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AlphaGo beats Lee Sedol again in match 2 of 5

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Re: AlphaGo beats Lee Sedol again in match 2 of 5

#342

Earlier quoted context omitted.

And yet the operative fact is that a human could not execute those calculations in a lifetime.

So what? Doesn't change the facts. There is no child here. There is a set of deterministic calculations written by some people, and executed.

I agree with EliRivers.

I'm pretty sure that if I wrote a child from scratch (AGCTTAACGGUAA ... etc), understood the underlying mechanisms connecting proteins to wining a baseball tournament ... I should get some credit for the win :)

There is no insight in making a child (can be done totally drunk and half passed out), although there is some in education.

Re: AlphaGo beats Lee Sedol again in match 2 of 5

#343
post #239

As someone who studied AI in college and am a reasonably good amateur player, I have been following the matches between Lee and AlphaGo. AlphaGo plays some unusual moves that go clearly against any classically trained Go players. Moves that simply don't quite fit into the current theories of Go playing, and the world's top players are struggling to explain what's the purpose/strategy behind them. I've been giving it…

I want to thank you for this comment. It's this kind of subtle, low-key, informed speculation that generates good, hard sci-fi concepts, which are absolutely relevant to my WIP novel.

"oh what if the machine suddenly came alive!?" has been done 1000 times. But such concepts like: a computer can detect and act patterns which we cannot, in ways that are almost, if not possibly intelligence, are magnitudes more believable, and therefore, compelling.

Thanks! :-)

Re: AlphaGo beats Lee Sedol again in match 2 of 5

#344
post #239

As someone who studied AI in college and am a reasonably good amateur player, I have been following the matches between Lee and AlphaGo. AlphaGo plays some unusual moves that go clearly against any classically trained Go players. Moves that simply don't quite fit into the current theories of Go playing, and the world's top players are struggling to explain what's the purpose/strategy behind them. I've been giving it…

Can you give an example of an "unusual" move? I'm a (very) novice Go player, and I think it'd be really interesting to see some specific commentary on how the machine is playing the game.

Re: AlphaGo beats Lee Sedol again in match 2 of 5

#345
post #239

As someone who studied AI in college and am a reasonably good amateur player, I have been following the matches between Lee and AlphaGo. AlphaGo plays some unusual moves that go clearly against any classically trained Go players. Moves that simply don't quite fit into the current theories of Go playing, and the world's top players are struggling to explain what's the purpose/strategy behind them. I've been giving it…

> It's both exciting and eerie. It's like another intelligent species opening up a new way of looking at the world (at least for this very specific domain). and much to our surprise, it's a new way that's more powerful than ours. I have been watching Myungwan Kim's commentary for the games - and it seems notable that a few moves he finds very peculiar immediately when they are made, he will later point out to as achi…

It seems that you are trying to create a new word that describe this new way of looking at the world. If human are able to decode the information contained in those unexpected moves, perhaps by creating a new heuristic, that could be viewed as a way of understanding the features the machine use internally, that is reading the machine brain. If human are able to decode that information creating new heuristics we could say that we are in a new state in IA in which learning among different intelligent species should be studied.

Re: AlphaGo beats Lee Sedol again in match 2 of 5

#346
post #239

As someone who studied AI in college and am a reasonably good amateur player, I have been following the matches between Lee and AlphaGo. AlphaGo plays some unusual moves that go clearly against any classically trained Go players. Moves that simply don't quite fit into the current theories of Go playing, and the world's top players are struggling to explain what's the purpose/strategy behind them. I've been giving it…

I think an important point was brought up by the Google engineer in the beginning of the game: Humans usually consider moves that put them ahead by a greater margin and base their strategies on that, while computers don't have that bias.

Building on that, I suspect that if AlphaGo thinks it has a 100% chance of winning with any of several moves, it has no way of distinguishing between them and chooses effectively at random. The longer that goes on - and once it hits 100% chance of winning, it will be that way for the rest of the game - the more chances it has to pick bad moves. As long as the move isn't bad enough to ruin its 100% chance of winning, it can't tell the difference between that and a good move.

(This also applies without a 100% chance of winning, as long as its chances of winning hover near the highest percent it's able to distinguish.)

Re: AlphaGo beats Lee Sedol again in match 2 of 5

#347

Earlier quoted context omitted.

> AlphaGo plays some unusual moves that go clearly against any classically trained Go players. Moves that simply don't quite fit into the current theories of Go playing, and the world's top players are struggling to explain what's the purpose/strategy behind them. Could AlphaGO be winning in a way similar to left handed fencers having an advantage over right handers by wrong footing them rather than simply being bett…

Seems unlikely. Training was partly from human games, and partly from self play; if there's some new, off book heuristics at play, there's no way to know that humans would respond poorly to them. Though I suppose it's possible it would notice that humans do poorly on simply off book moves generally.

Why does this seem unlikely? Humans do poorly with "off book" moves in general in sports and other games; it's why new styles of play or management work really well until others get used to them. Why would it be unlikely in Go?

Re: AlphaGo beats Lee Sedol again in match 2 of 5

#349
post #283

Earlier quoted context omitted.

I disagree. Art is mostly not a "problem" to be "solved" by science. Art is not graded in a scale of difficulty, from "easy" to "harder" art that mankind has to gradually reach. Literature is not a lower form of art that we must strive to automate so that we can dedicate ourselves to more "complex" forms. You are confusing the unknown with art.

You confused the problem statement. What is being solved is "how do we created an AI that can produce art" not "art"

Maybe. That's definitely not how I read it. Example:

> If an AI won the next Hugo award, I would be rejoiced. It wouldn't mean the end of literature at all; it would mean that humans are ready to produce an even higher form of literature.

To me this seems to be claiming that what we have now is a form of "lower" literature, to be tackled by AI so that humans can produce "an even higher form of literature". But, of course, literature isn't graded in a scale of "low" to "high". (Well, there is lowbrow and highbrow, but that's something else).

The mention of medicine as "holy art turned into boring science" (already somewhat dubious) also seems to point to the idea that it is art that's being "solved". But I admit I might have misread it.

By the way, I don't rule out that art can be produced by an AI (whatever that means). I subscribe to the notion that art is in the eye of the beholder, so if humans can find meaning in something produced by a non-human, that's probably valid art!

Re: AlphaGo beats Lee Sedol again in match 2 of 5

#350

I don't get the mystery of this. This algorithm is complex. SURE! But deep learning is very fast training / repeatition of a game (or some other goal) while saving the good or bad results. Predict user moves. Find good positions/patterns. Or did i miss some here? https://web.archive.org/web/20160128151110/https://storage.g...

Yeah...AlphaGo has played more games in the last few months than a human will in their life time.

I'd be interested in how strong it would be if given the same constraints as human learning (playing thousands of games, rather than millions).

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