4 ms·
It seems analogous to Searle's "Chinese Room" argument: automated responses to predefined stimuli isn't the same as "intelligence" or "understanding". The OP s
by twblalock 7y ago
It seems analogous to Searle's "Chinese Room" argument: automated responses to predefined stimuli isn't the same as "intelligence" or "understanding".
The OP suggests modern AI is a fancy way of teaching systems to effectively hardcode or automate their behavior themselves.
I'm not sure why that matters, as long as the results are what we aim for. It's not like most AI researchers are trying to create sentient artificial life-forms.
- mattkrause 7y agoIt matters because the hard-coded behavior is brittle and often doesn't do exactly what we want (or think). For example, GPT-2 has been ascribed nearly magical powers: it's a knowledge base, it can play chess, it does calculus, it's a dessert topping AND a floor wax! When you look closer, however, it doesn't do any of those things particularly well. It can regurgitate something that looks like a true fact--or its negation with equal probability. It doesn't quite know the rules of chess. It needs a solver to check that the solution to an integral is, in fact, a solution.
- whatshisface 7y agoAll of those caveats apply to human intelligence, but to a lesser degree. Kids can play chess without exactly knowing the rules, and come on, everybody needs to check their integrals.
- TeMPOraL 7y agoBut kids can eventually learn proper algorithms for chess and integrals. DNNs cannot. In a sense, deep learning is like slide rules - you can squeeze some problem domains into giant, funny looking lookup tables, but generalize it does not.
- taurath 7y agoInterestingly though, at the population level it can seem a lot closer.