"Inside Views, Impostor Syndrome, and the Great LARP" by John Wentworth episode artwork

EPISODE · Sep 26, 2023 · 8 MIN

"Inside Views, Impostor Syndrome, and the Great LARP" by John Wentworth

from LessWrong (Curated & Popular) · host LessWrong

Epistemic status: model which I find sometimes useful, and which emphasizes some true things about many parts of the world which common alternative models overlook. Probably not correct in full generality.Consider Yoshua Bengio, one of the people who won a Turing Award for deep learning research. Looking at his work, he clearly “knows what he’s doing”. He doesn’t know what the answers will be in advance, but he has some models of what the key questions are, what the key barriers are, and at least some hand-wavy pseudo-models of how things work.For instance, Bengio et al’s “Unitary Evolution Recurrent Neural Networks”. This is the sort of thing which one naturally ends up investigating, when thinking about how to better avoid gradient explosion/death in e.g. recurrent nets, while using fewer parameters. And it’s not the sort of thing which one easily stumbles across by trying random ideas for nets without some reason to focus on gradient explosion/death (or related instability problems) in particular. The work implies a model of key questions/barriers; it isn’t just shooting in the dark.So this is the sort of guy who can look at a proposal, and say “yeah, that might be valuable” vs “that’s not really asking the right question” vs “that would be valuable if it worked, but it will have to somehow deal with <known barrier>”Source:https://www.lesswrong.com/posts/nt8PmADqKMaZLZGTC/inside-views-impostor-syndrome-and-the-great-larpNarrated for LessWrong by TYPE III AUDIO.Share feedback on this narration.[125+ Karma Post] ✓

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Epistemic status: model which I find sometimes useful, and which emphasizes some true things about many parts of the world which common alternative models overlook. Probably not correct in full generality. Consider Yoshua Bengio, one of the people who won a Turing Award for deep learning research. Looking at his work, he clearly “knows what he’s doing”. He doesn’t know what the answers will be in advance, but he has some models of what the key questions are, what the key barriers are, and at ...

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