I've mostly been here for the sequences and interesting rationality discussion, I know very little about AI outside of the general problem of FAI, so apologies if this question is extremely broad.
These people seem confident deep learning and neural networks are superior to some unspecified LW approach. Can anyone give a high level overview of what the LW approach to AI is, possibly contrasted with theirs?
There isn't really a "LW approach to AI," but there are some factors at work here. If there's one universal LW buzzword, it's "Bayesian methods," though that's not an AI design, one might call it a conceptual stance. There's also LW's focus on decision theory, which, while still not an AI design, is usually expressed as short, "model-dependent" algorithms. It would also be nice for a self-improving AI to have a human-understandable method of value learning, which leads to more focus diverted away from black-box methods.
As to whether there's some tribal conflict to be worried about here, nah, probably not.
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