Our field isn't quite "artificial intelligence" -- it's "cognitive automation": the encoding and operationalization of human-generated abstractions / behaviors / skills. The "intelligence" label is a category error
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The resource-intensiveness, naturally, comes from the lack of adaptability: you need to plan for every possible unknown, whether explicitly or via a dense sampling of possible situations (assuming a fixed distribution)
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intelligence is the ability to achieve complex goals in complex environment
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Is reinforcement learning going into a good direction? Adaptation via both experience and environmental stimula
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And it's even harder than that. The problem is not that we have a problem. The problem is that we have problems. So the solution is not finding a solution to a problem. The solution is finding a metasolution that is valid across time and tribes. Bam! the challenge of the universe
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Per this definition of intelligence, would that not mean perhaps only the earliest men experienced actual intelligence?
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Does the passing down of genetic information down from parents to offspring not imply that offspring are not entirely exposed to experiences without a frame of reference?
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If so, it means than, rather than adaptation to unknowns, intelligence is the ability, i. e. the computational complexity necessary to learn this classes.
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Very fascinating discussion. Are these classes of unknown really unknown or can they be reformulated as a unsupervised information representation learning problem so part of an underlying structure. Like the laws of physics.
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