AI for Atoms: How Periodic Labs is Revolutionizing Materials Engineering with Co-Founder Liam Fedus
What happens when you apply the scaling laws of large language models to the physical work of atoms? Elad Gil sits down with Liam Fedus, co-founder at Periodic Labs, which is pioneering an AI foundation lab for atoms. Liam discusses how he pivoted from dark matter physics research to the front lines of artificial intelligence, including stints at Google Brain and working on ChatGPT at OpenAI. He talks about how Periodic is connecting massive language models to the physical world to overcome data bottlenecks in material science. Liam also shares how they use language models as an orchestration layer operating alongside specialized neural nets to run closed-loop physical experiments. They also explore the future of AGI and ASI, as well as the role of robotics in lab automation.
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Chapters:
00:00 – Cold Open
00:05 – Liam Fedus Introduction
00:39 – Liam’s Background at Google Brain, OpenAI
05:14 – From ChatGPT to Materials and Atoms
06:34 – Training Data in the Physical World
09:52 – Generalization Across Domains
11:31 – Models as an Orchestration Layer
12:48 – Commercialization and Business Model
16:10 – How Periodic’s Success May Shape the Future
17:45 – Multidisciplinary Scaling
19:41 – Capital and Compute
21:12 – Hiring at Periodic
21:44 – Thoughts on AGI and ASI
23:30 – Timeline for Machine-Directed Self-Improvement
25:39 – Automation and Data Generation
27:59 – Why Liam is Excited About the Future of Robotics
29:25 – Conclusion
Training an AI Scientist with Feedback from Reality, w- Liam Fedus & Ekin Dogus Cubuk (from a16z)
Today’s special crosspost features a16z General Partner Anjney Midha with Liam Fedus and Ekin Dogus Cubuk of Periodic Labs. They discuss experiments in training frontier AI models on real-world physics lab experiments—rather than digital reward functions—and how coupling language models with automated materials synthesis could accelerate the discovery of room-temperature superconductors and transform R&D in advanced manufacturing.
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Core innovation: Periodic Labs is creating a "physically grounded reward function" by integrating experiments directly with AI systems.
Physical lab integration: Unlike traditional AI labs, Periodic includes actual physical experimentation facilities where AI can run tests in the real world.
Novel approach to training: Periodic takes pre-trained language models and further trains them on physics and chemistry knowledge to improve performance in scientific domains.
Read the full transcript here: https://storage.aipodcast.ing/cache/combinedtranscript-20251002T100327544Z.html
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Building an AI Physicist: ChatGPT Co-Creator’s Next Venture
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.
Follow Liam on X: https://x.com/LiamFedus
Follow Dogus on X: https://x.com/ekindogus
Learn more about Periodic: https://periodic.com/
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