Generality in AI (which a matter of degree, not an absolute) is an v. important problem. Yet, strangely, the people who say they work on "AGI" don't seem to be interested in understanding the problem of generality, & instead focus on achieving task-specific skill by scaling up DL
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‘Just a little more driving data...’
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That was one of your best threads!
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I can not believe that professionals believe this, in my opinion the neural network and not their weights should be adapted to learning in addition to maintaining what I learned, I only see as the only option that the network itself modifies its own code.
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I am implementing it now with
#metaprogramming and deep reinforcement learning at the compiler level, especially in activations and rectifiers
End of conversation
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