How Close Are We to Robots That Can Do Anything? | Sergey Levine, Physical Intelligence

Sergey Levine, cofounder of Physical Intelligence, joins South Park Commons Partner Aditya Agarwal to discuss the race to build general-purpose robots that can learn new skills and operate in environments they've never encountered before. They talk about how Physical Intelligence is developing AI foundation models for robotics, what makes teaching robots so difficult, and how advances in reasoning and reinforcement learning are bringing us closer to robots that can perform a wide range of tasks. Sergey also explains why solving robotics may require tackling many problems at once, how robots could eventually learn from their own experiences, and what it will take to make truly general-purpose robots a reality. Sergey Levine: https://www.linkedin.com/in/sergey-levine-5a31a24/  Aditya Agarwal: https://www.linkedin.com/in/adityaagarwal3/  South Park Commons: https://www.linkedin.com/company/southparkcommons/  Apply to SPC: https://www.southparkcommons.com/apply Chapters: (00:00:28) - From Video Games to Robotics: Sergey Levine's Journey (00:04:24) - Founding Physical Intelligence: Why the Timing and Team Mattered (00:06:30) - Inside Pi Zero: Building a Foundation Model for Robots (00:09:37) - From Pi 0.5 to Pi 0.7: Teaching Robots to Reason and Generalize (00:16:45) - What Makes a Great Robotics Researcher (00:21:10) - Solving Robotics' Data Problem and Building Learning Feedback Loops (00:28:04) - The Future of Robotics: General-Purpose AI vs. Specialized Robots (00:33:24) - World Models, Data Strategy, and Building a Robotics Research Culture