Generality in AI (which a matter of degree, not an absolute) is an v. important problem. Yet, strangely, the people who say they work on "AGI" don't seem to be interested in understanding the problem of generality, & instead focus on achieving task-specific skill by scaling up DL
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It seems to me that the greatest obstacle to making progress towards AI of increasing flexibility & breadth (up to some 'generality' threshold) is the fundamentally incorrect conceptualization of intelligence that is propagated by these sci-fi memes, which is now pervasive
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This is making it nearly impossible to have a conversion on this topic. Many people now think of "intelligence" as an intrinsic property of an algorithm, synonymous with "power over the world", that can be tweaked to reach arbitrarily high values. Like the height of a building
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And many people are, accordingly, waiting for some kind of philosopher's stone, or lamp genie, of infinite intelligence and therefore infinite power. They don't quite know how to create it, but presumably all you need to do is figure out the correct series of incantations
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Never mind that current AI algorithms have very close to zero flexibility and breadth today. We are at the "task-specific skills" stage (i.e. local generalization), and will stay there until we directly tackle to question of engineering broad, reusable cognitive abilitiespic.twitter.com/jkdH7Sdh6X
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End of conversation
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I often think about this. Would a piece of software that has multiple programs working together, each specialising in some narrow application of AI, be AGI? I think of this as 'smoke and mirrors', but on some level isn't this *kind of* how the brain functions?
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AGI was meant as a return to the goals of GOFAI because current DL has become focused on turning data into something you can profit from (yet claim to want an AI with abilities to match your first description). Please ignore anyone talking about the latter.
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Too hype exists with the word
#AGI, in addition to great ignorance
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