What do you think about visualization with regard to cognition? How important?
Arguably, the main challenges of cognition are not even represented in classic supervised learning from big data -- exploration, goal-setting, open-endedness, abstraction, extreme generalization, learning from few data points...https://twitter.com/fchollet/status/947119817286438913 …
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Visual thinking is the mode of thought used to make many (most?) of the major advances in physics and math. From Faraday to Feynman the discoveries are made in the visual mode, and they are translated into formulas afterwords.
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It may help to figure out first how neural feedback in a biological brain works, and what its exact function is. Maybe the MICrONS initiative will help. As for machine learning + big data. It's practical in the real world, but has nothing to do with intelligence or even learning.
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accurate hierarchical learning and representations... the list can continue
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Arguably? Are you kidding? Supervised learning has absolutely nothing to do with general intelligence. There is nothing to argue, really.
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Something to ponder. Unlike deep learning networks, the human brain can instantly see and interact with a completely new object or pattern that it has never seen before.
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Gonna go out on a limb here and say that all the functions you listed, except maybe for exploration, can be learned in a supervised manner.
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That's a pretty limb you got there. Careful you don't fall off...
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That sounds right, except perhaps abstraction (we seem to get that for free with DL a bit) and learning from few examples (we've got a long way to go but supervised learning can represent this problem)
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So I'd be curious to know : are the remaining things you mentioned actually hard? E.g adding "curiosity" to an RL objective was pretty easy to do and helped exploration
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