Re:Why are deep learning technologists so overconfident?
by danaris on Thursday September 01, 2022 @09:36AM
(#32676037)
I think it's important to distinguish between something that's a "dead end" in that it will take you nowhere interesting, and something that's a "dead end" in that it will, after a certain point, cease advancing.
The former would imply that there is no point using deep learning and other similar techniques at all, and is the common implication when people say something is a "dead end".
The latter is what I believe the current generation of machine learning to be: I do not believe it will lead to AGI, and I am skeptical that it can do a great deal more than what it has already done (it can continue to refine the types of things it already does, and I expect it to do so, but I don't think it will open up new categories of things it can do many more times). But despite that, it does do some very cool things now, and as they are refined, I think they can be commercially successful and generally beneficial tools.
The former would imply that there is no point using deep learning and other similar techniques at all, and is the common implication when people say something is a "dead end".
The latter is what I believe the current generation of machine learning to be: I do not believe it will lead to AGI, and I am skeptical that it can do a great deal more than what it has already done (it can continue to refine the types of things it already does, and I expect it to do so, but I don't think it will open up new categories of things it can do many more times). But despite that, it does do some very cool things now, and as they are refined, I think they can be commercially successful and generally beneficial tools.