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Gunnar_Zarncke comments on [Link] AlphaGo: Mastering the ancient game of Go with Machine Learning - Less Wrong Discussion
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Comments (122)
I actually think self-driving cars are more interesting than strong go playing programs (but they don't worry me much either).
I guess I am not sure why I should pay attention to EY's opinion on this. I do ML-type stuff for a living. Does EY have an unusual track record for predicting anything? All I see is a long tail of vaguely silly things he says online that he later renounces (e.g. "ignore stuff EY_2004 said"). To be clear: moving away from bad opinions is great! That is not what the issue is.
edit: In general I think LW really really doesn't listen to experts enough (I don't even mean myself, I just mean the sensible Bayesian thing to do is to just go with expert opinion prior on almost everything.) EY et al. take great pains to try to move people away from that behavior, talking about how the world is mad, about civiliational inadequacy, etc. In other words, don't trust experts, they are crazy anyways.
What would worry you that strong AI is near?
This is a good question. I think lots of funding incentive to build integrated systems (like self-driving cars, but for other domains) and enough talent pipeline to start making that stuff happen and create incremental improvements. People in general underestimate the systems engineering aspect of getting artificial intelligent agents to work in practice even in fairly limited settings like car driving.
Go is a hard game, but it is a toy problem in a way that dealing with the real world isn't. I am worried about economic incentives making it worth people's while to keep throwing money and people and iterating on real actual systems that do intelligent things in the world. Even fairly limited things at first.
What do you mean by this exactly? That real world has combinatorics problems that are much wider, or that dealing with real world does not reduce well to search in a tree of possible actions?
I think getting this working took a lot of effort and insight, and I don't mean to discount this effort or insight at all. I couldn't do what these guys did. But what I mean by "toy problem" is it avoids a lot of stuff about the physical world, hardware, laws, economics, etc. that happen when you try to build real things like cars, robots, or helicopters.
In other words, I think it's great people figured out the ideal rocket equation. But somehow it will take a lot of elbow grease (that Elon Musk et al are trying to provide) to make this stuff practical for people who are not enormous space agencies.