Scaling laws took us from GPT-1 to GPT-5 Pro. But in order to crack physics, we’ll need a different approach. In this episode, a16z General Partner Anjney Midha talks to Liam Fedus, former VP of post-training research and co-creator of ChatGPT at OpenAI, and Ekin Dogus Cubuk, former head of materials science and chemistry research at Google DeepMind, on their new startup Periodic Labs and their plan to automate discovery in the hard sciences. 00:00 Introduction 02:17 The Role of LLMs in Physics and Chemistry Research 03:53 What is Periodic Labs? 05:25 The Importance of Experimentation 07:44 Challenges and Goals in Physics Research 14:45 Building the Team 17:29 Scaling Laws and Physical Verification 22:36 Focus on Superconductivity 25:33 Creating a Repeatable Process for ML Systems 26:08 Balancing Commercial Viability and Scientific Goals 27:39 Periodic's Mission and Industry Applications 28:49 Integrating Diverse Expertise in the Team 29:52 Teaching LLMs to Reason in Physics and Chemistry 31:29 The Importance of Collaboration and Learning 35:38 Deploying AI in Traditional Industries 41:03 Mid Training and Its Impact on Model Performance 45:21 Collaboration with Academia and Future Directions 49:49 What Makes a Great Researcher at Periodic? Follow Liam on X: https://x.com/LiamFedus Follow Dogus on X: https://x.com/ekindogus Learn more about Periodic: https://periodic.com/