Another failure mode for deep learning, precisely anticipated by my 2001 book, The Algebraic Mind.https://www.newscientist.com/article/2198761-deepmind-created-a-maths-ai-that-can-add-up-to-6-but-gets-7-wrong/ …
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No bet on timeframe, but I will predict that progress will require something that directly maps onto symbol-manipulation, as articulated in my 2001 book.
@geoffreyhinton care to bet? -
I suspect you need to be more specific to what capabilities are missing. This will align with what many researchers are seeking. Example: is analogy making sufficient or is something else needed? I've at least have a model that captures this.
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I’ll bet
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On which side?
End of conversation
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It is a stupid idea to think AI just solves problems, you are not capable of. It is not a magic cube, it's software, which means, it does what the programmer intended. While surprising results are not a sign of intelligence, but a sign, that the inventor did not understand.
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The old "machines cannot be intelligent because computers can only do what the programmer tells them"?
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