Bridgewater's Greg Jensen on AI, Inflation and What Markets Are Getting Wrong

Tracy Alloway (0:10)

Hello, and welcome to another episode of the Odd Lots Podcast. I'm Tracy Alloway.

Joe Weisenthal (0:14)

And I'm Joe Weisenthal.

Tracy Alloway (0:16)

Joe, I think it's fair to say, there is a lot of excitement about investing in AI. There is also a lot of excitement about using AI to invest.

Joe Weisenthal (0:27)

Yes, I mean, I think there's like a new like chat ETF I saw an ad for, and there's like, oh, we're getting, you know. I think I saw another like project, it was like, we're going to have Chet GPT pick the stocks for us.

And I, you know, I get it. It's kind of exciting. And maybe there's some new way of like these super advanced digital brains that can beat the market, et cetera. But like, I don't totally get it.

Tracy Alloway (0:51)

Well, I also feel like there's a tendency nowadays for people to talk about artificial intelligence in a sort of abstract manner. You hear people bring up AI almost as a synonym for just software at this point.

I think you pointed out recently that the Kroger CEO mentioned AI like eight times on the earnings call. So a supermarket chain, right?

Joe Weisenthal (1:16)

Yeah. And, you know, it's like machine learning, tech, algebra, algorithms. It's all existed for a long time, quantitative investing. But it feels like because of the excitement around a few specific consumer facing products that have been unveiled over the last six months and the way they've captured people's attention, people like, you know, suddenly there's a lot of interest in, like, how are companies using this tech to do something?

Tracy Alloway (1:41)

Yeah. Well, I'm glad you mentioned that, because today we really do have the perfect guest. This is someone we've actually spoken to about AI before last year. In fact, someone who is at a firm that has a lot of experience using machine learning and AI of different types. And we're going to get into the differences between all those technologies.

I'm very pleased to say we are going to be speaking once again with Greg Jensen, the co-chief investment officer at Bridgewater Associates. So, Greg, thank you so much for coming back on Odd Lots.

Greg Jensen (2:15)

Yeah, it's great to be here. Exciting topic.

Tracy Alloway (2:19)

Yeah. So I actually revisited our conversation from last year. I think it was in May of 2022 And you said two things that stuck out in retrospect. So number one, you said that markets had further to fall, which turned out to be correct. And two, you brought up artificial intelligence as a major point of interest for Bridgewater. And this was all before ChatGPT really became a thing.

Everyone started talking about AI at every single conference and earnings call and so on. So I guess just to begin with, maybe you could lay the scene and going back to Joe's point in the intro, we are used to hearing these terms. So Bridgewater does machine learning and systematic strategies and quantitative trading strategies and AI and things like that.

What's the difference between all of these things and how do they relate to each other at a firm like Bridgewater?

Greg Jensen (3:18)

Yeah, great question. So I think to answer that, let me take a step back for a second and give you a little bit of my background because it all kind of comes together in a way to connect these different pieces.

So, you know, even as a kid or whatever, I was certainly interested in kind of translating and predicting things using some mix of my thinking and technology. So I can think back to in the late 80s using astro-automatic baseball cards, I don't know what they are, but programming them into computers to try to calculate the way to create the best baseball lineup and use that in fantasy baseball type situations. And similar things with poker and whatever, and trying to learn how to kind of use technology to combine with human intuition to get at what was different ways to create edges. And then in college when I heard about Bridgewater, Bridgewater was a tiny place at the time, but the basic idea that there was a place where we were trying to understand the world, trying to predict what was next, but doing that by taking human intuition and translating that into algorithms to predict what was next, kind of mixed two things that I loved. I loved to try to understand the world. And I loved the idea of having to discipline to write down what you believed in, stress test what you believed and utilize that, right? So if you go back, and this is now in the 90s, kind of where artificial intelligence was at the time, most of the focus was still on expert systems, was still on the notion that you could take human intuition, you could translate that into algorithms. And if you did enough of that, if you kept kind of representing things in symbolic algorithms, that you could build enough human knowledge to get kind of a superpowered human. And Bridgewater was a rare example of where that worked, where given the focus of trying to predict what was next in markets, given the incredible investment that we made into creating the technology to take human intuition and translate that into algorithms and stress test that, it's an incredibly successful expert system essentially that was built over the years. I'd say probably the most profitable expert system out there.