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Chelsea Finn: This is the State of the Art in Robotics Chelsea Finn: This is the State of the Art in Robotics 59 min Your Next Budget PC Upgrade is...Custom Watercooling?? Your Next Budget PC Upgrade is...Custom Watercooling?? 25 min This is NOT an iPhone This is NOT an iPhone 2 min New Alien Host Planet Just Dropped New Alien Host Planet Just Dropped 1 min Apple Intelligence scares me Apple Intelligence scares me 1 min Android 17 Is the Biggest Upgrade in Years Android 17 Is the Biggest Upgrade in Years 18 min Every iPhone Ever. SAME photo! Every iPhone Ever. SAME photo! 1 min This GPU can be Hacked to Unlock Secret Memory This GPU can be Hacked to Unlock Secret Memory 20 min The Weird Orbit of the ISS The Weird Orbit of the ISS 2 min The Best Value Gaming PC I’ve Ever Seen The Best Value Gaming PC I’ve Ever Seen 12 min How Strong Is The STRONGEST Magnet? 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Chelsea Finn: This is the State of the Art in Robotics

2026 59 min

Robots can already fold laundry, make espresso, clean kitchens, and assemble things. The harder problem is getting them to do those tasks reliably, for long periods of time, without a human babysitting them. At Startup School 2026, Physical Intelligence cofounder Chelsea Finn explains what it takes to build general-purpose robots that work in the real world. She shares how reinforcement learning pushed robot throughput up 2x, how their systems can run autonomously for hours, and why she believes robotics is entering its GPT era: moving from specialized models toward general-purpose systems that can work across tasks, robots, and environments. Transcript: https://www.ycrootaccess.com/p/chelsea-finn-on-the-next-decade-in Apply to Y Combinator: https://www.ycombinator.com/apply Work at a startup: https://www.ycombinator.com/jobs Chapters: 00:00 — The State of Physical Intelligence 01:23 — What It Takes to Make Robots Useful 05:11 — The Reliability Problem 07:43 — Reinforcement Learning for Robotics 09:35 — Learning From Failures 12:43 — Training Robots to Improve Themselves 14:21 — Can a Robot Work for 13 Hours Straight? 17:36 — Why Robots Need Memory 21:22 — Building a General-Purpose Robot 25:02 — From Fine-Tuning to Out-of-the-Box Models 27:35 — Training on All the Data 30:20 — One Model That Beats the Specialists 31:21 — Compositional Generalization 37:49 — The GPT Era of Robotics 39:49 — Q&A

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