Sergey Levine - Building LLMs for the Physical World

**Patrick O'Shaughnessy** (0:00)
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Hello and welcome, everyone. I'm Patrick OShaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at colossus.com.

**SPEAKER_2** (2:15)
Patrick OShaughnessy is the CEO of PositiveSum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of PositiveSum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of PositiveSum may maintain positions in the securities discussed in this podcast. To learn more, visit PSUMVC.

**Patrick O'Shaughnessy** (2:43)
My guest today is Sergey Levine, one of the co-founders and researchers at Physical Intelligence. As a disclaimer, I'm an investor in Physical Intelligence because I believe it's one of the most important companies tackling the problem of robotics. As you hear us discuss today, robotics has what I would call a scarecrow problem. All of these amazing physical devices are becoming ever more possible in all sorts of cool permutations. But what they all really need is an intelligence, a brain. And that is what they're developing at Physical Intelligence. They're trying to develop foundation models that can make any physical robot do any task in any environment. The nature of our conversation today is all of the problems facing robotics and all of the promise of solving these problems across the world. I hope you enjoy this great conversation with Sergey Levine.
Sergey, this is going to be a real treat and a blast to learn about possibly the most exciting, impactful area of technology being developed. Just to set the stage before we go back in time, maybe you could just define physical intelligence as you see it.

**Sergey Levine** (3:42)
Fundamentally, the goal of physical intelligence is to develop robotic foundation models that can control basically any embodied system to do any task. Broadly speaking, you could imagine that in the same way that a language model is rapidly evolving towards a system that can do any task that can be expressed in language, what we would like is to build a new class of models that can do any task that can be done by a physical actuated device. Part of the thesis of this company is that we believe that doing it at the full level of generality might actually in the long run be easier than trying to special case very specific narrow application domains. Again, in much the same way that for language models, it turned out to be easier in some ways to solve natural language tasks in their full generality than to narrowly target like machine translation or sentiment analysis or whatever.