What Happens After A 1,000,000x AI Compute Leap? | Jeff Dean

Thank you to Google for the invite! 🙏 ❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambda.ai/papers 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Adam Bridges, Benji Rabhan, B Shang, Cameron Navor, Charles Ian Norman Venn, Christian Ahlin, Eric T, Fred R, Gordon Child, Juan Benet, Michael Tedder, Owen Skarpness, Richard Sundvall, Ryan Stankye, Shawn Becker, Steef, Taras Bobrovytsky, Tazaur Sagenclaw, Tybie Fitzhugh, Ueli Gallizzi My research: https://cg.tuwien.ac.at/~zsolnai/ Thumbnail design: https://felicia.hu Chapters: 00:00 Intro 02:07 Are We Running Out of AI Data? 06:22 The 90% Shift: Why Inference is Taking Over 09:34 The End of the Pre-Training and Post-Training Split 12:02 What Happens After a 1,000,000x Compute Leap? 15:03 How Distillation is Supercharging Open Models 16:17 The Quest for a "Lifetime AI" 17:25 Multi-Agent Workflows 18:40 AI Generating Operating Systems (and Running Doom) 20:15 Solving The Attention Problem 22:13 Data Center Disasters: Supernovas and Cosmic Rays 24:45 The Lightning Round: Jeff Dean Chuck Norris Jokes 25:40 The One Thing Jeff Dean Got Wrong (Healthcare AI) 26:50 The Ultimate Developer Debate: Vim vs. Emacs