David Silver leads the reinforcement learning research group at DeepMind and was lead researcher on AlphaGo, AlphaZero and co-lead on AlphaStar, and MuZero and lot of important work in reinforcement learning. Support this podcast by signing up with these sponsors: – MasterClass: https://masterclass.com/lex – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Reinforcement learning (book): https://amzn.to/2Jwp5zG This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 – Introduction 04:09 – First program 11:11 – AlphaGo 21:42 – Rule of the game of Go 25:37 – Reinforcement learning: personal journey 30:15 – What is reinforcement learning? 43:51 – AlphaGo (continued) 53:40 – Supervised learning and self play in AlphaGo 1:06:12 – Lee Sedol retirement from Go play 1:08:57 – Garry Kasparov 1:14:10 – Alpha Zero and self play 1:31:29 – Creativity in AlphaZero 1:35:21 – AlphaZero applications 1:37:59 – Reward functions 1:40:51 – Meaning of life

David Silver, a principal research scientist at DeepMind and a professor at UCL, dives deep into the evolution of reinforcement learning. He discusses the fascinating transition of AlphaFold from RL to supervised learning for protein folding and highlights RL's potential in protein design. Silver also reflects on how personal health impacts research output and shares insights on AlphaZero's learning strategies in various games. He encourages aspiring researchers to embrace boldness in their endeavors and sketches his journey towards advancing artificial general intelligence.

In a dynamic discussion, David Silver, a leading professor in reinforcement learning, dives into the nuances of meta-learning and planning algorithms. He explores how function approximators can enhance RL during inference and contrasts human cognition with machine learning systems in tackling complex problems. Silver also discusses the recent advancements in RL algorithms mentioned during his keynote at the RCL 2024, highlighting ongoing innovations in the field.