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Frank van der Velde's avatar

Hi Gary,

I fully agree.

Case in point: deep learning architectures are designed. E.g. BERT is bi-directional, GPT uni-directional. This difference is not learned but preset ('inborn') to influence learning.

But it is interesting to ask if critical aspects of compositional cognition, e.g. the 'logistics of access' it requires, can be learned from a more basic architecture or need to be preset.

Best,

Frank van der Velde

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Saty Chary's avatar

Hi Gary, excellent article that lays out the two 'sides' :) Indeed, nurture won't be useful without nature.

Also - Bloom's Taxonomy offers a quite useful, graduated/hierarchical list of capabilities, that can serve to create tests against which to assess AI mastery. AI thus far has been stuck at the bottommost level :) :(

Also, seems to me that human learning stands apart from all others', on account of our innate abilities to represent happenings directly, ie gain body-based "experience", AND to represent things (direct experiences, objective knowledge...) symbolically as well. This duality lets us glide back and forth, lets us symbolize our knowledge and experience for others to pick up, and conversely, lets us benefit from others' symbolizations (going back to 1000s of years!). Other animals seem more limited in the 'direct <-> symbolic' mapping.

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