Blutorangensaft t1_iz92v1x wrote
Reply to comment by Phoneaccount25732 in [D] If you had to pick 10-20 significant papers that summarize the research trajectory of AI from the past 100 years what would they be by versaceblues
What is people's take on Minsky? Because the XOR issue is easily relieved with a nonlinearity, and I never understood why not knowing how to learn connectedness is a major limtation of neural nets. In fact, even humans have trouble with that, and I fail to see how that generalises. He may be an important figure, but not in favour of progress in artificial intelligence.
Of course, if the question is just about portraying important junctions in AI research, regardless of whether they were helpful or not, then Minsky belongs there.
ThisIsMyStonerAcount t1_iz9c2oo wrote
Minsky's work was very relevant because at the time the perceptron was the state of the art, and that algorithm can't solve XOR. That's why his work started the first AI winter.
Blutorangensaft t1_iz9pl46 wrote
I get that, but I find it a little hard to believe that nobody immediately pointed out a nonlinearity would solve the issue. Or is that just hindsight bias, thinking it was easier because of what we know today?
ThisIsMyStonerAcount t1_iza1qzy wrote
What nonlinearity would solve the issue? The usual ones we use today certainly wouldn't. Are you thinking a 2nd order polynomial? I'm not sure that's a generally applicable function, with being non-monotonical and all?
(Or do you mean a hidden layer? If so: yeah, that's absolutely hindsight bias).
Blutorangensaft t1_iza9zrt wrote
I see. I meant the combination of a nonlinear activation function and another hidden layer. Was curious what people thought, thanks for your comment.
chaosmosis t1_izawfsz wrote
Non-monotonic activation functions can allow for single layers to solve xor, but they take forever to converge.
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