Everything is learned -- it's "merely" a question of the timescale of learning
Even in Artificial Intelligence, there's an ideological bias for nurture over nature. @GaryMarcus explains how @DeepMindAI spins its successes.https://medium.com/@GaryMarcus/deepminds-misleading-campaign-against-innateness-a2ea6eb4d0ba …
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If you call evolution by natural selection 'learning', then learning is so broad it's meaningless.
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Evolution generates new individuals based on old individuals modifying them ~randomly then selects the best ones and repeats. Mostly like trial and error.
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No. Individuals are vehicles for the replication of genes within a specific niche. There are no 'best oness', evolution is not a zero sum game. Unlike learning, the criteria for selection is not predetermined by some objective function, but instead exploits the adjacent possible
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see my book Kluge on this topic = imperfections in human cognitive system that derive from accidents in evolution, a la Gould’s classic Panda’s Thumb
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There's no place for "nature" in "artificial" intelligence. https://en.wikipedia.org/wiki/Genetic_algorithm …
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That’s not the problem either, bc we’re not close to the stage where speed per se is an issue in GAI- we can’t do the basics with any amt of computing power, though we can do many even perceptual things far better than humans...Innateness involves game rules, not just knowledge.
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Sure- a superset of learning including instinct?- fine, but what does that conflation buy us in GAI? If innateness is more like Chomsky’s miraculous black box, conflation is less imp than contrast and the related, ongoing search for Corpus Callosum-type interaction/synthesis.
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