Latent Space: The AI Engineer Podcast · Synthesis Superintelligence: from Semiconductors to Superconductors - Periodic Labs’ Liam Fedus and Ekin Dogus Cubuk
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Built reinforcement-learning environments that ingest noisy experimental data from their physical labs and reward agents for correctly identifying crystal phases from X-ray diffraction patterns
“You can construct reinforcement learning environments where you say, okay, given that body of experimental evidence, and given the choices, what was the next choice that the scientists made”
“I built an agent that ingests and transforms transcripts that we get from users and customers so that we can turn it into product recommendations”
“Stores that data for 15 years, by the way, 15 years of your travel patterns are sitting on their servers”
“The second thing that they see is we typically discover agents that they had no idea were actually running in their environment.”
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