Demis Hassabis has had one of the most extraordinary careers in tech. He started as a chess prodigy and video game designer at 17 before getting a PhD in neuroscience and going on to found DeepMind. His lab cracked Go, solved protein structure prediction with AlphaFold, and then gave it away free to every scientist on earth. That work won him the 2024 Nobel Prize in Chemistry. Today he leads Google DeepMind, pushing toward the same goal he set as a teenager: AGI. On this special live episode of How to Build the Future, he sat down with YC's Garry Tan to talk about what still needs to happen to get us to AGI, his advice for founders on how to stay ahead of the curve and what the next big scientific breakthroughs might be. Chapters: — Intro — Demis Hassabis: From Chess Prodigy to DeepMind — What’s Missing Before We Get To AGI? — Why Memory Is Still Unsolved — How AlphaGo Shaped Gemini — Why Smaller Models Are Getting So Powerful — The 1000x Engineer — Continual Learning and the Future of Agents — Why AI Still Fails at Basic Reasoning — Are Agents Overhyped or Just Getting Started? — Can AI Become Truly Creative? — Open Models, Gemma, and Local AI — Why Gemini Was Built Multimodal — What Happens When Inference Gets Cheap? — From AlphaFold to the Virtual Cells — AI as the Ultimate Tool for Science — Advice for Founders — The AlphaFold Breakthrough Pattern — Can AI Make Real Scientific Discoveries? — What to Build Before AGI ArrivesApply to Y Combinator: https://www.ycombinator.com/applyWork at a startup: https://www.ycombinator.com/jobs
