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@jitendramalikcv
Prof, EECS, UC Berkeley. VP & Distinguished Scientist, Amazon. Elected NAS, NAE, FRS. https://en.wikipedia.org/wiki/Jitendra_Malik
AI
A post highlighting UC Berkeley work argues that visual imitation followed by trial and error is a good recipe for robots—and questions where that leaves teleoperation.
AI
A user sees large-scale real2sim—bringing the real world into simulation—as within reach, noting how hard it once was to imagine OpenAI putting serious resources into 3D/4D.
AI
A researcher describes work across Gemini, Omni and generative media to test ideas about physical AI, arguing that language models remain indispensable.
AI
A post introducing AgentSTAR describes an agent-based method for reconstructing and tracking jointed objects from single-camera video. It claims tracking can handle rapid motion, objects largely hidden from view and thin objects.
AI
One post connects the question of knowledge’s usefulness to the step-by-step automation of knowledge production.
AI
A reply says language models could improve with a closed feedback loop, accurate task checks and safety guardrails—but argues the system needed for that setup is still far off.
AI
The foundation model performs unseen long-horizon tasks through in-context learning.
