← Deep Questions with Cal Newport
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- [00:00]
A
AI news comes at you fast. Each article feels more breathless and more terrifying than the last. But before you have a chance to see how any particular story turns out, there's 10 more in its place. I think this speed and lack of accountability can create a sense of overwhelming disruption and change that can really be pretty disquieting. Well, it's Thursday, which means it's time for an AI Reality check episode. So I thought this would be a great opportunity to try to slow down this news onslaught and get a better sense of what has actually been happening in the AI space recently. All right, here's my plan. I've invited the AI commentator, Ed Zitron to join me, and we're going to look at three of the biggest stories about AI to land in 2026 so far, including one in which Ed is actually very much involved. And what we're going to do is for each of these stories, we're going to take a closer look on what actually happened and how things have since turned out. Our goal by the end of the episode is to answer a simple but critical question. Has 2026 been a good or bad year for AI so far? And we have a lot to cover, so let's get right into it. As always, I'm Cal Newport, and this is Deep Questions the Show for people seeking depth in a distracted world. And we'll get started right after the music. All right, Ed, well, it's been three or four months since you were last on the show, and there's been some big AI news since then. So I wanted to have you on to go through some of the big stories that have happened since January. And because you're a commentator who is, maybe I should say this, less impressible than the average AI commentator, we. I figured your point of view is good for my Reality Check audience. We're going to try to end this, this discussion by voting whether or not 2026 has been good or bad for AI so far. But what's your pre vote? Where do you think? Based on what you know, you're going to end up here?
- [02:10]
B
Probably not a good time for them. It's just every time we talk, it's like there is very big news and everyone's like, oh, look at, we've got a new number. It's even higher than usual. But. But the actual underlying economics and infrastructural layer or even just the service performance is worse and it's very strange.
- [02:28]
A
Well, this is part of the reason why I like doing these reviews with you is often the story will be big. Everyone will get worried about it. People will call people like you and I for quotes, and then everything moves on and there's no follow up. And I think it's useful for calibrating how to react to the news story you're hearing now to occasionally go back and say, hey, what happened with that story? That had me worked up a couple months ago. Which brings us to a great place to start, because what was the first big story of 2026? I think arguably it would be Open claw, which I believe became generally available to the public later in January. Now I've broken this up into two sub stories. I want to start with the easily dismissible one just because it's fun, and then get to the more serious one. I'm going to read you a quote, then we'll get into it. So the easily dismissible but fun aspect of this story is when someone opened books book a social network that was configured so that it is easy, if you're writing an OpenClaw agent, to post on it. So they add hooks into it. So it was easy for your OpenClaw agents to post and read things from the social network for about four days. Everybody went crazy about Mult Book. I'm just gonna read you a quick quote from your favorite publication, Axios, from the end of January. Imagine waking up to discover that the AI agent you built has acquired a voice and is calling you to chat while comparing notes with other agents on their own private social network. It's not science fiction. It's happening right now and it's freaking out some of the smartest names in AI. Well, you're a smart name in AI, Zed. So are you still freaked out about Mult Book?
- [04:04]
B
No. The moment I saw it, I'm like a. This is just LLMs. This is just LLMs doing what they think a social network looks like. As in when I shouldn't have even said the word think, spitting out what the model would say is likely to be a social network post. And then the second thought I had was, this is fake. This is what? Well, 100%. There are regular people just using their open clause to post on here. These don't read that. They didn't read like LLMs in some cases. Some. Some cases they did, but some of them were just like, I saw someone post the slur within one hour. I'm like, okay, this is just a regular person using the. Regular is probably the wrong word. A person is using this as a means of posting. And it's funny when you say like the smartest people as well. Because I think that that term no longer has any value because that's like Andre Karl Pathe, who is. It's just the term smart at this point. Just. Does that just mean they got good grades at school? Because if that's the case, we are completely screwed. Like, if we think only the people who got good grades are smart, then I don't know what to say for the world. Because the people that fell for Malt Book was. That was insane. They were like, oh, it's AGI. It's as if they forgot how large language models worked or never learned in the first place.
- [05:21]
A
Well, I don't think they understood what OpenClaw was or what Molt Book was or what any of this was, other than it involved lobsters.
- [05:29]
B
Yeah. And they heard Agent. Agent. It's autonomous. Bought a Mac mini.
- [05:34]
A
I did a little digging here. Axios original. They moderated the headline, but I thought it was worth just to. Because I think we memory hold a lot of this coverage. But the original headline was we're in the Singularity. Colon. New AI platform skips to humans entirely. But it did the trick where you put the quotation marks around the first part. So technically you are not declaring that to be the case. You are quoting someone. This one got fully memory hold, right? No one talks about Molt Book. I mean, I think I covered it on my show at the time. I said, yes. People are just telling their LLMs. The post. LLMs write stories. They finish the stories you tell them to write. There's actually good research. This came up in my doctoral seminar. I'm teaching on super intelligence Intelligence, which is great because it's like 10 doctoral students who just do AI research and I'm learning a ton from them. And they know the literature even better than I do. And they're saying there's really good research out there. That whenever you do any prompting of an LLM, if anything in your prompt in any way indicates that you're prompting an AI, almost always it goes into sci Fi mode. Right. So the LLM will if you. So you can ask the same question. And if you say you are a. Whatever, you are a journalist, please answer this question. It'll give one answer. And if you say, well, you're an AI, so how do you think? Blah, blah, blah. It always will go towards dystopian themes of AI coming alive. And like, that's. It's so. It's very easy to prime. And I think a lot of that was going with openclaw people would say, please go post on this social network. And they just wrote AI type stories.
- [07:07]
B
Right.
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A
But was covered very credulously, I would say, which is the key point.
- [07:14]
B
Pretty much par for the course. I mean, I still. I don't know if we want to wait until the second part of this, but it isn't. The Open Claw thing is one of the most insane things I've seen in the tech industry. May even be crazier than the overall LLM. Boom.
- [07:27]
A
Well, go on with it because let's get into the second part. I have some quotes, but let's. Well, let me read you the quote and then let's get into it.
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B
Yeah, read the quote.
- [07:33]
A
This is a like a representative person talking about OpenClaw earlier, like early February, late January, for the past week or. And this tone, this is called AI Enthusiast. This is like such a known tone. This can sound very familiar. For the past week or so, I've been working with a digital assistant that knows my name, my preferences for my morning routine, how I like to use Notion and Todoist, but which also knows how to control Spotify and my Sonos speaker, my Philips Hue Lights as well as my Gmail. It runs on anthropic cloud opus 4.5 model, but I can chat with it using Telegram. I called the assistant Navi, inspired by the fairy companion of Arcania of Time,
- [08:13]
B
not the Ocarina of Time, the game.
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A
Yeah, all right. Nerd.
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B
Zelda.
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A
Oh, okay, I get you.
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B
No, no, no, it's just like. It's like a really weird choice.
- [08:23]
A
Well, he makes a point. It's not the James Cameron movie based.
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B
There we go. Okay.
- [08:28]
A
And Navi can even receive audio messages from me and respond with other audio messages generated with the latest 11 labs text to speech model. Oh, did I mention that Navi can improve itself features? And then it's running on my own M4Mac mini server. And also I just got fired because I just spent 100 hours setting up Navi. Instead of doing my job well, I
- [08:45]
B
added myself and I now can't pay my rent because I spent $4,000 a month on API calls.
- [08:51]
A
Yeah, like. Oh, that. That's the other problem. Okay, so that's Open Claw. Right. So you could. My understanding is it's a library. It's a Python library.
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B
Yeah.
- [09:01]
A
Which makes it easy to write your own agent. An agent being code that calls an LLM and then uses the response from the LLM to help drive its movement. So you can say, hey, LLM, what should I do? And then it does it openclaw made it easy for people to write their own. So people all around the world began destroying their computers and leaking all this information. It's actually hard to write.
- [09:23]
B
But here's the thing. Even that term gives it too much credit. It just does what LLMs do. Like, it's just, oh, I had it. I read this thing on one of the Mac websites where it was like, oh, yeah, I had it build a website and it's just the most generic looking vibe code slop ever. Oh, I had it transcribe my. My voice notes like, yes. So, okay, it's doing what LLMs do. Oh, and it's able to write stories. So LLMs. And that's. This is the weirdest thing. The thing that really confused me is on top of the credulous media coverage and pretty much everyone who covered this should be ashamed of themselves. I think most people did the worst job possible in the sense that I read most open claw coverage because I was trying to work out what it did. God's on God's honest truth. I was like, what is this? But you read like the Atlantic. And it was like, I was the Atlantic or cnbc. They were like, this is another chat GPT moment quoting Jensen Huang because of
- [10:20]
A
the fast adoption that a lot of people tried it. And then they looked at that chart and said, well, this is a big deal.
- [10:25]
B
But the thing is, it's like fast adoption. It's like slop. It's Slop commits on GitHub and also Mac Minis selling out in the greater Bay Area. But the thing that was crazier to me, other than all the credulous coverage, was Nvidia's GTC 20, 26, $4 trillion or so market cap company, right?
- [10:45]
A
That's their conference. GTC is the big conference.
- [10:47]
B
Yeah, yeah, yeah. And you got a 3D AI generated picture of Jensen Huang, the CEO of Nvidia with. With lobster claws. They released this thing called Nemo Claw. And they're like, ah, this is the chat GPT moment. This is the agentic future. And it's like, what are you talking about, mate? Did you just get in a car accident? Do you have a concussion? You just steered your company like a year ago. GTC was like, Jensen, Jensen going out with full swagger, being like, yeah, we've got Vera Rubin. We're gonna do this 10x more efficient shooting guns in the air signing. He signed a woman's boob last year. This year he's like, yeah, we've got Nemo Claw. Got Nemo Claw? You want to try Nemo Claw? Ah, you like that, did you? Jingling the keys again? Do you like Nemo Claw? What? But please spend125,000 on a GPU. You need to buy Vera Ruben. Even though we don't have anywhere to put it as we'll get to. But it's. It's just so weird because when you actually get down to it, it's the classic LLM story. It's like, okay, what are you talking about? It's a new agentic interface for managing programs. It's an LLM. It's an LLM. Is it a chatbot connected to an API? Yeah. So the Donnie Darko meme.
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A
What's the dying.
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B
The Donnie Darko moon. It's like, I forget what the line is in the movie, but it's like, oh, I've started. I've managed to create a new agentic workflow. Is it just an LLM connected to an API? Yeah, yeah. Because that's every story, every story I've read. It's just. Do you have two LLMs bonking each other's heads? Is that what's happening? Gray? Okay, I'm very impressed. We need to have the largest company on the stock market do something about this pronto. It's hysterical.
- [12:34]
A
I think that's an important point because I do think when the average person hears about things like openclaw or different agents, they're often thinking there's a new artificial intelligence technology that there's a new. We built. Openclaw is a new digital brain that can improve itself, and it's learned how to do things that prior models haven't. And I think what people don't understand is that openclaw is a Python library. It's a Python library that makes it easier to write a Python program that can make calls to LLMs, and you can aim it at whatever LLM you want. The LLM is somehow like that is the brain. But there's no new LLM for openclaw. It's a library that makes it easy for the average person to say, I'm going to write my own agent. It turns out agents are hard to write, right? Because LLMs, they write plausible stories, but as we've learned, they're not often really good, carefully checked plans for doing things. And so it causes a lot of problems if you say, hey, LLM, give me a plan for doing stuff with my personal data. And then you have a program that just automatically implements that. Turns out sometimes bad things happen. But there were two. Here's my two useful things. I'm going to say there's two useful things about. Two useful things about openclaw. One, because a lot of people began experimenting with building their own OpenClaw agents, one of the quick things they discovered is, oh, the big frontier LLMs are expensive. And they were racking up thousands of dollars of token costs, the API calls to Claude or to GPT. And so it got a lot of the real booster tech enthusiast types to start looking at much smaller, much cheaper models because they just literally couldn't afford it. This is why I think OpenAI bought open claud.
- [14:19]
B
Well, there's an important detail though.
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A
Okay, please.
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B
So it's important to know where this was in history. So Open Claw came out January. Ish.
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A
Yes.
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B
Now you used to be able to, during this period connect your Anthropic Claude max account. A 200 buck a mat buck a month account. You used to be able to connect it to OpenClaw. So you weren't paying API calls, you were just using Anthropic.
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A
That's unlimited. You pay 200. And it was supposed to be.
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B
You have a rate limit, but there's. You can use it as much up to that rate limit and you can spend like thousands of dollars, dollars of API calls. And that's been proven. There's a coder called Shelik who did a study on it.
- [14:56]
A
This is when you quote a number often about how much it's actually costing per token versus what they're charging. This is where partially that number is coming from.
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B
Yes, yes. So it works out to like somewhere between 8 and 13 and 13 $50. Weird way of saying that per dollar of subscription. So you're able to burn like $2,700 on the anthropic subscription or 200.
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A
You're paying 200. It's costing them 2700.
- [15:20]
B
Yes, exactly. Sorry. Kind of clutchy explanation. So Anthropic let this happen. So the reason that Claude the Open Claw got so big, Anthropic sued them because they were called like Claude Bot at first Claw C L A W. But nevertheless Anthropic allowed this to happen. Then February 12, they raised the $30 billion round. Couple weeks later, Open clause cut off the Aristocrats. It's just it that Anthropic is such an unethical company, they should have never let it happen to begin with. But one of the reasons that openclaw got so big was both using those cheaper models but also using those Max subscriptions. And so OpenAI buying OpenClaw was so funny. Just like OpenAI is just meta, it's meta plus Enron. And it's so funny watching them with. Why would you buy this? What possible reason? Oh, we can build agents with it. What do you mean?
- [16:16]
A
No, why can't.
- [16:18]
B
Why? Why?
- [16:19]
A
They have much better frameworks for. Well, I have two explanations. Let's get back to you. Tell me which one you think is more likely. So this is maybe giving too much savviness credit to them. The savviness is. I think it was a real problem for a lot of enthusiasts to discover. Oh, wait a second. If we use really cheap open weight models, open source models, or even just really like 3 billion parameter models we can run on our own machine, we get pretty similar results. Like actually we don't need a 1 to 10 trillion parameter super frontier model to read my emails and to add appointments onto my calendar. I think that's really terrifying. If you're a company like Anthropic just taking on 60 billion in investment or your OpenAI, we need people to think that these are the big brains and nothing else matters. So the conspiratorial business savvy interpretation would be. OpenAI needs to sort of slow the roll on that or make that tool much more native to its models because they really do not want a generation of AI enthusiasts to say, oh wait a second, I can. Kimmy is like a fraction of the cost that it does. Just as well. The other way of thinking about it, it's like them buying that podcast show recently.
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B
Tppn.
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A
Yeah, there's just like we're just buying things left and right because we have money. We're not quite sure what to do. The sort of.
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B
Yeah, I think, I don't know which ones.
- [17:37]
A
It's probably number two because.
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B
Because they're going to keep running open claw. They've said that already. They're going to keep running it and people are still using open source models. So it's kind of like I just think that they were buying stuff because they thought, crap, we got to do. We don't have an open claw. What if we just bought it? It's rich kid syndrome. Like that's the thing. Like both open AI and anthropic act like rich kids. Because I went to a private school, I'm not proud to say it. I was the dumbest kid in the private school. I did not do well. Bottom of my class every single year. Failed multiple languages, like genuinely, legendarily terrible. I barely scraped through. But I've met a lot of these kids and my parents scraped by to get me there as well. It's good on them. But I met a lot of these kids and what they do is when they don't want to learn something, when they don't want to build knowledge, when they don't want to put something together of their own, they just acquire. There's like, dad, go and buy me that. Daddy, go and go and buy me. Buy me a boat, buy me whatever. And it's OpenAI doesn't know what they're doing other than they have a lot of money so they can spend it. And I think they bought it thinking, wow, this will be a back door into anthropic a little bit. We'll be able to see what anthropic does more because lots of people use this and we can, we can somehow see how Claude is running agentically or they bought it to kill it.
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A
That's what I think.
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B
But the other thing is, is Peter Steinbrenner or whatever he's called, he's still farting around, that guy. I don't know if you've ever read his post, but he is constantly working.
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A
Yeah.
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B
And I would. I don't give him a ton of credit for that because it's like. Feels like a depressed person. But also, I've heard he got hundreds of millions of dollars for it as well. So it's like, if I had that much money, you wouldn't hear from me again. I. I would disappear. Well, no, I'd keep posting. But it, it's strange because it's like, what are you actually working on? And I think he vibe coded a lot of it as well, which is even more terrifying. And there are massive security issues as a result. It's just one. It is like a psychosis unto itself. And what I think get. I know we talk a lot about the media stuff. What I think it is is the media and the AI community is so desperate for a hero. They're so. They. They know. They know in their deep down in their soul that something is wrong, that none of this makes sense. So the moment anything even directionally feels like it proves that they're not wrong. They grab it and they shake it vigorously. They just go like, this has to be it. This is gonna be the thing. And if, if we love this enough, it can be a real boy. And it never is. Like, openclaw is gone. Like, just no one's talking about it anymore.
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A
No one.
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B
No one cares. Searches on Google have gone down.
- [20:23]
A
Yeah, I just Looked for it, it's minimal. I checked this morning. It's minimal coverage. It's been minimal coverage. I mean it's kind of around, but it's become a niche topic. Well, let me tell you my second thing that I think is good about openclaw, right? The second thing is I think it actually points towards what I think is the healthy sustainable future of AI, which is smaller, task specific and much more modular architectures, right. So not built around a single AI entity like an LLM. Bespoke AI systems that do specific things. There's a great. If I want to play poker with AI, there is a great AI system to play poker with. If I want to, you know, if I want to do certain types of digital VFX work, like there's really good AI systems that's like made to do that. I think that's.
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B
But all those LLMs.
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A
No, well, no, they're not. Right? Or because they have LLMs in them. That's why I say modular architecture. I think the future is you have multiple different things, most of which are just hand coded by a person. And maybe you have an LLM in there if there's language involved because it's pretty good at if it needs to speak to someone or interpret it. I point towards the Cicero model as the great example of this, Noah Brown's AI system that plays the board game Diplomacy. And it has an LLM in there, small one for chatting with the other players and then converting what they say into a sort of more technical language that the rest of the system understands. And then it has a planning engine and it has a policy network that can evaluate the different boards. It has multiple other systems that all hook together.
- [21:56]
B
Classic AI shit. Like this is, this is real AI stuff. Like when it's just like, yeah, I made Diplomacy, but this actually just reminded me of something.
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A
But just I want to get to that. But just to bring it close to the point is I think this gave people a taste of that. If you're building. They were like, oh, I want to build my own system to do one thing. Thing. I want to build a system to answer my emails that come in to request for my show, to answer those emails and to put things into a spreadsheet and like, oh, I can write a program to do that and I'll use an LLM to help me. And it can be a small one because that's kind of not the core of it. And suddenly you're exposing people to this idea. I mean, I call this vision Distributed AGI where Like one day you would look around and be like, there's 10,000 bespoke small systems that each do something well. And if you add it all up, oh, that's a lot of things now that computers do as well as people. And it's a very different vision than Opus 5.9 is or whatever it is. Grox 7. Yeah. It's embodied in a robot with predator machine guns and it can just do everything. Anyways. All right, back to your point.
- [23:00]
B
So this just reminded me. So Jack Clark of Anthropic, fascinating character, one of the co founders. He used to write at the Register, one of the single most critical tech publications in the world. His public, his blogs were extremely critical. I've seen him twice pedal out this example which he refers to as like a, an evolution simulator, a predator prey simulator. And he brings it up all the time. And he write, he uses these high fluid in terms. I went and looked this up. It is like a 50 year old idea. He's like, yeah, I used Claude code to build it. Yeah. Because there are hundreds of them online, hundreds of them that it was trained on.
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A
It's just a little simulation program.
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B
It's a little simulation that says, okay, we got bees. And the bees get killed by the bee. The, the bee eating bears. I'm just making up animals already. This is why I can't make one myself. But it's like all of the different creatures and how they interact. He's like, yeah, And I'm able to change things here and here and there. And it's like, yeah, there is a web version of this. It is 20 years old. Yeah. But the way they frame all of these things is like, oh, simulation, like the singularity. It's like, no. And it just, I feel like the AI era is a mass exploitation of ignorance. It's just it that they found something where the media just. They knew. The media, maybe they didn't know this in advance, but the media won't check anything. The media will just think, yeah, it's got a social network. This is AGI. Now every time a 3 gigawatt announcement is made, they go, the 3 gigawatt data center, that's like 3 nuclear power plant, big one. Wow. Even though it's not getting built, which I know we're going to get to, it's just AI as a term, as you well know, is it means so little and so much at the same time that they can basically do anything. And I think combined with the hysteria they are in the situation where literally I think we could have another Sam Bankman Freed situation that we don't know about yet. That an AI company could come out and just go yeah, we've done this. And it's the, I mean kind of mythos is almost that. I know we're not going to get into that but it's. I feel like we are. Maybe there's already a scammer out there, but this is the environment. The exact environment.
- [25:11]
A
Yeah, you could gather a billion dollars easy.
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B
Well, I mean I just saw another one the other day where it's like a company that claims it's doing recursive self learning and they raised half a billion dollars and one of the co founders runs another company called U.com and you know what's crazy? That is not mentioned in the Financial Times's piece. It's just we are like grifters have found their meat. This is so much worse than crypto and NFTs. It's so, so much worse because the fuzziness of AI allows them to have infinite time and infinite money to say well we still haven't worked out that recursive self learning company by the way. Of course they are still thinking theoretical like all of them. Yeah, like world models.
- [25:57]
A
But no, the 50% job loss, it's, it's next month now.
- [26:01]
B
Yeah, that's what that's.
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A
I, I said the wrong month.
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B
It wasn't this one like 8 to 12 months, baby. With a margin of error of maybe 100%.
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A
Banner headline, 50% every time.
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B
Just read the top thing.
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A
Yeah, that reminds me a little bit about my, my oldest plays. I coaches help coaches, little league team, baseball team or whatever. And the pitchers are getting better. They're at the 13U. They play on the full size fields now or whatever. And like the pitchers are better now. So what they learn is if I throw the high fastball into batter swings I'm going to throw some more high fastballs. Like this is clearly. And I kind of feel like this is Dario Amade saying 50% of jobs. He's rolled this out three years in a row now he's like it gets covered every time. I'm going to keep throwing those high fast falls as long as the, the media swinging the proverbial bat.
- [26:47]
B
Yeah, but high fastballs are proven to be difficult to hit as opposed to LLMs which have never been proven to take and take jobs.
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A
Ah, there we go. I like it.
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B
Baseball's way more fun than AI. Just if only we'd have put this money into baseball.
- [27:03]
A
I agree with you there. Yeah, baseball has less constant waves of existential dread being poured upon the entire populace?
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B
No, they just reserve it for, like, Cincinnati and Pittsburgh and Mets fans.
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A
And that's right. You're right. Mets fans are like fans. Mets fans look to AI for a little bit of psychic relief. They're like, oh, this is not. It's not quite as dark as what we're dealing with.
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B
Yeah, this isn't punishing.
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A
Only half the jobs are going away. That's not so bad as an 11 game losing.
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B
Yeah, no. And most Mets fans are like, yeah, I would fire half of them.
- [27:32]
A
Yeah, they should be fired. They should win.
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B
Maybe we should do all of them.
- [27:36]
A
Yeah. I hope Juan Soto's the first one on that list. All right, story number two. I actually, for whatever reason, I didn't cover this one as much. I talked to some sources in the sort of surrounding DC Tech industry. But I want to get your take on this. This is the Anthropic and Department of War story that picked up in February. I'm just going to read a little bit from Dario Amadeh's statement that kind of kicked off this whole thing. So he said Anthropic understands the Department of War, not private companies, makes military decisions. We have never raised objections to particular military operations, nor attempted to limit use of technology in an ad hoc manner. However, in a narrow set of cases, we believe AI can undermine rather than defend democratic values. Some uses are also simply outside of the bounds of what today's technology can safely and reliably do. Two, such cases have never been included in our contract with the Department of War, and we believe they should not be included. And then you list mass domestic surveillance and fully autonomous weapons. So can you first bring us up to speed on what unfolded and has unfolded there and then what is actually happening? Because I find the story, because I haven't looked at it as closely, kind of confusing.
- [28:43]
B
All right, so just before the war in Iran, I think Dario is a savvy con artist, and I think he. I call him. You don't. It's not you saying, it's me saying he's a con artist. So just for some background, Anthropic has been installed with classified access in the US military since June 2024. That's a very important detail. They were used in Venezuela, incursion, whatever you call that, they were used throughout and are still used in the war in Iran. So what happened was Amade said. I forget what the conversation was. I. Maybe he instigated it. It's kind of hard to tell, but Some conversation between him and the US military was we're not going to let you use this for mass surveillance of Americans, nor are we going to let you use it to control autonomous weapons. Now the second one really pissed me off because you, you cannot control anything with LLMs. You can't control. If you control the robot with LLMs, it would barely move because the processing time, even people's like, oh, what about on device? But shut the. You don't know how these work. That's not how this fits.
- [29:49]
A
That threw me off as well. I know enough about AI. Like, why are you talking about LLMs? Why? Because autonomous. I think they mean AI in general.
- [29:57]
B
No, no, they meant autonomous weapons. They 100% meant that. I know because I read every single article and every single statement about this, every single time, like autonomous weapons. And to be clear, Anthropic in their own statement said LLMs are not consistent enough to run autonomous weapons. Correct. Thank you, Dario.
- [30:16]
A
Your false. But also it would make no sense to run a model based on language parsing and generation to steer a missile. So I don't understand that. Okay, but the first one you say was happening though, as far as you can tell, using these tools as part of intelligence gathering. And sure, they probably were involved in the change somewhere.
- [30:35]
B
I mean, were they? But the thing is, I can't confirm whether it is. No one can because anthropic is already. Was already embedded and they attempted to basically renegotiate the contract post hoc. And I'm not siding with the US military here, but they tried to say we're adding these things and they did it mysteriously somehow just before the war in Iran. So what I think the. This is my personal belief. I think the. Like it was a few days beforehand, I think what.
- [31:03]
A
So they're just to clarify what you're about to say. I'm just looking at this now. They're saying mass domestic surveillance of fully autonomous weapons. In that February statement, they're saying, oh, have never been included in our contracts. So I had been given the impression that they were specifically called out in the contracts as we will not do this. But actually what I'm seeing here is it's not like that wasn't discussed at all in the contracts. And Amadeus saying, hey, we never mentioned in the contracts these two things you might use it for, and we want this in the contract. So. Okay, go on. But that's a. I'm only seeing this now that when I'm rereading that. Yeah, it's a little tricky.
- [31:41]
B
Anthropic 100% had visibility into what the US military is doing. So I would not be surprised. I cannot confirm this, whether they time this specifically to time at the war in Iran, because suddenly there was this insidious, awful. Every single person who spoke like this should be ashamed of themselves. I'm disgusted by it. There was this insidious thing of people being like, anthropic is the ethical company. I saw Hashtag, Jisui, Claude, death penalty. I saw Katie goddamn Perry being like, I just bought Claude. And it's like, you just paid a company that was actually part of this war. And people like, well, open AI is now. And then Sam Altman slid in and was like, well, we can do whatever that is. Then Sam Altman claimed that they had actually negotiated something that didn't allow the things that Anthropic wanted. Then it turned out that Emil Michael from what's His Butt from Emil Michael from the US Military said, actually, we've agreed to all you. All legal means. To be clear, there's. I don't believe either of these companies give a rap about any of this. I don't think they care about it at all. But Anthropic had this swell of good press because people thought that they were opposed to the war in Iran, when in fact they were directly part of it. Claude was used during it. Now, how complex was the use? It was probably like, here's a bunch of images. Where should we blow up? And it went, here's a school. And they went, oh, just great. And that actually happened. And then there were weird articles that came out saying, like, actually, Claude didn't do that. Yeah, you can't prove that, mate. What I can prove is that Claude was used in the war in Iran. So whatever.
- [33:24]
A
But your conjecture, Your conjecture is the reason why Amadei brought this up was its press.
- [33:30]
B
Yes.
- [33:31]
A
The size of that contract is worth jeopardizing when you're looking at like an IPO six months from now, sorry, size of that contract.
- [33:39]
B
Their military contract is up to $200 million. And the. Up to is an important operative word, $200 million. They lose that money on inference, like two weeks. Yeah.
- [33:50]
A
And they're looking to raise. I mean, their valuation is, what, in the hundreds of billions? Three.
- [33:54]
B
Three something. 100 billion. They'll probably IPO at 750, if they even make it. But that's the thing.
- [34:00]
A
No, they did it for $100 billion. Move there. In theory, yes.
- [34:05]
B
Yeah. Well, also the thing is, as well is, like, then the Department of War said, oh, we're going to. We're going to. We're gonna put you as a supply chain risk. Nothing happened. Then they were like, it's a supply chain risk, but we're gonna keep using you for six months. Then there was a lawsuit. The department, the anthropic, sued the Department of Defense and said, if we don't have this removed, we might die. And. And then admitted, by the way. And this is one of my biggest. This was like my full joker moment during that. During that motion that they filed, Krishna Rao, the CFO of Anthropic, filed an affidavit, sworn affidavit, where he said that Anthropic had only made $5 billion in its entire lifetime.
- [34:52]
A
Yeah.
- [34:53]
B
Now when you go and add up all of the reports of revenue, such as the information saying $4.5 billion in revenue in 2025, such as anthropic themselves saying annualized revenue, that would mean They've made 1/2 billion dollars in the space of a month in 2026. It adds up to way more than 5 billion. I have tried to talk to pretty much every major reporter that covers Anthropic's revenues, and they will not discuss this. It's the most conspiratorial I felt this entire time. It is like. It is like everyone is trying to ignore a fire in a room. And the crazy thing is, is that happened. Nothing changed. And then a judge said, actually, Anthropic's right. We're not going to allow the supply chain risk designation. And now, apparently the US Government is using Claude Methos. So in the end, nothing happened. Yeah, Anthropic. Anthropic got a bunch of completely spurious press around them being ethical, despite the fact that they are already part of the military. They revealed their actual revenues. It was great. It's all good.
- [35:56]
A
That revenue story, that is an amazing. Outside of you, I covered it. I learned about it in part from you. I found only one article. There was maybe a Reuters or an AP article that talked about this quote, unquote, like shaky revenue math that's popular in Silicon Valley. So there's one piece I found where a financial reporter actually was covering. Like, hey, when you hear these numbers, there's a lot of multiplying by 12 or multiplying by 24 going on. And you multiply at the right time times. But that was a big story. So for the listeners to understand it, Anthropic had to, under oath, signed affidavit. Right. So the penalty of perjury or whatever you would say in a corporate setting had to release their revenues and it was $5 million. 5 billion to date on 60 billion of investment in debt. I think the date. So.
- [36:42]
B
Yep. And they spent 15 billion on compute so far.
- [36:46]
A
Yeah, 15 billion on compute so far. The other part of that, the part of the story I did cover that I thought was interesting was the Undersecretary of Defense, whoever that was, Emil Michael. That was Emil Michael. Right. And he went on and it was. It was funny. It shows something about how the online commentary space works. He went on and said, hey, here's why we don't want to work with this product. This is. If you watch him, he's basically be like this is a product that'll say it has a soul or that like their company is saying that there's like a chance that it's alive. And what he was saying was like this is a wonky product. Right. Like this doesn't seem like the type of thing you want in a. A military setting where you have the CEO saying there's a chance it's alive and it'll say it has a soul. This doesn't seem like a reliable piece of hardware. And what was the online commentator report was Pentagon convinced that Claude has a soul. So it completely. They flipped the veils.
- [37:40]
B
He was basically saying, I'm so sick of this. I'm so sick of the goddamn AI bubble. I'm sorry. So tired of this. Yeah, I wish I got this kind. I wish anything I did was. I wish. You've not read One Punch man, have you?
- [37:54]
A
No.
- [37:56]
B
Okay, so this is a complex thing, but one of your listeners is going to hear this and love this. There is a character in One Punch man called King. Everyone thinks that he's the most powerful man in the world because of the King Engine, which is his so called power. It's actually because his heart. He is so anxious and scared at all times that his heart is going that you so fast you can hear it. He has no powers. He's a regular guy. But because Saitama, the main guy comes along and destroys anything near him. Everyone thinks he's amazing. And there are multiple times during the story where a bunch of stuff happens around him and people go, wow, they must have all just died when they saw King. Wow. King must have destroyed them with the King Engine. This is anthropic. Anthropic is just this wasteful crap pile of a company with services that break half the time less than two nines now of service availability. And they have models that degrade at random. They gaslight the users, they rug pull them on rate limits. But everyone's like, Anthropic's capacity is so they're hitting capacity because they're so popular and their models are so good. It's like, I'm going crazy, man. I just, at some point what I'm saying will feed into the mass consciousness, I guess. And at that point I'm going to be insufferable. But it's like every time I hear a story like this, I feel like I'm. I'm going insane.
- [39:17]
A
What are the main revenue sources if we're being realistic about it? So if you're these AI companies. Well, my understanding is OpenAI is ChatGPT subscriptions.
- [39:27]
B
Yes.
- [39:27]
A
Anthropic is like cloud code.
- [39:31]
B
API.
- [39:32]
A
API.
- [39:32]
B
Apparently it's API. Yeah, but here's the thing. I'm not accusing anyone of fraud, but I. There was a. Eric Newcomer had a piece where he said the Anthropic, they had the cochyu venture capitalist and he shared the deck that Anthropic had shown them. And there was a bit where it was like, yeah, 85% of their revenue is API calls and 15% is subscriptions going to be honest, I don't believe him. I just don't believe it. I don't believe that There is what, 4 odd billion dollars of API calls and OpenAI apparently is the other way around where it's like 85% subscription, 15% API.
- [40:11]
A
What would an API call be? So for the Listener, so what's APIs?
- [40:16]
B
So it would be an AI startup. It would be a business that's running their own models for some reason that is running their own systems that built on top of the API. But that's the thing. Even that question kind of gets at what I'm saying, which is what the hell are you doing with this? Like what? What? Like I get AI startups that just sell things that have LLMs plugged into them, but it's like they're claiming they have all this enterprise use. And what I think it might be is that Anthropic is slowly. Because this, the information reported this recently. I think it's been going on for a lot longer. Anthropic has started to push enterprise users onto the API even when they're using Claude or CLAUDE code. I think that's fairly recent in the last few months.
- [40:57]
A
Right.
- [40:58]
B
But I also just think that these companies are making up what they're saying index because no one can prove otherwise. I think I want them to go public so bad. I want them to go public. So bad. Never in a million years have I wanted a company to file an S1 more. I want to see inside their laundry. I want to go look around.
- [41:18]
A
I don't. I don't doubt you'll be the first to read those S1s cover will be.
- [41:23]
B
I will be smoking a big cigar. It's going to be delightful.
- [41:28]
A
Before we get to the third story, let me tell you my new term I coined about AI coverage. All right, I just came with this on the spot, but something else that's going on right now that I want to call out is what I call dread laundering. And what you do is you will launder a sense of despair or dread about one thing related to AI to help amplify a less supported feeling of dread or despair about another. And so here's where I've been seeing this recently is I think the technology business case for LLM somehow being at the core of automating a bunch of jobs or destroying the economy is very weak. And I think there hasn't been a lot of good support for that because again, these are just LLMs that we're building better apps on top of. And it's slow going, but there's a lot more focus recently. It's like, we have to. There's a dread quota. So how do we fill it if that is losing some traction right now? So there's a lot of other coverage going on about destruction of the arts, writing. The writing's going to disappear. Movie making is going to disappear. Education is falling apart. And you put that next to Dario Amade talking about jobs or this or that, and you're laundering the dread from, oh, we have a text generator. And people are going to be lazy and try to not write text, which is a real story and an annoying. And just one is a writer I don't like. And you launder that dread over to like, well, all these other bad things. This is all kind of the. If we're worried about that, that kind of just justifies the dread in general. So also, like, maybe my job's going away. Maybe the terminators are coming. And I really wish these were really separated and that you could have an argument about. We have automatic text generators. Brings up a lot of problems for parts, you know, people who produce text for a living. Let's talk about it then. We have over here this claim that an LLM is going to take over an executive job or is going to, you know, and that's like, those fall under scrutiny it's really hard to get a compelling case over there, but if you throw enough darts at enough things, you create a miasma of unrest in which, like, it's hard to make out what the actual signals are or not. So just everything, it's like a pox in all the houses. Everything is terrible. So that's my.
- [43:38]
B
I fully agree. And I also think that Dooma porn clearly gets clicks. It's just that I think that when this is all over and the bubble burst, I think every single person who engaged in it should lose their job across the board. I know it sounds aggressive, but I think everybody who. I think everybody who engaged in the doomer porn. And yeah, there are some people who try and tried to do it in good faith, but the ones who like the Axios of the world who genuinely sat there and fermented dread, they shouldn't be allowed to work in journalism for a minute. They should take a knee, they should step aside for people who actually live in the real world.
- [44:16]
A
It is a problem that we have to address. Maybe I talked about this on your show earlier this week, but I'm hearing from listeners and readers that again, they use terms like I'm stuck in a cage having wave after wave of despair or dread crash on me with no option, hope, or of escape from it. And I just am taking wave after wave. There's a responsibility aspect to it, right? Like it is difficult for the normal person to be hit again and again from all different angles. Well, what if this is terrible? What if this is terrible? What if this is terrible and if there's smoke, there's fire mindset that we're wired for. And it's really, I think, been very unsettling. Again, I get unsettled by it and I actually know the technology and know that 98% of this is really not well supported. But it's just emotionally difficult not to be. Having to just immerse yourself in wave after wave of everyone putting their full attention on. What angle can I find that makes this seem the worst? Like, that's always the angle that things are coming from. It's never from the. Well, this doesn't make sense. What happened to that? Well, where's all this revenue? Hey, what about this story from three months ago? Nothing happened of it. I mean, there was a guy who posted a video that I made fun of and then he attacked me when openclaw first came out where he said, literally, the singularity is here. Like in the next few days. This is it. Look at this graph line goes up next few days, Singularity is here. And I kind of made fun of him. And then he recorded a whole video attacking me about how crazy my takes are. And I just want to say, okay, it's been four months. I don't see the robot army that was supposed to be there in a couple days. Can we never follow up with that?
- [45:49]
B
Where you at? Where's Ultraclaw? Where's the clawed bot that's going to chop my goddamn head off? But that's the thing. It's like, I think that there is an actual theme above all of this that is actually outside of the AI bubble as well, which is short term memory and long term memory that just. People say stuff, things happen and then they forget about them entirely. Like remember the Claude Code marketing push at the beginning of this year? It was the Atlantic that said, this is the chat GPT moment. And it had all sorts of people, of people building useless apps. There was that whole surge of support for that. And now Anthropic is actively throttling their services. They are making their models worse. They are cutting off open claw.
- [46:35]
A
Nothing.
- [46:36]
B
Yeah, no coverage. None of the, none of the people. Because you'd think, here's the thing that I have with AI boosters, even if they fundamentally disagree with me about the economics and all, they don't even seem to engage with the problems. I don't even mean this in an anti antagonistic way. I mean, if I was a pro AI person, if I was like, I don't know, I've been, I have a big piece of metal in my head or something, I would, I saw some British guy being like, hey, they're losing billions of dollars. I would at the very least be like, I should probably look into this. Yeah, I should probably make sure. And if I really like this stuff, then I saw the company screwing over their customers, I'd be like, wow, doesn't that change the story a bit? Nope. Mainstream media, honestly, a lot of independent media just goes, you know, it'll. Something will happen. It's like when it comes to the doom, they will extrapolate as far as they need to. When it comes to the capabilities, they'll go, yes, it's going to be this powerful that when it comes to the things happening in real life, they're like complicated.
- [47:39]
A
Yeah.
- [47:40]
B
You know. Yeah, he's a. You know, things happen, you know, we'll be all right though. And when I say all right, I can't really tell you what that means, but it will be. When I say all right, I mean everyone's going to make money but not me, but the companies who I love for some reason. That's so weird.
- [47:54]
A
That part confuses me. That part confuses me. The media class I'm a part of hates all billionaires except for like these three. Don't get that part.
- [48:02]
B
Yes, exactly.
- [48:03]
A
I don't get that part. All right, story number three. This is in your wheelhouse. It has to do with the reality of the data center boom. I'll read you a quote from a futurism article that includes includes you in it. So be prepared.
- [48:13]
B
Nice.
- [48:14]
A
The data centers powering your favorite AI chatbot are running low on helium, cash and neighbors who don't hate them. And that's not even the worst of it. According to reporting by Bloomberg, about half of the data centers slated to open in the US in 2026 will either face delays or outright cancellations. The publication interviewed analysts at market intelligence company Sightline Climate, which in research first flagged by Ed Zitron last week noted that 12 gigawatts worth of power consuming data centers are set to open in the US this year. But here's the catch. They say only a third of those are actually under construction right now, with the rest in a liminal pre production stage in which they could and likely will be canceled. There's a huge story going on here that's not being covered outside of it's covered in Bloomberg in places where people really need to monitor the private credit markets and other things that could affect their investment portfolios, but it's not broadly known beyond it. What's going on with this illusory data center boom.
- [49:06]
B
Every time you hear someone say we're building a 2 gigawatt data center, real simple. Just say no you're not. No you're not. We don't know how long it takes to build a 1 GW data center because no one has built one. I know that sounds crazy. No one has built one. But once again and cnbc, I'm going to say Mackenzie Singloss at cnbc. I'm specifically saying she has laundered the reputation of these companies because what happens is Stargate Abilene open AI's 1.2 gigawatt 1.2. They opened a single data center in September 2025. And then what was published was the Stargate Abilene was operational. Project Rainier, a 2.2 gigawatt data center in Indiana for Amazon, fully operational. That's a quote from Amazon. No it's not. 2.2 gigawatts is what they're saying. They claim to have half a million trainium, two gpus, 500 watts apiece. That's about 250 megawatts. They claim they're up to a million now. That's 500. That's a lot less than 2.2 gigawatts. Because data centers take forever to build. We do not have the power. And people are saying, well, the power's getting built. That proves they're going online. Nah, the problem problem isn't that the power doesn't exist at all. It means the power doesn't exist at the point of need. So sightline climate. I actually caught up with them on a recent newsletter where they, they said that of the 115 gigawatts of data centers that are meant to come online by the end of 2028, only 15.2 gigawatts of them are actually under construction. Now this is really weird because I did the math. This is napkin math. Forgive me it. When you look at these and you say, okay, they have a PUE. So the efficiency, so 1.35 efficiency we'll call it. When you use that and you take that 15.2 gigawatt thing, you divide it by 1.35, it's about 10 gigawatts of pure GPUs. That's about $285 billion worth of Nvidia GPUs. Why am I saying this? Well, Nvidia claims that they have visibility into half a trip trillion in GPU sales by the end of 2026 and a full trillion by the end of 2027.
- [51:24]
A
Right?
- [51:26]
B
Where are they going, Jensen? Where are the GPUs going? Jensen? Where are they? Where are they as well? Because Nvidia has sold.
- [51:36]
A
It's just a billion people are building custom video gaming rigs at home. Come on, it's easy.
- [51:41]
B
I, well actually I think I know where they are. I think they're in Taiwan because. So it's just very weird because what this means is that Nvidia has already sold too many GPUs. It has already sold more GPUs than are being, than are actually having data centers built for them. It's crazy. And this is the thing. I bring this up with journalists, I bring this up with economists, I bring this up with tons of people.
- [52:05]
A
They're like, man,
- [52:08]
B
it's fine they're being built. What are you talking about? I'm like, look at the data. And they go, ah. It's always like a weird wave off. But this is like this is the largest company on the stock market. And I think that their total revenue from the last few years is over $300 billion. And they're claiming that they'll hit half a half a trillion by the end of the year. They have half a trillion. I think that's just for the year. They keep saying these numbers as well that don't match up, but let's say they're true. And if Nvidia beats and raises so they beat their earnings estimates from analysts again, I think we need to start asking a real question about what Nvidia is doing with these GPUs because talking to some hyperscaler accountants, I know there is a way that they could be doing this where they're able to book the revenue without sending anything. It's called a transfer of ownership. It's when you just sign a contract saying, yeah, you own these GPUs, they're sitting in my warehouse, but these are yours and that counts. Legally that's perfectly legal. It's very strange. And if they're not saying it, they should be filing an 8K. But Nvidia's inventories are growing on their earnings as well. So like it's a sign that something's being warehoused. But I spoke with a few sources and what it is is when a hyperscaler say Microsoft, they don't buy a GPU from Nvidia. They don't go, send me a gpu, I'll put it in a server. What they do is they work with someone called an ODM and original equipment manufacturer, Original device manufacturer or design manufacturer. I think it's design manufacturer, they build the servers and they put the GPUs in there. Quanta Foxconn, also known as Hon hai Precision Corporation Ltd. Hell yeah, I wish we had more normal names. Wishtron, Wuyin, all sorts of companies out there. What they do is they, they, their revenues, all of these ODMs are going up crazy style. But because what they do is they pass the cost of the GPU through as revenue. They buy the GPUs from Nvidia, they put them in a server, they sell them to a Microsoft or an Oracle or a Meta or an Amazon and then they say, yeah, it costs this much with the cost of the GPU in there. This allows Nvidia to hide a great deal of GPUs because they're sitting in Taiwan. Quanta's inventories went up last quarter. I don't know if it's categorically because nobody's buying them. Or they're not being shipped. But for the most part, I think the Nvidia is just pre selling years of GPUs. And I don't know how this is not scarier to people. Michael Burry brought it up briefly weeks after I did, just to be clear. And no one seems concerned about this, when in fact, if there's only 15.2 gigawatts of actual capacity being built and 10 gigawatts of that are GPUs, Nvidia can't sell more GPUs unless it wants to put them in a warehouse.
- [54:57]
A
Right?
- [54:58]
B
But to the larger abstraction of data centers not getting built as well, it's like we're dealing with fraud. Then if we've got a hundred and something gigawatts of data centers being being built, announced, but only 15 of those are actually under construction, under construction could mean anything. It can mean a sink, a scaffolding yard, which is the case with N Scales Data center in Loudon, England. Then that means fraud. That means that someone is doing fraud. That means that people are not actually building things, that people are likely buying land and speculating that a data center might get built there. Perhaps they'll file some planning paperwork, paying their CEO six figures the whole time. Fermi is a great example. Rick Scott's fermi building an 11 gigawatt data center out in. I forget, it's Project Matador. Don't worry though, they're not building anything. Have a patch of land the CEO just left. They apparently didn't pay their contractors. Fraud. So this, and, and this is the thing everyone's talking about the AI boom with all this certainty, but the actual proof that things are happening isn't really there. In fact, and I, I did the maths and it turned out that over 50% of the data centers under construction through the end of 2028 are for OpenAI or Anthropic. Every time Anthropic announces, they just announced a 3.5 gigawatt deal of Broadcom chips. Where are they going? Where are they going? No one asks, no one thinks, no one tries. And the answer is they're not going anywhere. These chips probably will never get bought.
- [56:37]
A
So. Okay, so let's walk through this a little bit. Right? So it sounds like, I mean Nvidia is selling the. They're selling them to these ODMs. Right? So the ODMs are basically saying we will, we're getting contracts, so we'll keep buying chips because there's a lot of money in this market.
- [56:53]
B
Yeah, I just want to be clear. This is how it's always worked. This is not a weird thing. This is how they build datasets. Continue. Sorry.
- [57:02]
A
Because there's a lot of interest in AI. There's a lot of money that's raisable in AI. So you have a lot of entities saying, I want to raise money for AI projects. This is leading to a lot of we will now spend money on these ODMs to Hey, we want to buy X number of chips in, set up in servers. But then there's nowhere.
- [57:21]
B
I think I've, I think I've muddied it up a bit. Okay, so you've got two stories. The ODMs are so when a hyperscaler at Microsoft, they said $37.5 billion of capex last quarter. When they buy servers, they buy from the ODMs. Yeah, ODMs then put them in a warehouse in Taiwan and they say, okay, when you're ready for the data center, let me know.
- [57:41]
A
Yeah. And these data centers are taking longer than, or are harder to build than people realize. They've raised the money, they've made the orders, there's nowhere to put them. So the warehouses are piling up. Nvidia's like, hey, put them wherever you want. Like we're getting our paychecks. Like you can put them, put them on a hot air balloon, we don't care.
- [57:57]
B
The dodgy thing with Nvidia though is that it's unclear because we're talking 100 billion plus GPUs that have nowhere to go, that have been sold. Which begs the question of whether they're leaving Nvidia's warehouses at all. Yeah, because Nvidia could do accounting treatment that just goes, yep, this is yours now. It's here. And so, but completely separate to that because Microsoft, Amazon, Google, their data centers are being built though they're taking forever. But even then there's not enough capacity, not capacity to install these GPUs then completely separate to that, over 100 gigawatts of data centers have been announced that are just not being built. Yeah, and those are more than likely not hyperscaler ones. They are more than likely random fly by night operations. They're companies like Nebius, N Scale Iron, these former crypto companies. But are they spending money?
- [58:50]
A
Are they, I know they're, they're raising money. Are they spending money to the ODMs? Like there are chips somewhere in a warehouse. Either the ODMs or the Nvidias that they paid for, they have nowhere to put Them or are they just raising money and paying salaries until it fizzles out?
- [59:06]
B
Little column A, little column B, hard to tell. I wouldn't be surprised if it's both. I think that there is. And when like Corey, for example, they buy from ODMs, like from like Dell and Super Micro who recently had a co founder arrested for selling chips to the Chinese. So that's cool. But yeah, I think that there is a lot of. Yeah, we're building a data center. Ah, you know, business is rough. We just got to find the land. Ah, we got to find the power. Now that's going to take another three months. I'm going to need to make $650,000 a year. In fact, that's probably a fun thing to go and look at the companies in question and seeing what executive compensation is. But then there's also just the problem of data centers are hard to build.
- [59:54]
A
Yeah, well, this sounds like this at least rhymes with the housing crisis though the magnitude is a little bit smaller. And tell me if I have this right. Like my understanding of the financial crisis of the earlier 2000s is okay, we have these, in that case financial product, these mortgage backed securities. And people want in on those. Right, because they're making a lot of money selling these, they're making a lot of money reselling these. But you kind of ran out of mortgages. But everyone still wanted to get into this. But there's no more mortgages to put in the mortgage backed securities. So we say, well, we'll make, you know, these, these credit default options and these swaps and we'll, we'll build derivative products on top of these. We just need things that we can keep selling because there was more money that wanted to be spent here than there was things to actually spend it on. And of course, once you had built out this giant house of cards built on leverage and bets on bets on bets, when the middle of the house couldn't support, the whole thing fell down. This feels like a simpler version of that. There's a lot of money out there. That's like we wanted to get into AI too because every 16 seconds we're getting an article about how it's the most powerful technology ever and it's about to take over and take all of our jobs. So there's a huge amount of money that wants to go into AI, but there's not actually enough places to put it. And that seems like a summary of what's going on now. And literally there's not enough land and buildings that can take the chips to put the chips in. So we have all this money being spent and Nvidia seems to be collecting a lot of it. But there's nowhere to put these chips. It seems to be what you're saying. It's just way more money that wants to go into this market than there is actual investable assets to put the money into. And so shenanigans follow and you get a very fragile system. And this is why we're worried about the private debt market. Market is beginning to teeter a little bit because these, these investments aren't returning. Nvidia has so much of this money coming in with nowhere to put it. This feels like that's the core of instability. So what happens when some of these contracts fall apart and Nvidia has a fall and it's you know, X percent of the stock market. Is that the right way of seeing it? This like it kind of rhymes with the financial crisis in that sense.
- [61:55]
B
So here's the thing. I don't think it will be as bad.
- [61:57]
A
It's not as much money at stake by far. And it's not. Not derivatives. It's not bets on bets on bet. So it's simpler.
- [62:03]
B
Not yet. Yeah, with that's the big thing. It's not derivatives. Private credit. The big scary thing there is like 30 to 4 is, is related to the software industry and software debt, which is a whole separate subject. You are right in that there is a massive amount of speculation happening here. To quote Gordon Gekko, I think from one of the Wall street movies, speculation is the root of all evil. Someone correct me whether it's Wall street too. Money never sleeps. But it's. It's weirder than that. This is unlike anything because it's a very centralized thing of Nvidia and Nvidia's continued value and Nvidia's kind of load bearing 8%, 7% of the stock market. It's also very weird that it's one company effectively doing it. But the there are hundreds of billions of dollars of data centers that are allegedly getting built and probably a maybe half of that, maybe 75 of that is funded by debt. The private credit industry that's thing that's scary is that much of private credit is funded by retirement and insurance. So right now I don't think data centers make up a ton of private debt. That's awesome. Like at least not a load bearing palm.
- [63:15]
A
Yeah.
- [63:15]
B
I will say the actual housing crisis comparison I'd make is venture capital. And it's not related to. It's Actually not related to data centers at all. So what it is is AI venture capitalists get paid sometimes as a percentage of the fund's value, the assets under management, like any kind of asset manager. So AI companies right now are awesome for them because they get them and they constantly number go up so fast, so big, so huge. Because AI companies are fluffy right now and everyone has these AI companies. And in the subprime mortgage crisis, the way that people waved away the thing about, well, your interest rate's going to change in a year or six months was they said, well, I'll just refinance. In the case of AI startups, Elad Gil, famous venture capitalist, yesterday said all AI startups should look to exit in the next 12 to 18 months. And it's like, okay, well why would you buy them? Because most AI startups are just wrappers for models and you can't take them public because they lose a bunch of money. The subprime AI crisis I talk about is partially with companies not being able to run because the costs go up. It's Also, you've got 200 billion, $300 billion worth of venture capital tied up in AI startups that can't be sold.
- [64:32]
A
Right.
- [64:33]
B
And how does that connect to data centers exactly? Well, data center customers, predominantly AI startups, predominantly two of them, Anthropic and OpenAI, but others as well. Cursor just signed a deal with XAI to rent GPUs, for example. What happens when all of those die? Who's going to pay your data center bills? Also, all the data centers are deeply unprofitable because the horrible debt they require, it's just, it's not. It like you kind of said it rhymes, but it's not like for like. And again, I say it's like more people should be thinking about this. Even the people who are AI boosters should be thinking about this because this is an existential threat. This is not just a ed's being a hater or ED hates this. It's like the maths doesn't make sense. There's not enough space for the GPUs to get installed. There's not even things being built for half of them if they manage to sell. If Nvidia sells like half a trillion dollars worth of GPUs in the next year, they're not going anywhere. Yeah, in fact, I worked out mathematically, based on their last quarter, it takes six months to install a single quarter's worth of GPUs. And I actually think it takes longer. Now I at Some point this falls apart and everyone's gonna act as if it was a big surprise and they shouldn't. The warning signs were there from the beginning.
- [65:54]
A
Right? Right. They literally, they cannot keep selling that many GPUs because there's nowhere to put them and you're building up such a supply. It looks like what's inevitable is going to be two things, financially speaking. There's going to be a stock market hit and private retirement fund insurance hit when this game of musical chairs stops, which is going to probably lead to much more financial scrutiny, probably regulation on accounting within the these companies. And then the venture capital firms when they take the hit of like, oh, we couldn't exit these companies, which we're not otherwise going to be able to get an exit out of. But if we don't get them sold right away because again, it's hard to build a useful, profitable AI product. You're going to get AI Winter. So they're going to be like, well, forget this. You're going to have a few years where it's going to be very difficult to get AI and invest.
- [66:45]
B
So I, yeah, I would actually reframe that slightly. I think what happens is, I think you're right about the stock market stuff. When it comes to the AI startup cards, I think what's going to happen is a fire sale moment. It's going to be a panic. You're going to hear about an AI startup, maybe perplexity may be lovable. That needs to sell. They're like, we need to, we need to get this out the door. And an AC A funding round will fall through, then an acquisition path will fall through. The moment it becomes obvious that AI startups are trying to sell, everything will start collapsing. VCs will have to start telling their investments to sell, sell right now, get out of there. Except when you look Historically, AI startups do not get acquired. Windsurf AI coding company acquired by Google. Nope. They paid $2 billion for three people. The rest of them got sold to Cognition for a couple hundred million dollars and most of them got laid off. What was it? Inflection AI to Microsoft. Microsoft. Billion or so dollars. Mostly went to investors, mostly went to Mustafa Suleiman. What was the other one character AI bought by Google? Several billion dollars. Except that mostly went to the founders and some of the team and of course the investors. But the actual products are not getting acquired. The actual IP doesn't exist. So when these things come to exit, I don't think it's going to be pretty at all. In Fact, it's really easy to clone most of these companies because they're just rappers for LLM models. Right.
- [68:19]
A
And the top mines, which is what is actually being acquired, they've all pretty much now there's not that many left of truly innovative researchers in this space who are doing startups to get. All the big companies have snapped them up for the most part. That's the issue. Dennis Wasabi got snapped up by Google, the Hinton's company got snapped up. I mean these companies have. There's only so many of these big academic research minds and they've all for the most part been. And sometimes it's very expensive to do. You had to buy and shut down their company to get them. But I hear your point. The problem is, yeah, you cannot, if you're a vc, assume well anything we fund will also get bought for a billion dollars because our founders are so brilliant. Actually the brilliant founders are already for the most part probably under cotton. There's only so many of them and they're under contract with these companies. And if what you really have is the product. Yeah, which is a point. And then we'll wrap it up after this. But I do think it's an important point is that like it is we don't really know how to build very useful profitable products. That's the odd thing about this space.
- [69:21]
B
Well, I mean you can't.
- [69:23]
A
There's a couple popular products, the various coding harnesses like Claude code, et cetera are popular among programmers. Not a particularly profitable product space though because they're expensive to run. The chatbots are popular in the sense that they have lots of monthly active users, but it's unclear that I don't imagine those are particularly profitable either just because of the compute cost of people using them. And that's kind of it, I think is the problem. It's very difficult to have your wrapper company actually be a large concern. So that's interesting. Yeah, yeah. So that could be. That's the story that underlies all these other stories and I think it's going to. If it's true, I think it'll so surprised a lot of people because it's going to be biggest technology ever, about to conquer everything. Best technology ever, about to conquer everything. AI Winter stock market collapse Never mind if that happens, that's going to be. That will be an interesting moment. I think there's going to be a lot of frustration among the American populace of like, well, wait a second if that happens. You spent two years trying to scare me. You spent two Years of. Forget Covid Coven's cold and flu season. In terms of disruption, this is like World War II level impacts on our country. Like, it's just. This is it. If it does fizzle into. Not only fizzle, but basically the conclusion of it is that everyone's, you know, in retirement portfolio halves and then that's. That. That's not going to go well. I mean, that, that would have like political ramifications here in the US I think you're going to see, you know, political parties rebuilding around how they think about these technologies. And maybe it won't happen, but I
- [71:00]
B
mean, I, I am confident on my AI startup thing because every single AI startup is a wrapper of a model owned by someone else. And every. Because the. The core thing, and then we can wrap up. I apologize, is that you cannot control the cost of a user with an LLM. You can't do it.
- [71:17]
A
Yeah.
- [71:18]
B
You're mo. And also your most excited customers are the most expensive, which is antithetical to how a business works. And also all of them are unprofitable.
- [71:27]
A
Yeah, this is very different than. Even though the SaaS model is now falling apart for other reasons, it's a very different situation where at least what made that tech sector so desirable, for example, was this idea of you can just scale up profits infinitely. Just everyone who pays $20 a month for this is $18 a profit and we can handle an unlimited number of users. And that of course, got a lot of private equity eyes bigger than their stomachs. Like, oh, great, we'll just build giant sales teams. And look, if line goes up like this with 10 salesmen, what if we have 100? But at least the underlying profit mechanics made sense of it cost us negligibly more to have 100,000 users versus a thousand. And it's massively more income. This is very different, you're saying, than LLM based AI? It's actually very expensive to service the users and the more they use it, the more expensive it becomes. And that's a hard dynamic. Yes. And more users doesn't make it cheaper.
- [72:22]
B
No. More expensive, in fact.
- [72:24]
A
Yeah, it's unlike a gym or something. Like, great. More the merrier because very few people actually use it. It's actually the opposite. All right, Ed, well, a pleasure as always.
- [72:33]
B
Thanks for having me.
- [72:34]
A
Yeah, yeah. You always bring out the radical in me, but I think we gotta balance out. I think people are hearing all day long the strongest of boosterism. So it's good to check back in on some of these stories and give a less impressible take. So we'll have to do this again soon because there will be, unfortunately, no shortage of new stories coming out that we're going to have to react to.
- [72:55]
B
Thanks for having me, man.
- [72:56]
A
All right, talk soon.