AI Skeptic: This Business Makes No Sense

I think that this problem is across the industry. I think basically every AI startup is unprofitable at its core and there is nothing that's going to shift these economics in their favor. There is no sign that inference is becoming cheaper. There is no sign that anyone has any plan to do so, and neither Anthropic nor OpenAI seem particularly concerned with bringing those costs down. These margins do not make sense. These costs don't make sense. I don't see how you pick up the pieces here. I don't see it at all.

Thanks for having me.

Across the board with public stocks, nobody is showing a profit from AI. And for the most part, nobody is showing even the revenue they're making from AI. And when I say revenue, I do not mean profit. Microsoft revealed a $37 billion ARR run rate for AI. The majority of that comes from OpenAI feeding it money from, well, OpenAI's venture capital funders and probably leftover Azure tokens from the $13 billion in funding. Anthropic similarly is funded entirely with venture capital, and their connected counterparties are seeing massive boosts in their remaining performance obligations. So their revenue backlog is mostly from Anthropic and OpenAI. In fact, between Microsoft, Google and Amazon, $748 billion of their upcoming revenue — over half of it — comes from two companies either buying compute or, in Google's case, Anthropic buying TPUs from Google to rent back from Google. The whole thing is very circular, and really outside of OpenAI and Anthropic there's not really any sign that there's a real revenue stream here. I have serious questions about the way they count revenue, but as private companies it's hard to pierce. There's also the other real problem. Big tech is there between Meta, Google, Amazon and Microsoft — over $800 billion of capex. I don't think data centers are being built at anywhere near the rates that people think. I have on good authority that one of the major hyperscalers only has around one and a half gigawatts of actual IT capacity despite hundreds of billions of dollars of capex, and data centers are just not getting built — 18 to 24 months minimum. People see the AI boom as something that's happened, as in something that there's tons of data centers being built. I've seen people saying tens of gigawatts built every year. It's nonsense. I think there may only be a gigawatt or two built every year. The compute constraints people are facing are not a result of incredible demand, but a lack of actual data center capacity coming online. We are yet to get to the real monstrosity that this has created. And when it pops, it's going to be very bad for everyone involved.

So, let's start with that statement about being early. We're not early. If we do it by time, it's been four years — coming up on four years since ChatGPT came out. And if you think about what constitutes early, it really is investment and innovation. We have had all the king's horses and all the king's men trying to make generative AI into something that generates profit. Hasn't happened yet. No one has managed it. I also have serious questions about how Anthropic is doing revenue. Krishna Rao, their CFO, in the Department of War lawsuit, actually said in an affidavit on March 9th, 2026, that they had made $5 billion in lifetime revenue. That does not match up with any of the reported previous annual recurring revenue or ARR run rate or whatever they use for numbers. It just doesn't. When you add those all together, it's 6 or 7 billion, maybe more. I think Anthropic is counting revenue in a way that is fundamentally different to how most companies count it. My theory is that with the largest clients they have, clients don't pay in arrears — smaller ones do, but the largest don't. They buy massive amounts of tokens in advance. I think Anthropic, for example, if someone is going to do $50 million worth of tokens and it lasts over six months, they're going to take that money up front. They're going to say, 'Wow, in that month,' because all ARR is is month times 12 or 13 depending on how they do it. So I think both OpenAI and Anthropic are inflating their numbers. I actually think one or both of them is misleading investors, but that's something we'll find out about in the future. I also fundamentally just don't see evidence outside of these two companies that anything's happening. The largest company within this space was Cursor, and now they've been kind of sort of not really bought by Elon Musk. They also — if there was so much demand, by the way, why did Elon Musk give up an entire data center to Anthropic? There are enough signals here that suggest there is a fundamental weakness and no real major business model here. We still don't know Anthropic's true burn rate. But we do know that if all of the commitments from Amazon and Google come together on this $50 billion round — it's 30, it's 50, it changes every day, it seems — they'll have raised $108 billion in the last year. What's going on? Where is that money going? And to whom is it going other than Google, Microsoft, and Amazon? So, one of my simplest points as well is: other than Anthropic and OpenAI, why are there no other AI winners? Why is everyone piddling around 100 to 300 million ARR, which is 10, 20, 30 million a month? It's not actually that much for what is meant to be an industry-changing thingamajig. And there are signs that the economics don't work. The biggest being that Microsoft, GitHub Copilot — by the way, one of the largest clients of Anthropic — is moving to token-based billing on June 1st, 2026. They have been subsidizing tokens for their users to the tune of — I saw one person who spent $5,000 worth of API calls on a $39 a month program. I think that this problem is across the industry. I think basically every AI startup is unprofitable at its core and there is nothing that's going to shift these economics in their favor. There is no sign that inference is becoming cheaper. There is no sign that anyone has any plan to do so. And neither Anthropic nor OpenAI seem particularly concerned with bringing those costs down.

This one specifically, just because Amazon Web Services was profitable in nine years. The total capex between 2002 and 2017 was $52 billion, and that was for all of Amazon, not just AWS, between 2002 and 2017. If we're talking about the dot-com bubble, the dot-com bubble's economics were actually fundamentally different. Fiber was much cheaper and also had more uses, more obvious uses. Let me put it really simply. I know what you're getting at, but to put it really simply...

But Amazon was also not just a cloud compute company. It basically went from a bookstore to a store to a cloud computing company to the side.

Yeah, I think those points I agree with, and I think it's something that needs to be talked about more, and I'm glad that you're bringing this up. My point, just to be clear about what my point was: the idea of these business models not working yet, to me, doesn't seem to be a huge problem. But when you look at the amount that they are spending, and when you look at just the sheer size of the spending, to a lot of your points, I do wonder if when we extrapolate this, you know, 10, 15, 20 years down the line, whether it will look like the dot-com boom and whether these internet companies will be comparable. And I am increasingly thinking they won't. And something that I've been thinking — and this is something that Sam Altman has said — is I wonder if it looks like utility services. I mean, Sam Altman has said OpenAI is going to be a utility company, and we've seen this with utility companies before where, you know, having a regular market doesn't really work because the economics don't make sense, and so you basically just have to have one company that's operating for a specific area. And so I guess what I'm getting at is the business model. I don't write it off entirely, but it does seem that it will have to be fundamentally different from other businesses. And I wonder if you agree with that, or if you think that they just won't work at all and they will therefore implode.

So if we think about the dot-com comparison and we break down the kind of businesses we had with the dot-com bubble, it was really two bubbles. It was the telecommunications bubble and the software bubble. The software bubble and the e-commerce bubble — the pets.coms, the Kozmos and such. Their economics didn't make sense because they didn't make them make sense. They just were — pets.com, I think, was spending like 250 bucks a customer or something insane like that. But it was being invested, and it involved the movement of physical goods, and those are margins you can bring down, as Amazon did, build their own logistics network. And also, Chewy.com is basically pets.com. Kozmo now exists as Instacart. Like, there are — Webvan, pardon me, I think is Instacart now. Not the literal same company, the same business model. In the AI bubble, you really have three different kinds of companies. You have AI labs, you have AI startups, so wrappers, and then you have infrastructure. Infrastructure within AI — data centers, GPUs — is one of the most commoditized businesses of all time. It's a horrible business, but it's also — there's really no difference between a CoreWeave and a Nebius and an Iron or a Lambda. They're all backed by Nvidia. They're all feeding money from Jensen Huang to Jensen Huang. The point is that those companies do not have really — there is no changing this business model. Even if I don't believe this, there was a chip in the future that was theoretically profitable. Blackwell isn't. Vera Rubin won't be. Hopper wasn't. None of the Nvidia GPUs are clearly profitable for operators. Otherwise, we would have someone making a profit within the telecoms and...

Exactly. More money than they have spent.

Not Nvidia. Very profitable for Nvidia.

Nvidia, memory stocks, they're all profitable because they're pre-selling a bunch of capacity, storage and servers and all that. But a vast majority — like the dot-com bubble, which was also much smaller than this as far as actual money being invested. Venture capital was — I think one round from Anthropic this year is bigger than all the venture capital that went in during the dot-com bubble. It's insane, and that's — I mean, even with inflation, it's still pretty close. AI wrapper startups are all dying, and also the way that they are raising and dumping money is not something that's creating any useful residue. Harvey, for example, I think they've raised $900 million and they make 200, 300 million ARR. Those are stinky margins. But the point is, it's not like Harvey is buying a bunch of stuff and doing proprietary data or buying servers like happened a lot during the dot-com bubble, because AWS didn't exist, so people were buying their own servers. There's no useful residue. All of that money is being dumped directly into OpenAI and Anthropic. Anthropic and OpenAI also do not have assets. They don't have capex. They have their models. They have their model weights, which, by the way, Microsoft has full and complete access to OpenAI's model weights. And so they don't have their — they have talent, I guess, they have research, but they don't really have — they just have their models. That's the only thing. Those companies die. There's not really any useful residue to pick up. Perhaps someone could buy the assets of Anthropic, even though Amazon and Google will take them, but there's not really a thing to recover. And then you get to the CoreWeaves, Nebiuses, Irons of the world. And again, you've got a bunch of old GPUs probably in data centers that haven't been built yet, which means that there's nothing really to pick up other than you pick up a cheap office chair or a cheap server. Back in the dot-com bubble, you could do something with that. What are you going to do with a GPU? Especially when it's insanely expensive to run. I have a source at Oracle that told me it's about $6.30 an hour of COGS to run a B300, pardon me, GPU from Nvidia. These margins do not make sense. These costs don't make sense. I don't see how you pick up the pieces here. I don't see it at all. And indeed, I don't think there's much useful infrastructure left over. And this is the big argument that people are making, because people are saying, 'We're in a bubble now. We're in a bubble now.' But don't worry, after the dot-com bubble, people picked up stuff for cheap. What stuff? We already have piles of unused GPUs. Super Micro had a multi-billion dollar order cancelled from Oracle. They have at least a billion dollars of B200 chips that no one wants to buy. We've already got the FOW inventory. Nothing's happening. I'm sure someone will do something, but nothing's going to be cheaper in 10 years. Things were like you could pick up the servers and you could actually put them in — like, there's ways that you could make that useful from the dot-com bubble. It's not really the story here.

I think there is. I have very specifically said there is value in coding. I've said that for years. That's classic misinformation there. Not from you. It's spread all around by certain...