Open letter to @ylecun: I have been explicit that I believe that symbol-manipulation is part of the solution to AGI; Hinton has ridiculed that idea. Where do you fit in? With me? W Hinton? If in between, where? The field would benefit from a clear statement of your view.https://twitter.com/tabithagold/status/1070736319901519876 …
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Replying to @GaryMarcus
I have expressed my position on this many, many times (including in the recent book "Architects of Intelligence"). But you still seem misunderstand it every time and to insist that we disagree, when we don't actually disagree that much. I'm tired of wasting my time.... 1/2.
3 replies 14 retweets 99 likes -
Replying to @ylecun @GaryMarcus
... but here we go again 1. Whatever we do, DL is part of the solution 2. Hence reasoning will need to be compatible with DL 3. That means using vectors instead of symbols, and differentiable functions instead of logic. 4. This will require new architectural concepts. 2/2
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Replying to @ylecun @GaryMarcus
...continued 5. The argument that "DL sucks" is simply wrong. DL is gradient-based optimization of multi-module system. That is not going away. 6. Supervised and reinforcement learning as they exist today are insufficient. .....
3 replies 6 retweets 42 likes -
Replying to @ylecun @GaryMarcus
... 7. Something like self-supervised learning is necessary. Now.....
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Replying to @ylecun
Agreed, though we differ in what see as the answer there.
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Yes, I proposed using vectors to represent the values of variables - while incorporating explicit operations over those variables — in 2001 book The Algebraic Mind, and have pointed to work that does essentially that (with clever innovations I didn’t consider).
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Geoffery Hinton explains the difference between symbolic AI and deep learning to great applause from the