Chapter 1: What are the main concerns about the AI industry's profitability?
Will America recover its political decency after Trump leaves office? I think the bigger concern I have than Trump's staying power is, let's say he's cratering. He has had an effect on the civic mind that is not going to go away. I'm Preet Bharara, and this week, George Packer of The Atlantic joins me to discuss Trump's lasting effect on the American mind. The episode is out now.
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Today's number two. That's the number of times Sir David Attenborough has been knighted for his services to British television and conservation. It appears that after Brexit, the UK has run out of people tonight.
Welcome to Profit View Markets.
I'm Ed Elson. It is May 14th. Let's check in on yesterday's market vitals. The major indices were mixed as investors digested new inflation data from the producer price index. Tech stocks drove the S&P and the Nasdaq to new records while the Dow fell.
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Chapter 2: How does Ed Zittrain view the current state of AI startups?
We'll talk about that inflation in a moment. Inflation concerns also pushed the yield on 10-year treasuries higher. And on Kalshi, the odds of a rate hike this year have steadily climbed to 31%. Meanwhile, Apple stock closed at a record high as CEO Tim Cook joined President Trump, as well as several other big tech leaders for a summit in China. We will be discussing that shortly as well.
Okay, what else is happening? Big tech is on track to spend $725 billion on AI in 2026, and it shows no signs of slowing. Yesterday, reports surfaced that Anthropic is in talks to raise $30 billion at a valuation north of $900 billion. And SoftBank posted a $46 billion gain for the year, fueled by the soaring value of its stake in OpenAI. The markets are currently rewarding the AI boom.
The NASDAQ is up 27%. Since its March 30th low, much of the gain comes from the AI trade, with chip stocks recording their best monthly performance in decades. But not everyone is buying it. Big tech's free cash flow has been shrinking as AI capex balloons, and some investors are asking when, if ever, the spending will generate a return. So...
Chapter 3: What insights does Ed Zittrain provide on AI funding and investment?
We wanted to check in with one of AI's fiercest skeptics and critics and ask, what could the market be missing? So joining us to talk about the state of AI and perhaps some of the stuff that people are not paying enough attention to, we are speaking with Ed Zittrain, author of the Where's Your Ed At newsletter, great name, and the Better Offline podcast. Ed, thank you for joining me on the show.
Our producer Claire mentioned this to you offline, but... I will say it now. You are probably the most requested guest we've ever had on the show. My audience has been asking over and over again, you have to talk to Ed Zittrain, you have to talk to Ed Zittrain. We're finally here. So thank you for joining me. So I want to start with maybe just a summary of your views.
You have been writing for a long time that you believe that a lot of what we're seeing in AI is fake, misleading, Not what we think it is. If you could just start with a summary of what you believe is really going on in the AI world right now.
So across the board with public stocks, nobody's showing a profit from AI. And for the most part, nobody is showing even the revenue they're making from AI.
Chapter 4: What are the implications of the producer price index data?
When I say revenue, I do not mean profit. Microsoft revealed that a $37 billion ARR run rate for AI, the majority of that comes from open AI 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. 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, 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's – there's tons of data centers being built.
I've seen people saying tens of gigawatts built every year.
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Chapter 5: How does inflation affect the broader economy?
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 I'm going to play a little bit of devil's advocate. I want to couch this by saying a lot of what you're saying I agree with. I agree that the revenue is circular in a lot of ways. I agree with you, your points about the data centers, the fact that they're not coming online and there is a lot of questions on are these data centers even going to get built? Are they even going to work?
Are we even going to allow them to get built through regulation and through policy? I agree with a lot of that. At the same time, though, I do look at the growth of some of the revenues of some of these AI labs. I look at OpenAI.
Chapter 6: What are the expectations for Trump's visit to China?
And to your point, we haven't gotten the financial audit of these companies. These are privately reported, but that's the way private companies work. But OpenAI was $2 billion in ARR in 2023. It's up to $25 billion in ARR today. Anthropix reached $30 billion ARR today. It took Salesforce about 20 years to get that. They've done it in under three years.
I mean, those are dollars that are coming in and companies are trying to adopt AI as much as possible and they're paying money to do it. And I guess the way that I feel about it is we're probably very early to this game. They're doing whatever they can to get this through. They want to adopt AI. But I still find those numbers striking.
And to me, it tells me that something about this is real and meaningful. Maybe there's some BS around as well. But overall, I don't want to write it off.
Chapter 7: What key topics will Trump and Xi Jinping discuss?
What would you make of that?
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. Yeah, coming up on four years since ChatGPT came out. And if you think about what constitutes early, early, it really is investment and innovation. We have had all the king's horses, all the king's men trying to make generative AI into something that generates profit.
Hasn't happened yet. No one has happened it to. 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, ARR, run rate, or whatever they use, numbers. It just doesn't. When you add those all together, it's six or seven billion dollars, maybe more. I think Anthropic is counting revenue in a way that is different.
Chapter 8: How do tariffs and trade relations impact inflation?
fundamentally different to how most companies count it. My theory is that when, so 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. 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 in 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 to 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 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.
So some really interesting points in there. I would still disagree with your point that it isn't early. I mean, when we're talking about technologies of this size, I still think four years is early, and to the point about profitability, like, you know, you look back to the internet... It took a long time for the internet to get running.
Amazon took nine years before it was consistently profitable. And eventually, I mean, you can take decades before your business model works properly. And we have seen that with companies in the past.
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