Were You Still Talking?
Joel Albrecht
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Introducing Training robots for a world they’ve never seen from Possible. Follow the show: Possible Useful robots won’t be programmed one task at a time; they’ll need to adapt to unfamiliar objects, environments, and robot bodies. Physical Intelligence cofounder Chelsea Finn (named last month to the TIME100 AI list for 2026) joins Reid Hoffman and Aria Finger to explain how general-purpose robot models learn to act in the messy physical world. She explores why lower-quality training data can strengthen a model, what months of failed laundry-folding attempts revealed, and how the same system can work across different robot platforms. A robot mistaking an oven for a drawer becomes a lesson in the strange line between useful generalization and obvious error. They also examine why robot demos can mislead, how hardware reliability can stall progress, and what it will take to move AI off the screen and into the world. Congratulations to Chelsea, recently named one of TIME’s 100 most influential people in AI: https://time.com/collection/time100-ai/2026/chelsea-finn/ DISCLAIMER: Please note, this is an independent podcast episode not affiliated with, endorsed by, or produced in conjunction with the host podcast feed or any of its media entities. The views and opinions expressed in this episode are solely those of the creators and guests. For any concerns, please reach out to team@podroll.fm.
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