What's Your Problem? Teaching Robots How to Do Everything
Jun 5, 2025
Chelsea Finn, a Stanford professor and co-founder of Physical Intelligence, dives into the fascinating world of teaching robots to perform everyday tasks. She discusses the current limitations of AI in manipulating objects, even for simple chores like laundry folding. Chelsea emphasizes the complexities of training AI models, mentioning a case study on the Pi 0.5 model for household tasks. The conversation also covers the delicate balance between generalist and specialized robots, the ethics of robotics, and the importance of tactile feedback in robot design.
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Complexity of Basic Motor Skills
- Motor skills feel simple but are extremely complex for robots and AI.
- The lack of extensive data on motor control makes developing robot autonomy difficult.
Data Scarcity for Robotics AI
- Robots lack the data abundance that language and vision models benefit from online.
- Videos alone are insufficient to teach motor control since they don’t convey precise action.
Teleoperated Data Collection
- Operators use teleoperation to control robots with lightweight arms like puppets.
- Teleoperation captures synchronized video and motor commands to create training data.