Chelsea Finn 在 YC 活动上讲强化学习让机器人效率翻倍，还能连续干活几小时，想了解通用机器人怎么落地可以听听。
Physical Intelligence 联合创始人 Chelsea Finn 在 YC Startup School 2026 上分享了通用机器人的研发经验。她表示强化学习将机器人吞吐量提升了 2 倍。其系统已能自主运行数小时，无需人类全程监护。她认为机器人正进入 GPT 时代，从专用模型走向跨任务、跨机器人、跨环境的通用系统。
Robots can already fold laundry, make espresso, clean kitchens, and assemble things. The harder prob...
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_int cofounder @chelseabfinn 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. 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 Your browser does not support the video tag. 🔗 View on Twitter 💬 6 🔄 4 ❤️ 27 👀 7276 📊 9 ⚡