#475 – Demis Hassabis: Future of AI, Simulating Reality, Physics and Video Games

Summary

It's hard for us humans to make any kind of clean predictions about highly nonlinear dynamical systems. But again to your point, we might be very surprised what classical learning systems might be able to do about even fluid. >> Yes, exactly. I mean fluid dynamics, Navia Stokes equations, these are traditionally thought of as very very difficult intractable problems to do on classical systems. They take enormous amounts of compute, you know, weather prediction systems, you…

Show notes

Demis Hassabis is the CEO of Google DeepMind and Nobel Prize winner for his groundbreaking work in protein structure prediction using AI. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep475-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/demis-hassabis-2-transcript CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or ca

Themes

• google-ai
• society
• culture
• It's hard for us humans to make any kind of clean predictions about highly nonlinear dynamical systems
• But again to your point, we might be very surprised what classical learning systems might be able to do about even fluid
• I I used to write uh physics engines and graphics engines and in my early days in gaming