by the end of 2026 is entirely fictional, and the company is inspiring one of the largest misallocations of capital in the history of capitalism.

  30. Assessment: Can’t be checkedSaid

    “I fear that every single model around existing and future data center construction and AI compute demand is wrong, and that every assumption we have about the underlying economics of AI is corrupted by the belief that there’s far more operational capacity than there really is.”

    What we tested: The author fears that every model of existing and future data center construction and AI compute demand is wrong, and that every assumption about the underlying economics of AI is corrupted by the belief that there is far more operational capacity than there really is.

  31. Assessment: UnresolvedSaid

    “At the very least, hyperscalers are going to be burdened with brutal depreciation charges or onerous write-offs for years to come, whether their capacity turns into revenue or not.”

    What we tested: Hyperscalers will face brutal depreciation charges or write-offs for years regardless of revenue.

  32. Assessment: UnresolvedSaid

    “I don’t even know how to write what I’m thinking without sounding alarmist…but I don’t see how 90%+ of NVIDIA’s sales ever end up generating a single dollar of revenue”

    What we tested: The author does not see how 90% or more of NVIDIA's sales ever generate a single dollar of revenue, and given how many data center debt deals are project-financed, very little protects investors if AI compute demand never arrives.

  33. Assessment: Can’t be checkedSaid

    “I think everybody who invests in these things ultimately loses, ranging from embarrassment and terrible earnings for hyperscalers to genuine destruction for anyone that trusted the pablum that “all useful compute will be used.” Until that happens, more and more money will be sunk into further theoretical capacity, making the eventual collapse all the more gruesome.”

    What we tested: The author thinks everybody who invests in these things ultimately loses, from embarrassment and terrible earnings for hyperscalers to genuine destruction for anyone who trusted that 'all useful compute will be used'. Until then, more money will be sunk into theoretical capacity, making the eventual collapse more gruesome.

  34. Assessment: Can’t be checkedSaid

    “None of this ever had anything to do with AI, and everybody who cheered Jensen Huang’s ascent in the belief it did is a mark.”

    What we tested: The NVIDIA GPU boom never had anything to do with AI itself.

  35. Assessment: Can’t be checkedSaid

    “The longer this continues, the more promises are made, the more projects that are announced…the worse it’s going to be.”

    What we tested: The longer the AI buildout continues and more projects are announced, the worse the eventual fallout will be.

Held from this post (41)

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