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    Chris Paxton Posts on Human Edge Over AGI

    Robotics researcher Chris Paxton shares thoughts on human physical skills versus AGI.

    CP
    2 Sources, 27d ago, first seen 27d ago

    TLDR

    Chris Paxton, who leads AI at Agility Robotics and has prior roles at Meta FAIR, retweeted his own post replying to @EvanBuilt. In it he outlined one possible human comparative advantage over AGI: greater skill at physical tasks. He wrote that humans might perform better at such work because we have had bodies for a long time. The post offers no further details or predictions. No other sources or outcomes appear in the packet.

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    2 Sources, first seen 27d ago

    Combined views

    1.1K

    2 Sources, first seen 27d ago

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    2 comments
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    3 reposts

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    Positive——Negative

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    2 Sources

    @chris_j_paxtonThoughts on human comparative advantage over AGI: - we might be better at physical stuff. we've had bodies a lot longer than we've had brains. perception, picking out fine details, etc. - we're much more energy efficient, for what it's worth. - long horizon in-context reasoning is still something we're better at. like, really long horizon. days. - our learning process is, right now, MUCH more data efficient. perhaps this will change in the future, but due to economies of scale for AI inference not really allowing for test-time-training i think it also might not But the real answer is... i don't know. This is to some extent an article of faith based on the fact that our hardware is just ridiculously different.

    2 Sources

    @chris_j_paxtonThoughts on human comparative advantage over AGI: - we might be better at physical stuff. we've had bodies a lot longer than we've had brains. perception, picking out fine details, etc. - we're much more energy efficient, for what it's worth. - long horizon in-context reasoning is still something we're better at. like, really long horizon. days. - our learning process is, right now, MUCH more data efficient. perhaps this will change in the future, but due to economies of scale for AI inference not really allowing for test-time-training i think it also might not But the real answer is... i don't know. This is to some extent an article of faith based on the fact that our hardware is just ridiculously different.