TalkChess.com

Jesse Gersenson wrote:Starting a little earlier lets you see, and hear!, the placing of the stone and the reaction of the 9-dan pro:
https://www.youtube.com/watch?v=l-GsfyVCBu0&t=1h17m40s

He looks at the board. Then looks again and scowls. Then checks the board a 3rd time before placing the stone. Then checks it a few more times.

That Sedol left the room after a very surprising move isn't surprising. FIDE rules don't allow such behavior, but it's well known that after the opponent plays a startling move you need to regroup your thoughts and then begin looking at the position calmly to find the ideas beyond it.

Listening to his commentary, it seems to me (speaking as the dreaded "instant expert" ) that a player is basically either fighting in a region of the board or building a framework that can later become territory (though they have also been saying that good moves achieve more than one thing).

What seems to have happened was that Sedol thought he could construct some framework quietly enough that AlphaGo wouldn't notice, but was then shocked to see AlphaGo unexpectedly attacking an important piece of this framework.

Laskos wrote: I don't know why 1600 ELO engines like Crazy Stone and Zentih show a plausible advantage fairly early in the game of 3500+ ELO opponents, while 3000-3400 ELO points 9 dan pro commentators seem to be so confused. Maybe these MCTS "weak"engines only seem to be correct, but for wrong reasons.

do you know if they are able to 'justify' their evaluation by winning in self play ?

Henk wrote: I don't see much resemblance between Chess and Go.

That's probably reason why also Chessbase is now informing about the match:

http://en.chessbase.com/post/computer-b ... ofessional

Anyways: the techniques used by alphago team are even more relevant for computer chess discussion than for pure chess discussion (which in its self - even chessbase thinks is justified).

Not to mention that the chess engine "Giraffe" got many people over here interested due to its highly innovative nature and that engine uses some similar ideas to alphago.

At this point no one knows for sure if machine learning will sometime in the future cause a breakthrough in chess engines strength. Yet we know that there are certain typical weaknesses in how engines play which are difficult to address with traditional approaches and thus machine learning could potentially help with e.g.: play in closed positions, recognizing positions that are likely to be a fortress and then of course with better candidate moves assessment and thus more effective pruning.

So I guess the big question is: had the alphago team invested similar effort to mastering chess than they did to mastering go, how would the resulting engine strength compare to todays top "conventional" engines ?

Henk wrote:

MikeB wrote:

Henk wrote:I thought this website was about computer chess. If not I will soon publish my latest monopoly games here.

The top human GO player in the world playing a computer - no question it's on topic. Your latest Monopoly games - I don't think so - not even close.

I don't see much resemblance between Chess and Go. Otherwise start a new website AI Club. But I would like to keep computer chess in a separate division.

Obviously you known what this thread is about and you could simply ignore it. You might as well complain to Chessbase as well while you're at it. You are the voice of a single minority, the world does not revolve around you , let the people enjoy this once in a lifetime event in peace. It will soon be over.

duncan wrote:

Laskos wrote: I don't know why 1600 ELO engines like Crazy Stone and Zentih show a plausible advantage fairly early in the game of 3500+ ELO opponents, while 3000-3400 ELO points 9 dan pro commentators seem to be so confused. Maybe these MCTS "weak"engines only seem to be correct, but for wrong reasons.

do you know if they are able to 'justify' their evaluation by winning in self play ?

A Crazy Stone evaluation of 60%-65% gives maybe 90% probability of win in self-play, these are directly linked.

towforce wrote: My experience of playing human chess masters is that I think I'm doing better than I expected, then suddenly a win for the opponent emerges.

If Crazy Stone genuinely had a good evaluation, it would be able to beat human opponents. Maybe it is weak at evaluating the "frameworks" that will eventually become territory?

It might also be related to some deeper tactics too, from what I saw, these "weak" (much stronger than me anyway) engines lose large fights too to strong humans, so it's not clear to me whether the general assessment of the position is to blame for their weakness.

Kai, if you make a chart for game 3 please post it here. Thanks.

I awoke early, so I watched most of game 3. I found Michael Redmond's commentary annoying today.

I may be overestimating, but today it seemed as though about 3/4 of the time he was guessing the next player's move wrongly, and then doing variations from a position that the viewer could see was never going to arise because the player had already chosen a different move. Often the move after had already been done, making the analysis even more irrelevant.

At one point, they even had the analysis board position wrong because they had missed a move - and it took them several minutes to discover this.

They need an extra team member to give them a buzz when a move has been made, and a different kind of buzz when the move is different to the one expected.

Having said that, I do appreciate the value of having a 9-dan English speaking commentator, and I do understand that high level board game players do tend to analyse by doing variations.

towforce wrote:I awoke early, so I watched most of game 3. I found Michael Redmond's commentary annoying today.

I may be overestimating, but today it seemed as though about 3/4 of the time he was guessing the next player's move wrongly, and then doing variations from a position that the viewer could see was never going to arise because the player had already chosen a different move. Often the move after had already been done, making the analysis even more irrelevant.

At one point, they even had the analysis board position wrong because they had missed a move - and it took them several minutes to discover this.

They need an extra team member to give them a buzz when a move has been made, and a different kind of buzz when the move is different to the one expected.

Having said that, I do appreciate the value of having a 9-dan English speaking commentator, and I do understand that high level board game players do tend to analyse by doing variations.

Just as a counterpoint.. I watched games 2 and 3 live, but I'm not a Go player, and I found his commentary very interesting and useful to be able to even vaguely follow what was going on in the game. I don't think his predictions were as off as you imply--it seemed to me that he called the right move at least half of the time. There were a bunch of times when he predicted the right move immediately, and then spent 1-2 minutes discussing some variation he thought might be interesting, even if it didn't involve that move (e.g. to explain to the audience why an alternate move would be bad and thus unlikely to be played). I'd also say the analysis wasn't "irrelevant" even if the game had moved on beyond that point already (which we could see for ourselves on the stream anyway). He was speaking mostly to an audience of amateur players and non-players, so playing out variations was useful to show us why his instinctive reactions were mostly justified. As a viewer I think that cutting him short mid-sentence to restart on the next position, and then likely cut that one short too, would not have been better.

Since Lee Sedol was in time pressure for a while in the 2nd half of both games 2 and 3, he always moved within 60 seconds and sometimes much less. On several occasions, it was obvious that Chris Garlock had glanced at the actual game position and knew that a move or two had already happened, but did not want to interrupt Michael in the middle of his analysis of how some variation might play out, and I think I preferred that. Sometimes Michael obviously knew a move had happened too, but wanted to finish his explanation before returning to the game position.

Anyway, it was amazing to watch a match of such a high skill level, and without Michael Redmond's commentary it would have been completely inaccessible to me, so I appreciated it quite a lot.

Jesse Gersenson wrote:Kai, if you make a chart for game 3 please post it here. Thanks.

Yes, today I put Crazy Stone in real time analysis, and it gave a pretty significant advantage to AlphaGo right in the opening fight in the upper-left corner, much earlier than Redmond started to say that AlphaGo is better. Then on, it proceeded smoothly with an increasing advantage of AlphaGo, decreasing only slightly when AlphaGo decided not to cut the left group of Lee, probably seeing a surer way to win.

Game 3: