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Go grandmaster Shin defeats AI KataGo with a two-stone handicap

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Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#101

Post by snakeboy »

DiogenesKynikos wrote: post #71
hyperpape wrote: post #37

Earlier quoted context omitted.

You're right that Shin Jinseo is a generational talent, and more dominant than anyone since Lee Changho (peaked in the 90s and was strong into the early-mid 2000s). However, you can't compare goratings over time, the top ranks are not nearly stable enough. https://www.goratings.org/en/history/ (I think it's believable Shin Jinseo is better than Lee Changho, but not that there has been steady progress since the days o…

You can't compare Elo ratings over long stretches of time, period. Ratings drift over time, based on the total population of people competing. I think the most accurate way to view Elo ratings is as a measure of skill vs. the average rated player. If you want to compare Magnus Carlsen's peak rating of 2882 in the year 2014 to Garry Kasparov's peak rating of 2851 in the year 1999, you have to know how strong the total…

> If you want to compare Magnus Carlsen's peak rating of 2882 in the year 2014 to Garry Kasparov's peak rating of 2851 in the year 1999, you have to know how strong the total pool of players (including all the amateurs who compete at lower levels) was in the year 2014 vs. 1999.

I imagine that FIDE has all of this data somewhere, right? They don't publish more in-depth distributional analyses of players somewhere?

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#102

Post by [deleted] »

nottorp wrote: post #90
sermah wrote: post #81

Earlier quoted context omitted.

No. It’s not my first language too, but your version sounds odd. Usually you put an action first and only then the details

Trouble is, from the existing title it's not clear who had the handicap. So the poster is right to try and fix it.

[deleted]

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#103

Post by jrimbault »

ctchocula wrote: post #68

Given all the interest in sudden interest in go in this thread, anyone have a sure-fire method to improve at go from double-digit kyu to single-digit kyu and amateur dan level?

Handicap Go by Nagahara Yoshiaki helped me tremendously.

I started playing I believe in March of 2025. I had the very good luck that one of my high school best friends is a 4 dan EGF player, and was in the French team 20 years ago. We played constantly against each other with 9 stones handicap and him teaching me a lot.

But when I read that book, in a few weeks/months we went from 9 stones to only 3 stones by August 2025. and we have stayed at 3 stones since, playing very even games, with only a handful or couple of points differences. Only very recently did I win by 9.5 points. Which made me hope I had made new progress, but I had to resign in the very next game.

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#104

Post by kuboble »

matsemann wrote: post #98
EchoAce wrote: post #48

Earlier quoted context omitted.

You can think of joseki as “local opening”. Like, in a vacuum, this is known by study / AI to be an even result for black and white. It’s just like a chess opening, there’s no calculation up to a certain point. And it doesn’t exist in the midgame, it’s not similar to forced sequences which exist in both games; it’s much more like choosing French closed vs open or gambit/gambit declined. The one thing is (and this is…

Sounds like the counter is a strategy Magnus Carlsen has been known for in chess: get out of theory, probably on a bit weaker foot than the other player, to then crush them on raw power.

Yes, exactly.

The feeling among the go players I know is that the match had been kind of a setup for the human to win.

It's an equivalent of playing in chess with a bishop handicap and a computer playing deterministic chess so that a human can prepare a forced sequence into a winning endgame.

Shin is an absolutely amazing player and not anyone could have achieved that, but nobody really feels like he won vs a computer team that tried its best.

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#105

Post by kuboble »

Davidzheng wrote: post #73
thangalin wrote: post #16

In Go, there are exchanges of plays called "joseki". Professionals consider the outcome of joseki to be an equal result for both players. Most joseki are only a handful of moves, but some, such as the "flying knife" joseki have variations that continue for upwards of 50 moves. A traditional 19x19 go board has 361 intersections. Shin's genius was to play out a complex variation of the flying knife joseki that was, in…

In odds chess bots, the bots would willingly take more disadvantageous positions which are more complicated--probably the bots in GO which are trained for odds do similar? Why does it not avoid such a joseki & play a worse response which it believes the human cannot read?

Because the computer team in this match for some reason didn't do it. It was like a match vs vanilla stockfish at fixed depth rather than leela chess odds.

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#106

Post by Garlef »

geocar wrote: post #79
xhevahir wrote: post #23

> "This series taught me that rather than trying to imitate AI, it is far more important to build the board according to my own style." It's never made sense to me that so many go players study AI go play in the hope of emulating it in a human game. We're not machines. We can't do thousands of Monte Carlo tree searches per second.

> It's never made sense to me that so many go players study AI go play in the hope of emulating it in a human game. > We're not machines. We can't do thousands of Monte Carlo tree searches per second. You sound so sure of that, but I have seen people catch a ball, and I am not so sure that any artificial person should be any more aware of the tremendous maths they are "solving" From the perspective of a game with far…

> but I have seen people catch a ball

from what i remember, dogs sometimes run in curves so that the perceived trajectory of the object they try to catch is more linear

so not everything might be in-brain math but also good trickery

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#107

Post by Alpha3031 »

kadoban wrote: post #64
rudi-c wrote: post #14

Earlier quoted context omitted.

While AlphaGo originally only had win rate as a metric, modern Go AIs have more knobs, including an evaluation of "complexity". Just stating this off the top of my head so I could be misremembering, but I heard that the KataGo settings used were tweaked to favor complexity. This was most apparent in Game 1 which Shin Jinseo lost, where the AI had an unusual opening. However, the last game was quite plain leading me t…

There are tweaks to move choice like that, but it's all evaluation time. None of that happens in training. Zero times in the RL loop does katago see a two stone game against a weaker player. You can kind of tweak towards play this metric or that, but it's not the same.

Maybe not to the extent you mentioned earlier (I definitely agree that it's not "focused" on this) but there is definitely asymmetric playout training in the training data (see comments on lightvector/KataGo issues #39 and #162 mentioning it for example), that is presumably how they got the tweak for playoutDoublingAdvantage (i.e. actually having a few thousand of the millions upon millions of training games be games where playouts have been doubled for advantage).

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#108

Post by Alpha3031 »

ctchocula wrote: post #91
hakuseki wrote: post #87

Earlier quoted context omitted.

At double-digit kyu level, you should just play every day until you feel you are stuck. After you get stuck, you should pick one thing at a time to focus on improving. But the one thing should probably be related to tesuji or life and death.

Thanks! One follow-up: Any recommended go servers to play on? OGS, Fox, Pandanet?

Probably Fox would be the server with the most players but at DDK basically any would work and I think getting exposure to different playing styles would be worthwhile.

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#109

Post by bluecalm »

logicallee wrote: post #27
bluecalm wrote: post #18

KataGo isn't very good at exploiting weaker opponents. In chess people were convinced a grandmaster can never be beaten with a knight odds. It's just too easy to simplify the position and win. It was very easy (for a grandmaster) vs already super human Stockfish. It was still kinda easy (for a strong GM) vs 200+ ELO stronger NNUE Stockfish. And then someone made a net optimized for exploiting humans. Its games are am…

can the grandmasters still win with rook odds?

Sometimes, especially at long blitz/rapid but they usually lose. I am master level player (FM) and it took me almost 300 games of slow blitz to beat it with N odds and about 150 games to beat it with rook odds. I was beating it at Q odds (meaning more than 50%) but I suspect it might be even better now than it used to be.

Re: Go grandmaster Shin defeats AI KataGo with a two-stone handicap

#110

Post by throw310822 »

EchoAce wrote: post #48
mtlmtlmtlmtl wrote: post #42

Earlier quoted context omitted.

I have some questions as a chess player who barely even understands the rules of go. First these josekis sound like what in chess is called a forced tactical sequence. When you say Shin played out a long complex joseki, how does he do that? Does he have to read/calculate it out over the board(50 moves seems crazy to me unless the search tree is highly constrained by geometry/deduction/very few candidate moves, which…

You can think of joseki as “local opening”. Like, in a vacuum, this is known by study / AI to be an even result for black and white. It’s just like a chess opening, there’s no calculation up to a certain point. And it doesn’t exist in the midgame, it’s not similar to forced sequences which exist in both games; it’s much more like choosing French closed vs open or gambit/gambit declined. The one thing is (and this is…

I don't know absolutely anything about Go but your description of how josekis work- how their optimality makes their evolution deterministic and how they develop better on empty boards or break up against obstacles, makes me think about Conway's game of life. Cool.
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