Robotics in-context learning too early? Research often 10 years ahead of industry
chris_j_paxton · x · 2026-08-30
Chris Paxton responded to the discussion around in-context learning for robotics. He described it as a classic research problem: seeing the right direction 5 or 10 years away but being unable to act on it scalably. He cited his early work on world models, which was directionally correct but remained a toy project due to immaturity. Similarly, in-context learning is picking up now only because a few big companies have started scaling it.
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