Computer vision pioneer Jitendra Malik on why machines still underestimate vision and must learn like children.

Jitendra Malik — A professor at UC Berkeley and one of the seminal figures in computer vision, both before and after the deep learning revolution. Cited over 180,000 times, he has mentored many world-class AI researchers.
Lex Fridman interviews Jitendra Malik, a foundational computer vision researcher, about why vision is far harder than it appears since most human visual processing is subconscious. Malik argues that perception is fundamentally tied to action and that current systems rely too heavily on supervised, feed-forward learning. He advocates for systems that learn like children: multimodally, incrementally, physically, and through exploration. The conversation spans autonomous driving skepticism, segmentation, 3D understanding, the limits of the Turing test, and the present-day risks of AI in recommender systems.
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