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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Intelligence is adaption to unknown unknowns across an unknown range of tasks and domains. Automation is, at best, robustly handling known unknowns over known tasks (which is already incredibly difficult and resource-intensive in the real world -- whether engineering or data)
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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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cool story
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@threadreaderapp please compile -
Hola, you can read it here: Thread by
@fchollet: Our field isn't quite "artificial intelligence" -- it's "cognitive automation": the encoding and… https://threadreaderapp.com/thread/1214392496375025664.html …. Share this if you think it's interesting.
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Intelligence is ability to generalise and ability to learn new skills.
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We might very well be an autonomous abstraction generated by a superior lifeform. Your definition is circular as no point can be reached where you can say this organism is intelligent. Adaptability comes from encoded understanding of the world's mechanisms. 1/?
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The better your understanding/encoding of the world's mechanisms, the more intelligent, as the higher your ability to adapt, plan, and react. Intelligence should be measured by the correctness of the enc. of the underlying game mechanism. 2/?
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Hallo, the unroll you asked for: Thread by
@fchollet: Our field isn't quite "artificial intelligence" -- it's "cognitive automation": the encoding and… https://threadreaderapp.com/thread/1214392496375025664.html …. Share this if you think it's interesting.
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Adaptability of the lifeform is also resource intensive, randomly mutating genes and keeping only the better suited for "unknown unknowns". With cumulative cultural evolution it is not much different too. Adaptability seems to be the differentiator indeed. Random & nat selection!
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Genes (& books) are the automation part. Nat. selection (& research) is the hyper-adaptability part. Nature has both. The machines lack the autonomous-hyper-adaptability, same as autonomous abstraction generation. Algos are not fancy, but the computing platform is, the reality!
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