(Thread) On the heels of the recent @GaryMarcus & @ylecun Twitter "debate", here's one of my gripes. I find myself constantly frustrated in any deep learning vs. symbolic debate because symbol pushers tend to claim ownership over capacities like "reasoning".
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In the worst instances reasoning *capacities* and symbolic *mechanisms* are entirely conflated. In less pernicious instances reasoning capacities are presumed to require symbolic methods.
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Symbolic methods do indeed have properties that would be useful for reasoning, including a natural propensity for compositionality. But these useful properties are not "owned" by symbolic methods -- they are properties that learning-based methods can have too!
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And let's not forget the decades of history showing why symbolic methods are ultimately insufficient, with the symbol binding problem being near the top of the heap.
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question is why they were insufficient, and whether remedy is to replace symbols or bring them together (as i have suggested) other methods
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