Jim Chanos & Gary Marcus: Circular AI Financing, The Agentic Economy & Doomsday Scenarios

SPEAKER_1 (0:00)

Balance your trading strategy by adding futures. CME Group helps you manage risk and capture opportunities at all market environments. Capitalize on around-the-clock access to highly liquid global futures and options market across all major asset classes. Just visit your online broker and get started. Plug into valuable educational materials and trading tools and see what adding futures can do for you at cmegroup.com/on the table.

Quick question, do you know who's actually holding your money? You know, your stock's an investable cash. In this business, that answer matters. You should know who's safeguarding your assets. There's a good chance it's Apex Fintech Solutions. With millions and millions of brokerage accounts across 200-plus investment platforms, they're one of the largest and most reliable custodians in the business, providing the custody, clearing, and cloud native infrastructure that modern investing runs on.

Visit apexfintechsolutions.com.

Dan Nathan (1:08)

Welcome to Risk Reversal Podcast. I'm Dan Nathan. This is my friend, Jim Chanos. He's the founder of Chanos and Co. I think this is like maybe your 10th appearance on the podcast, Jim. You were also a fab professor at Yale University and at University of Wisconsin. You teach a class on financial fraud at both universities. Thanks for being back here, man.

Jim Chanos (1:29)

The history, not how to commit it.

Dan Nathan (1:31)

Hey, do you go to the Harvard, Yale football game or no, or just a lot of Wisco games? That's your deal.

Jim Chanos (1:38)

I have been known to go to Harvard and Yale football games, yes.

Dan Nathan (1:41)

I'm sure you're a great tailgater. All right. This is Gary Marcus. Now, this is one. This is really interesting how this came together. I, like hundreds of thousands of people, read Marcus on AI. That is your substack. You're also a multiple time author, a taming of Silicon Valley. You also testified next to Sam Altman in the Senate in 2023 That sounds almost cute, like a long time ago. We had different views of Sam Altman back in the day, and you're also NYU Professor Emeritus. Gary, welcome to the podcast.

Gary Marcus (2:11)

Thanks for having me.

Dan Nathan (2:11)

All right. This is kind of serendipitous how this came together. Jim was going to be on the podcast already. You graciously reached back out to us. You said you're going to do the podcast. You want to do it in New York, you're going to be in New York, and we were like, okay, let's do this together. Each of you have, I don't know, Jim, you've attacked this whole issue of the AI build from a financial standpoint. That's how you started with it. Gary, you are a technologist, is that fair to say? You have a PhD from MIT, that sort of thing. You've been in the space for a long time. You wrote your dissertation, is this 30 years ago? Sorry to age you a little bit. Our neural networks, and we all know this is, I don't know, like an early sort of fetus to what's going on right here. Does that sound kind of gross? I don't know.

Gary Marcus (2:58)

Well, my dissertation was actually on two things. It was on how children learn language, and it was on neural networks that are the ancestors of today's neural networks. So I've always been interested in natural intelligence and artificial intelligence, straight for a few decades, more than I care to admit.

And when these neural networks came back in fashion in 2012, I had been mostly working on the cognitive science side of things, the human side, but I was like, I recognize all this stuff, this is what I worked on in my dissertation. And in fact, I wrote a book in 2001 called The Algebraic Mind, writing about the limits of the ways that people were then building neural network. And I think I was actually the first person to point out that these things were going to hallucinate unless they changed how they built them.

And so many of the problems that we see now, I saw quite a long time ago. And over and over again, I keep hearing this argument, just give us more data and we'll solve them, which hasn't really worked. I mean, it's solved a little bit, but not that much. So I've been observing the limits of these systems for quite a long time. And then I got into the economics of it from a technical understanding. So in August 2023, it dawned on me that basically everybody was building the same thing. And that meant that there was no technical moat. And so I wrote a pair of essays in my Substack in August 23 saying, I'm not sure the finances of all this is really going to work out. And I said, look, there's no real technical moat here. And what that's going to mean is price wars. Everything's going to become a commodity.