Sam Altman's Trillion-Dollar Bubble: Why OpenAI is the 'Lehman Brothers' of the AI World?

Original article by Ed Zitron

Translation by Qin Xiaofeng, Odaily Planet Daily (@QinXiaofeng 888 )

Editor's Note: OpenAI secretly filed for an IPO with the SEC in June 2026, and is gradually approaching an IPO. The current timeline may be pushed back to 2027. If successful, it would become one of the largest AI IPOs in history.

Recently, independent tech commentator Ed Zitron published a lengthy article criticizing OpenAI. He argues that the real AI bubble is essentially the "OpenAI bubble." If OpenAI fails, it will become the "Lehman Brothers" of the AI era, potentially triggering a repricing of data centers, AI infrastructure, and tech stocks. He emphasizes that OpenAI's business model is unsustainable, relying on subsidies and circular financing, lacking genuine demand. (Odaily note: Ed Zitron is known for his straightforward style and intense focus on financial details when deconstructing tech bubbles. This long-form piece is his latest and most aggressive critique in a series criticizing the AI bubble, which has previously included articles like an exclusive report on OpenAI's losses and the Silicon Valley Bubble series.)

The original text is lengthy; Odaily Planet Daily presents the compiled translation below. Enjoy～

——————————————

Today's article is one of the largest free newsletters I've ever written, synthesizing the work of the past six months.

And it all starts with one question: How much do you trust Sam Altman? The stock market, and to some extent the global economy, hinges on your answer.

OpenAI has become one of the largest liabilities in modern economic history. You can argue that OpenAI is no longer the focal point of the AI bubble—you can talk about open-source models, Anthropic, or any other element—but without OpenAI, the AI industry would not exist, and trillions of dollars in capital expenditure would evaporate into thin air.

The AI bubble is not born from any real return on investment—whether purely monetary, like revenue or profitability, productivity gains, or anything tangible or measurable. Instead, it's a cult-like psychiatric episode infecting the minds of some of the most powerful and wealthy individuals and institutions. The powerful mythology of a single company has inspired—and has been used to inspire—the greatest capital misallocation in history.

Although this will annoy some, I fully believe the only reason this has lasted so long is that OpenAI hasn't collapsed yet. Its failure would be a watershed moment—the Lehman Brothers of the AI bubble. An event that will define the end of one era and the beginning of another, snapping the afflicted out of their delusion. Without this wake-up call, NVIDIA continues to sell GPUs, the semiconductor industry's coffers keep swelling, and more spending commitments are made.

OpenAI plans to burn through over $852 billion by the end of 2030. It accounts for $748 billion of Microsoft, Amazon, and Oracle's remaining performance obligations, plus at least $70 billion in RPOs (Recovery Point Objectives – likely a typo for compute commitments) from Cerebras, CoreWeave, Nebius, IREN, Lambda, and Nscale (according to Kakashii's data). It also plans to spend an indeterminable tens of billions of dollars on Broadcom's "Jalapeno" chip. It plans to spend $50 billion or more on computing power this year, which I estimate exceeds 50% of global AI computing expenditure (OpenAI accounts for over 50% of all AI computing infrastructure).

OpenAI can afford this spending solely because of its latest funding round (assuming it's fully completed) of $122 billion, of which at least $50 billion has been received, $20 billion of which comes from SoftBank (total $30 billion, with the third tranche due on October 1, 2026). In its latest quarterly earnings, NVIDIA mentioned that it "estimates that an AI research and deployment company contributed a significant share of [its] revenue for the first quarter of fiscal 2027 by purchasing cloud services from its customers," referring naturally to OpenAI.

The AI Bubble Is the OpenAI Bubble—Heading Towards an Inevitable End

OpenAI is the reason everyone is paying attention to AI. In March 2019 (according to JustDario), NVIDIA acquired a company called Mellanox, which produces the high-speed networking technology needed to create AI GPU clusters. Four months later, Microsoft invested $1 billion in OpenAI and began purchasing AI GPUs and building AI infrastructure for it. By March 2020, NVIDIA had shipped its A100 GPU, and by May 2020, Microsoft announced it had built a supercomputer for OpenAI equipped with "over 285,000 CPU cores [and] 10,000 GPUs."

ChatGPT launched in November 2022, perfectly timed for a tech industry that was scraping the bottom of the barrel and teetering on the edge of a prolonged downturn. The IPO market had collapsed, interest rate hikes ended the zero-interest rate era, pandemic-era over-hiring began to conclude with some of the harshest layoffs in industry history, global venture capital shrank after historic overinvestment in 2021, and tech stocks were battered.

For the first time, the tech industry was forced to live within its means—something it has historically been reluctant to do. Big Tech was unpopular with investors and the public. The excesses of the past decade, coupled with growing frustration towards "tech exceptionalism" (the idea that rules governing the rest of the world don't apply to Silicon Valley), tested the patience of regulators and legislators. Moreover, lacking "the next big thing"—a sensational, game-changing product category—it no longer had an excuse for profligate spending or for regularly breaking the unwritten and written rules governing society.

OpenAI's existence legitimized an era of mania and extravagance. Lacking new hyper-growth ideas, hyperscalers pointed to ChatGPT having the "fastest-growing user base ever" and the Microsoft "supercomputer" that built it, telling investors they would be left behind if they didn't invest. Amazon, Meta, and Google announced their own vague "supercomputers" in 2023.

By the end of 2023, NVIDIA had sold 500,000 A100 GPUs, and the sole reason it could do so was ChatGPT's rapid growth. Sam Altman's brief ouster only inflated the AI bubble further—adding a layer of drab palace intrigue to a tech industry lacking imagination and personality—and further cemented Microsoft's role as OpenAI's paternalistic funder, ensuring Altman's return to the helm.

To be clear, by "rapid growth," I mean OpenAI reached 100 million weekly active users by the end of 2023, with monthly revenue around $108 million. Microsoft invested another $10 billion that year, most of which was provided in the form of Microsoft Azure credits.

OpenAI is also the reason Anthropic exists—not only because several of its founders came from OpenAI, but also because Google and Amazon both agreed to provide it a total of $6 billion in 2023 as a means to "compete" with Microsoft's new darling. This gave both companies a justification to spend further hundreds of billions of dollars to "ensure they don't miss out on AI."

When you remove the word "AI" from the equation, it all seems a bit absurd. $16 billion in equity investments, coupled with over $150 billion in capital expenditure by the end of 2023—all basically rationalized because one website became very popular.

And the only reason these two companies could grow is that hyperscalers funded their entire infrastructure.

In Q4 2023, global venture capital fell to its lowest level since Q3 2016, with US startups accounting for $183.6 billion of the total investment for the year. Venture capital itself could not—and would not—truly support OpenAI or Anthropic at the scale of infrastructure they required. Without hyperscalers inflating the valuations of these two companies, there would be no hunger from hyperscalers or those providing debt financing for data centers—this is almost entirely due to OpenAI's success.

If you removed OpenAI from the 2020–2024 period, the AI bubble simply would not have inflated. No other major AI company showed any signs of life—whether peddled by hyperscalers, funded by venture capitalists, or launched by other tech companies.

The only reason any hyperscaler's AI efforts have generated revenue—and apart from OpenAI and Anthropic, the revenue is quite meager!—is that they know they just have to sit there and keep saying "AI is the future" until customers eventually cave and try it… largely because everyone is talking about ChatGPT.

Anthropic wasn't even considered a serious contender until early 2025, and it can keep getting funding only because people want to invest in the next OpenAI. Anthropic's initial funding rounds and infrastructure building were justified solely on the basis of competing with OpenAI.

The $178.5 billion in US data center debt transactions in 2025? Almost entirely justified by OpenAI's growth and its ravenous demand for computing power, because apart from OpenAI (and later Anthropic), nobody else was using massive clusters of tens of thousands of GPUs, and a market for computing power of this scale didn't seem to appear for months or years afterward.

The largest consumers of computing power remain Microsoft (for OpenAI), Google (for Anthropic), Amazon (for OpenAI and Anthropic), CoreWeave (for OpenAI and Anthropic), Meta (imitating other hyperscalers), and Oracle (for OpenAI). Otherwise, there is almost no evidence—and I have looked carefully—suggesting that AI computing demand exceeds a few tens of billions of dollars, which is already generous.

All of this investment—whether in AI startups or data centers—exists solely to fund the next OpenAI, or to become the landlord for the next OpenAI.

The assumption—because no one has ever seriously thought about it—is that since there is one OpenAI, more OpenAIs will blossom. Since there is one major computing customer, a template for future compute-intensive startups has been established… and, again, because no one has ever seriously thought about anything, no one has realized that a second OpenAI hasn't emerged because OpenAI and Anthropic are a financial psychological operation orchestrated by the world's largest software companies.

OpenAI and Anthropic: Hyperscale Psychological Warfare Experts Tailored for Silicon Valley's Monoculture

The brutal truth is, you can't fund an AI lab through venture capital. While OpenAI and Anthropic have raised nearly $300 billion in the past few years, their actual infrastructure costs—the GPUs and data centers powering their services—are entirely funded by hyperscalers. This has likely cost another $250 billion in the process, as Microsoft indicated spending $100 billion on its relationship with OpenAI by early 2026.

Yet, the true cost isn't just financial; it's the experience and industrial knowledge required to execute a massive infrastructure bailout. Apart from Google, Microsoft, and Amazon, no other company has the scale or construction experience for the kind of AI clusters needed by OpenAI (and later Anthropic).

We know this for several reasons. First, because before 2023, almost no companies were building AI computing clusters at the scale required by OpenAI or Anthropic. The closest might have been cryptocurrency mining companies, and it's telling that many new cloud service providers today (most notably CoreWeave) originally operated warehouses full of ASIC chips mining Bitcoin and Ethereum.

Second, because according to conversations with data center industry insiders, the entire Overton window of what constitutes a "large" facility has shifted. Previously, a 50MW data center would be considered a significant (even noteworthy) development. These were exceptions, not the rule; most data centers were much smaller. The only companies with experience building at this scale are mostly the hyperscalers themselves.

By treating OpenAI as a "venture-backed startup," hyperscalers created the illusion that this is the next class of big company, which will, in turn, create the next massive demand center for cloud computing—except that the only reason these companies exist is that the hyperscalers themselves are enabling their existence, funding them with enormous sums, and allowing them to burn money at will.

This is why the idea that OpenAI will continue to grow indefinitely is the central myth of the AI bubble. The existence of one OpenAI allows others—no matter how illogically—to imagine the existence of more OpenAIs, which in turn implies those OpenAIs will need as much computing power as OpenAI does.

Gullible investors who believe this nonsense can rationalize it through countless buy-side analysts or paid media personalities—who talk about "insatiable demand for computing," point to capacity constraints (caused by slow data center construction and OpenAI/Anthropic consuming most of the world's computing power), and rising GPU prices as evidence of enormous real demand, without ever truly thinking deeply.

The biggest trick the hyperscalers play is never backing down. By pouring over a trillion dollars into AI capital expenditure without showing a dollar of profit, they provide justification for anyone to invest in an AI data center, based on the logic that "the world's largest companies can't all be wrong"—even if the reason they're doing it is to expand capacity for OpenAI and Anthropic, two companies they themselves incubated.

Hyperscalers spending this much money on AI infrastructure is fundamentally illogical and insane, and the reason few are willing to say so is that until recently, suggesting it was a waste of money was considered radical—almost entirely because of OpenAI's existence and continued growth. (Note: I realize Anthropic has garnered much attention and grown rapidly in the past year, but it can do this A) because of the OpenAI myth, and B) because it, too, was incubated and allowed to operate at massive losses.)

Whether or not you derive utility from LLMs is irrelevant, as this is not the actual basis for data center investment. While accelerated progress in code generation (which itself is only possible with massive subsidies) may have helped Anthropic grow, the vast majority of data center capital expenditure is chasing the phantom of what AI might become, rather than having any connection to company-wide revenue or economic reality—except, of course, for their own computing expenditures.

This is the underlying greed driving this wasteful, reckless, and destructive era—the belief that there will be another OpenAI, and, as I've said, the chance to become the next OpenAI's landlord. And because the media and analysts rarely have original thoughts, everyone rationalizes (and continues rationalizing) this waste through the same clichés, saying it's "like Uber (it's not!)" or "like Amazon Web Services (between 2003 and 2015, Amazon spent $29.7 billion in capital expenditure, adjusted for inflation)."

Like any great investment bubble, the more money pours in, the stronger the FOMO, the more dollars can be rationalized, and the more complex and twisted the myth becomes—which is why you see prominent venture capitalists claiming AI labs have "inference profit margins of over 90%," a completely unsubstantiated claim that AI enthusiasts have clung to and repeated so often it's been accepted as truth, likely because they are unwilling to face the fact that you can burn through $14,000 worth of tokens on a $200 monthly ChatGPT subscription.

This myth only grows in an environment deliberately starved of good information. We've been stuck in this terrible bubble for four years, and there is still no consensus on the actual cost of large language models, proving an industry-wide effort to suppress this information.

OpenAI, Anthropic, Microsoft, Google, and Amazon have done everything in their power—according to discussions with sources familiar with their infrastructure—to obscure the true underlying costs of their operations, and Silicon Valley, an industry supposedly composed of freethinkers and individuals, has been more than happy to accept any convenient myth that might sustain its dreams.

Ultimately, they have all become useful idiots for the hyperscalers. Their obsessive attachment to OpenAI—and, by extension, Anthropic—looks like a decision made in the name of "democratizing powerful AI," but in reality, every single dollar flows to Microsoft, Google, Amazon, or Oracle. These companies then funnel the money to NVIDIA or Broadcom, which then passes it to TSMC, SK Hynix, Samsung, or Micron.

Investing in an AI startup? They'll pay an AI lab, which then pays a hyperscaler. Investing in an AI infrastructure company? The money flows to NVIDIA, then upstream to semiconductor companies. Ultimately, whether they die or get acquired (because none of them will go public), all value falls into the hands of the hyperscalers who created this phantom era and then inflated it into something very dangerous.

Why the AI Bubble Cannot Survive Without OpenAI

Yet the problem is that this industry cannot survive without OpenAI under any circumstances.

When people discuss the possible collapse of OpenAI, they act like pure cowards, either saying "it won't be that bad" or vaguely claiming it's "too big to fail."

If OpenAI—the company with the most funding, the most infrastructure, the most attention, and the most AI talent—collapses, it will likely happen after AI data center debt and venture capital funds are almost completely exhausted.

You see, Goldman Sachs' Jeffrey Papai recently noted that replicating the hundreds of billions of dollars hyperscalers have raised over the past four years would be "very difficult"—$244 billion in 2026 alone, if you include NVIDIA and SpaceX—which is a problem because, as of Q3 2026, they can