Levine: Easy Data Collection Makes Physically Intricate Robotics Tasks Easy
Sergey Levine · World's Top Researcher on AI, LLMs, and Robot Intelligence · Invest Like The Best · Mar 31, 2026 · at 25:32
Sergey Levine, co-founder of Physical Intelligence and UC Berkeley professor, explains how machine learning is modifying Moravec's paradox based on data availability rather than mechanical complexity.
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“And I think increasingly what we'll see is a shift where domains where collecting data is straightforward They actually end up falling into the easy bucket over time, even if they are physically intricate. But there will be domains where collecting data is difficult, where you need to use more common sense, where you need to reason at multiple levels of abstraction, connect physical skills that you've learned in other areas to knowledge that you've got from the web, and those will be tough, and that's where we'll, will need more technology advances.”
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