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/