Noam Chomsky on Where Artificial Intelligence Went Wrong
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Noam Chomsky on Where Artificial Intelligence Went Wrong
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Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#2Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#3Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#4If you're interested in this area, which you might call the philosophy of artificial mind, or philosophy of cognitive science, I strongly suggest reading the link to Norvig's article (linked in TFA, but here it is again: http://norvig.com/chomsky.html ). In particular, I'd suggest reading it before reading the actual interview with Chomsky (maybe ideally reading it after the prefatory part of TFA).
My own inclination is that on the face of it, I find Norvig's approach less satisfying, as Chomsky appears to, but upon much consideration my current belief is that Chomsky's approach is too mystical and too just-so, and Norvig's approach at least has the merit of bearing fruit... fruit that one day might be concentrated into a concise and elegant theory.
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#5Norvig on Chomsky: http://norvig.com/chomsky.html
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#6Chomsky seems to keep using naïve models as a strawman, and Norvig rightly calls him on it. If you use simple models, you can only get simple insights, but statistical machine translation (for example) builds probabilistic context-free grammars, which maps human notions of language far better than "make sure every three words in sequence is plausible".
Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#7Re: Noam Chomsky on Where Artificial Intelligence Went Wrong
#8I haven't finished reading TFA yet, but so far it's really good, because it sounds like Chomsky is actually getting to the point.... which he sometimes does, and sometimes absolutely doesn't (or so it often seems to me). If you're interested in this area, which you might call the philosophy of artificial mind, or philosophy of cognitive science, I strongly suggest reading the link to Norvig's article (linked in TFA,…
You can hardly blame the AI researchers for sticking with methods that have been very successful (at least practically speaking) after they had their funding cut out from under them in the 90's for the perceived "failures of AI".
I do like the idea of developing a theory (e.g. vision is processed via algorithm in the brain represented by X) and then attempting to find evidence of that. It can help to avoid the reductionist idea that you need to model everything down to the cellular level in order to understand the brain. It's like trying to disassemble code in memory and then read the algorithm rather than examining every 1 and 0 in memory and trying to make heads or tails of them.
That's enough rambling from me..