I was replying to @Grady_Booch. Yes, even the biggest “deep learning “ systems are still majority standard hand-coded software. But how much of that uses “AI” methods (symbolic inference, SAT solvers, etc.)? Google solved an eigenvalue problem...
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yes, i do believe human brains have innate capacity for manipulating operations over variables, see eg my 1999 infant experiments reported in science, extended to newborns by Gervain, plus theoretical arguments in Algebraic Mind
but i also believe that symbol manipulation can be implemented i neural networks; whole point of algebraic mind was to consider solutions
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The majority of DL community will tell you that this 'algebraic mind' can be trained via gradient descent. In fact, that's exactly what the NLP community is doing. Graph Networks have explicit structural features that aid reasoning. Time leads to richer methods.
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DL inspired methods continue to make spectacular progress in many areas that you would describe as 'symbolic manipulation'. This kind of 'symbol manipulation' is radically different from how GOFAI works. GOFAI failure is to believe that AGI can be driven top down.Bottom up works!
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