The AI Industry Is Losing
We recorded 21 claims from this post. 7 were checked against evidence. 14 can’t be checked. 16 more are held. Read the post at its source.
Claims from this post (21)
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.
Assessment: UnresolvedSaid
Forecast
“Those millions of H100 and B200 and B300 GPUs are not going to usher in a digital God, they are not going to create recursive self-improvement, they are not going to be the fulcrum to adding $600 billion or more in brand new revenue to current services”
Our reading: The current GPU buildout will not produce a 'digital God', recursive self-improvement, or $600 billion+ in new revenue for current services.
No deadline stated Evidence as of
Limitation: The research is a preprint.
Assessment: UnresolvedSaid
Observation
“Anthropic and OpenAI have raised a little under $300 billion combined since 2019, but I estimate their true cost is at least $500 billion given hyperscaler capex investments that were necessary for them to exist, and that’s before you consider the $340 billion or more that Oracle is spending to build out the 7.1GW of “Stargate” data centers for OpenAI.”
Our reading: Anthropic and OpenAI have raised a little under $300 billion combined since 2019, but he estimates their true cost is at least $500 billion once the hyperscaler capex needed for them to exist is counted, before Oracle's $340 billion-plus Stargate buildout for OpenAI.
No horizon Evidence as of
Limitation: The funding clause and cost estimate remain separately unverified.
Assessment: ContradictedSaid
Observation
“Outside of OpenAI, Microsoft may as well not have an AI business.”
Our reading: Excluding OpenAI, Microsoft has essentially no meaningful AI business.
No horizon Evidence as of
Limitation: The result depends on the customer-based reading of outside of OpenAI.
Assessment: Can’t be checkedSaid
Observation
“meaning that, at least in that quarter, OpenAI likely represented around 70% of Microsoft’s AI revenue, and I’d be surprised if that dramatically changed in the year that followed, given that OpenAI’s inference spend was $3.648 billion in Q1FY26.”
Our reading: At least in Q3FY25, OpenAI likely represented around 70% of Microsoft's AI revenue, and he would be surprised if that changed dramatically in the following year.
No horizon
Scope: at least in Q3FY25
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“There is simply no logical or rational reason to invest any further capex in AI, outside of the mistaken belief that OpenAI or Anthropic could actually afford to pay without Google, Amazon, or Microsoft handing it to them.”
Our reading: There is no rational reason for further AI capex, since OpenAI and Anthropic can't pay without hyperscaler money.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“The current capital expenditures have, outside of the creation of OpenAI and Anthropic, been a near-complete waste. Microsoft 365 Copilot sucks. GitHub Copilot sucks. Google AI Overviews suck.”
Our reading: Apart from creating OpenAI and Anthropic, current AI capex has been a near-complete waste, and Microsoft 365 Copilot, GitHub Copilot and Google AI Overviews suck.
No horizon
Qualifier: outside of the creation of OpenAI and Anthropic
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Amazon Rufus sucks, and Amazon should be investigated by the SEC for suggesting it drove $10 billion in “annualized revenue” in Q3 2025, because it most assuredly did not.”
Our reading: The SEC should investigate Amazon for claiming Rufus drove $10B annualized revenue in Q3 2025, which it did not.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“I refuse to buy into the premise that LLMs’ ability to generate code or replicate open source software is proof that these things will become a powerful, autonomous tool in the future”
Our reading: He refuses to accept that LLMs' ability to generate code or replicate open source software is proof that they will become powerful, autonomous tools in the future.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“This report is industry marketing framed as research, but uses deliberately positive framing and questionable data sources.”
Our reading: Exponential View's AI revenue report is industry marketing framed as research that uses deliberately positive framing and questionable data sources.
No horizon
Assessment: Can’t be checkedSaid
Causal claim
“Instead, Exponential View says that AI is “real, big & fast” through a Pee Wee’s Playhouse of undefined models, datasets and alleged “quality grades” that helps feed a dangerous bubble further, and likely cons retail investors into further terrible decisions.”
Our reading: Exponential View's report feeds a dangerous AI bubble and likely misleads retail investors.
No horizon
Assessment: Can’t be checkedSaid
Observation
“They’re also tools intentionally built to produce engagement, and to make you feel you’re productive, even if you’re not.”
Our reading: LLM tools are intentionally built to produce engagement and to make users feel productive, even if they are not.
No horizon
Assessment: UnresolvedSaid
Causal claim
“what we’re witnessing is a widespread mental health epidemic caused by liars like Sam Altman, Dario Amodei, and their wealthy backers lying about the capabilities of AI”
Our reading: Altman, Amodei and backers lying about AI capabilities have caused a widespread mental health epidemic among tech workers.
No horizon Evidence as of
Limitation: Burnout, cognitive fatigue, and diagnosed mental illness are different measures.
Assessment: Can’t be checkedSaid
Observation
“The people who make these agents fantasize about replacing you with them, and want to use your data to do so. They are lying that it is possible, but they want you to be scared so you will use their products more.”
Our reading: The makers of AI agents fantasize about replacing workers with them and want to use workers' data to do so; they are lying that this is possible, and they want workers scared so they will use their products more.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Any “autonomous” tool that requires specific prompting, harnesses, scripts and tooling to make it sometimes work autonomously is conning you.”
Our reading: Any 'autonomous' tool that needs specific prompting, harnesses, scripts and tooling to sometimes work autonomously is conning its users.
No horizon
Assessment: UnresolvedSaid
Forecast
“As if I haven’t made it clear enough, the AI industry is losing. Their plans are not working, their products are not doing the things that they’ve promised, and though they intend to exhaust every available source of capital, they aren’t going to have enough money to do this forever.”
Our reading: The AI industry's plans and products are failing and it will run out of capital to keep going indefinitely.
No deadline stated Evidence as of
Limitation: The industry and its prevailing strategy are not precisely defined.
Assessment: Can’t be checkedSaid
Observation
“And no, AI is not “too big to fail.””
Our reading: The AI industry is not too big to fail.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“Even if GLM 5.2 is truly nearly as good as Opus 4.8, it did so by copying its outputs, which means that these models will likely only get as good as long as the foundation model companies keep training, which will only be possible if they can keep raising funding, which will become difficult if open source models eat their lunch in any meaningful way.”
Our reading: Distilled open models like GLM 5.2 will likely improve only while frontier labs keep training, which depends on fundraising that open-source competition would undermine.
No horizon
Only if: if open source models meaningfully eat frontier labs' lunch, fundraising becomes difficult
Assessment: Can’t be checkedSaid
Rhetoric
“Considering that Mr. Altman can’t even con a bunch of bankers who were dumb enough to believe that SpaceX could 300x its AI revenue by 2030, it’s clear that the jig is up.”
Our reading: Since Altman cannot even win over bankers who believed SpaceX could grow its AI revenue 300-fold by 2030, it is clear the jig is up for OpenAI.
No horizon
Assessment: UnresolvedSaid
Observation
“Anthropic is a large language model company that loses billions of dollars that has subsidized accounts that allow users to burn $8,000 a month in tokens for $200.”
Our reading: Anthropic loses billions and subsidizes accounts letting users consume $8,000/month of tokens for $200.
No horizon Evidence as of
Limitation: Financial losses and subscription economics require separate measurements.
Assessment: Can’t be checkedSaid
Observation
“about the “cost of intelligence going down” (when it’s actually going up)”
Our reading: The cost of AI 'intelligence' is going up, not down.
No horizon
Assessment: UnresolvedSaid
Observation
“Anthropic and OpenAI have $1.1 trillion in compute commitments that are contingent on their continued growth, at a time when their customers are protesting their costs, at a time when the market is clearly saying “you are not worth a trillion dollars.””
Our reading: Anthropic and OpenAI have $1.1 trillion in compute commitments that depend on their continued growth, while their customers protest costs and the market is clearly saying they are not worth a trillion dollars.
No horizon Evidence as of
Limitation: Older contract announcements do not establish June outstanding balances.
Held from this post (16)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The record does not meet the current rules. Our reading, not assessed: The only real outcome of all this capex appears to be propping up deeply unprofitable Anthropic and OpenAI and getting a small fraction back as revenue made possible only by hundreds of billions of dollars of venture capital subsidies.
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: Big tech's AI products are near-universally loathed and barely generate any revenue, and even the modestly successful GitHub Copilot (about $1.08 billion annualized at the end of last year) succeeded only because users' compute was heavily subsidized.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: There is no demand for these data centers being built, there never has been, and there never will be.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews reached different assessments. Our reading, not assessed: He expects that when the current AI era ends there will be financial carnage and chaos that could easily have been avoided.
- The two reviews read the claim differently
- The two reviews read the claim differently
- The two reviews read the claim differently