Let's say AlphaGo can beat all the best human Go players. Then what will the next more difficult game for computers to compete against humans and win?
Total War
AlphaGo beats Lee Sedol again in match 2 of 5
531–540 of 576 posts
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#532Earlier quoted context omitted.
I follow neither Go nor martial arts, but there seem to be some interesting parallels here with some emotional reactions to what appears to be the relative weakness of karate or kung fu versus grappling in UFC. The mystical aura of these martial arts as traditionally practised for hundreds of years suddenly falls away in the face of what often seems like brute force.
In fairness, UFC fairly severely limits what can be done. To begin with, they use gloves, and things like eye gouges and finger locks are illegal. Because strategies like "ripping out someone's intestines" are illegal, boxing and wrestling have an unfair advantage because they don't have to worry about that stuff to begin with. For more realistic fighting situations, see: https://en.wikipedia.org/wiki/Lei_tai
Small correction: they didn't use gloves in early tournaments.
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#533Earlier quoted context omitted.
you're confusing performance with the underlying intellectual property (e.g., the published song)
It's the same fungibility argument though. The market for sheet music for Willie Nelson's catalog isn't affected by the availability of other music, is it? If I want to play On the Road Again , there's only one IP owner for that.
oh got it, good point. yeah there is low substitute effect
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#534Earlier quoted context omitted.
Actually this AI kind of confirms these myths, since its basis are not in mathematics but in neural networks. While it could be argued to be just math, so is the brain, but that's besides the point. The point is, even the programmers have no idea what the AI is thinking. The way it picks moves is very similar to how top professionals do. Intuition is reduced to memories stored vaguely as neural connections.
I fear this is an overly mystical misinterpretation of neural nets. (Standard feed-forward) neural nets are layers of non-linear feature transformations. They take inputs and at each step transform those inputs into a more compact representation, distilling the inputs into their most important factors (and throwing away unimportant factors). So the most likely explanation is that policy/value nets in AlphaGo have lea…
I fear this is an overly mystical misinterpretation of neural nets.
Isn't most human experience an overly mystical interpretation of physics/chemistry?
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#535Earlier quoted context omitted.
The AI is based on the minimax algorithm [1]. Because of the way Minimax works, the only way for a possible next move to be designated a "win" is if it is a guaranteed win. (The tree is (effectively) fully explored, and the opponent is given the benefit of the doubt in the face of incomplete information.) So, if there are multiple such winning moves, and care is not taken to distinguish the "magnitude" of the win, th…
But once you have guaranteed winning moves, why not pick the shortest one available (in terms of turns)?
Yes, that's what I did after I found the design flaw which effectively threw that information away.
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#536This will be buried by now but: What happens if the Go master tries to deceive the oponent? As in purposefully play a counter-intuitive position, or even "try to lose"? Will the AI's response be confused as it is expecting rational moves from its oponent?
No. There is a scoring heuristic that AI programs use to determine if they are winning or not - ie: +2 stone ahead, -2 stones behind, etc. (Note: I don't actually know what the real heuristic is, I'm making it up). A computer will have no real reaction to a "try to lose" or counter intuitive move; it would merely recalculate the heuristic score and doing exactly what it has been doing all along - finding the next move that maximizes that score.
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#537What is interesting to me is that the computer makes clear mistakes when its on the lead. Since it might find the chances to win equally among different scoring results, it often picks a weaker one. This has a powerful consequence: we have not seen AlphaGo pushed to the limit, he is lowering the distances as if it were playing a teaching game. Lee Sedol I think came to this conclusion, and the only human strategy lef…
>What is interesting to me is that the computer makes clear mistakes when its on the lead. Since it might find the chances to win equally among different scoring results, it often picks a weaker one.
When they interviewed the devs briefly, they said this is because AlphaGo doesn't really consider the score other whan winning, so it will pick a move it think is an 81% chance to win by one stone over an 80% chance to win by 10 stones. When it's ahead these moves can look like mistakes but a better way of describing them would be hedging.
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#538As 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's also possible that the positional evaluation is strong enough that AlphaGo can see the value in a position before the human because of the complexity involved in determining the "value" of a given position.
My experience is with Chess and Chess AI, but in my experience, the more positional knowledge built into the evaluation function, the better the search performs, even if you have to sacrifice some speed for more thorough evaluation. A significant positional weakness may never be discovered within the search horizon of a chess engine because it may take 50 moves for the weakness to create a material loss, so while it's certainly possible that a deep, but carefully pruned search is being utilized, I suspect that some of the Value Network's evaluation is helping to create some of these seemingly odd moves.
For AlphaGo to recognize a position that doesn't achieve a good result for 20 moves, it would often have to search much deeper than those 20 moves (I'm not sure if you're using the term moves to mean ply or both players moving, but if it takes 20 AlphaGo moves for the advantage to materialize, that would be a minimum 40 ply search) to quiesce the search to the point that material exchanges have stopped (again, this is how chess typically does it, I don't know about Go), so the evaluation at the end of the 20 move sequence is arguably more important than a deep search. The sooner you can recognize that a position is good or bad for you, the more time you have to improve the position.
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#539Earlier quoted context omitted.
I'm not a Go player but play other competitive sports. Humans have a herd mentality...as Op mentioned there's certain styles of playing...which has their own strengths and weaknesses. Sometimes people will not examine other styles that may have better strengths and just focus on the exist one. Then comes along someone who 'thinks outside the box' with a new style and revolutionize the playing field. Think Bruce Lee a…
Lee isn't even the best human player at the moment, he has a 2-8 loss record against Ke Jie, who's actually ranked number 1 at the moment. Ke Jie is an arrogant 18 year old and he's been saying on social network in the past couple days how he will defeat AlphaGo.
He seems to have backed off that claim after the second game.
Re: AlphaGo beats Lee Sedol again in match 2 of 5
#540I wonder how "smart" the AI can become once Lee Sedol starts pattern matching and playing against its moves better.