The thing with pointing out "AI can't do X!" is that, if you keep refining X into something narrow and precise enough, you'll eventually cross a threshold where a realistic amount of engineering and training data make X possible.
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No matter how stupid the student, they can always pass the exam if you give them a set of problems very similar to what they will be tested on (reduced task uncertainty), and if they're willing to spend countless hours studying them (more experience).
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What's hard is to improvise from little experience in the face of high uncertainty and novelty. That's what biological intelligence has evolved for. That's what current algorithms and models can't do at all.
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Explains why so many chatbot projects end up implementing IF/THEN statements: super narrow requirements, no need for training an AI (on often non existent data) and trivial for humans to describe
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Where is it from?
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Agreed. And at least with respect to many professionals' judgments, the thing about "refining X into something narrow and precise" is that you'll probably find you've made so many compromises and simplifications that you've redefined (rather than automated) X.
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In the end AI works with proxies and a proxy is not the same as whatever it proxies (and if it is, your AI may be memorising instead of ‘understanding’)
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(biological organisms are inherently incapable of having 'little experience', subsisting as they do in an unbroken continuum of experience across all life of common origin and back to that origination.)
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Well, yes, but it's severely compressed.
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I suppose, then, the question becomes: How long until AI algorithms have proliferated and iterated to the point that they have been "taught to the test" for virtually every conceivable situation? A functional facsimile of general intelligence, even if technically it isn't?
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i.e., the world is its chess match?
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