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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