What really is at stake in current debates about deep learning & AI? A reply to #deeplearning pioneer Yoshua Bengio.https://link.medium.com/pFZy4GfpJ0
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if you're not advocating for a "simple hybrid" between symbolism & connectionism, then can you please point to a single implementation that: a) is representative of the thing you have in mind, and b) succeeded on a challenging task that has escaped a pure DL system?
the more general answer is that what i want does not yet (reliably) exist: the kind of thing that lets a human recognize a zebra after being told it is a horse with stripes, or manipulate a grater once told the logic
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There's an assumption here that this "thing" must be a hybrid, since the behaviour you outlined does not constrain the mechanism. It's fully possible that a purely connectionist model can accomplish this behaviour.
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Also, there's a bait and switch with your argument. You advocate for a more "subtle" hybrid system when criticizing the "simple" hybrid, but you only describe this mystery system by what it can do, not its implementation. Implementation is the point of contention, not capacity
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The goal shouldn't be to achieve the perceived properties of (conscious!) thought. But it should be to acheive the outcomes of (any level) thought - the ability to learn to create causality in the real world. Bc. otherwise, it's just building an artificial bird to acheive flight.
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