Of course, computational power isn't the real limiting factor for general #AI, anyway. We will need fundamental advances in understanding common sense knowledge and reasoning to achieve extrapolative AI rather than our current interpolative AI.https://twitter.com/Grady_Booch/status/1081740548627550209 …
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"Common sense" is knowledge about the everyday world. Do you think it is innate, or is it learned from experience? I'm betting on experience, at least for common sense about the physical world. 1/
some of it is obviously learned, but why would you think it is all learned, despite a billion years of evolution shaping neural development and a significant cognitive development literature on innateness?
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These are good points. I guess I was thinking about whether it COULD be done with a pure learning approach. Of course the most practical approach might be related to the Belbute paper I mentioned: wrap ML around a physics engine.
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I missed the note about the paper which sounds interesting – could you send a link perchance? Thank you
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“a billion years of evolution shaping neural development” aka learning.
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I don’t know about you, but I don’t have 1 billion years to wait for my GPUs to converge…
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Intelligence is finding fit in a complex environment with limited/ambiguous data and resources. Some of this is learning, most of it is not. Most is probabilistic reasoning + transfer learning. I honestly can’t believe we’re still debating this shit.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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