Comment by rao-v
1 day ago
It’s worth understanding that Shin Jinse has been significantly stronger than his nearest human opponents for a while now, more so than Magnus was even at his very peak.
In go ELO like scoring he’s something like 120 points over the next strongest player. No other player has ever broken a 3800 rating let alone 3850. Ke Jie (the previous long time champion) peaked at 3755. Shin Jinseo’s strength graph is the most absurd straight line.
2 stones is historically the gap between a 9P ranked and a 1P ranked professional player (very roughly the gap between super grandmasters and an almost grandmaster)
That is to say it’s shocking that Katago (almost certainly significantly stronger than AlphaGo) is a mere 2 stones stronger than Shin Jinseo. I suspect it would be 3-4 stones vs any other human pro.
I read this comment before looking at the article and thought that the grandmaster beat the AI even giving the AI 2 stones. Too bad. But this way around is of course more realistic.
And of course you would need to take into consideration the scale of go ratings and chess ratings when making that comparison. With top chess ratings being around 2800, being 1000 less than the top go ratings, one would have to apply a factor of roughly 3/4.
If you scaled Shin Jinseo to 2800, you would have players with extremely negative ratings. This page shows ratings of European players on a roughly aligned scale: https://europeangodatabase.eu/EGD/createalleuro3.php?country.... It still has negative numbers on it, and this only contains players who have attended a tournament (though it's more common for beginners to play tournaments in the west, since it's hard to find times to play).
It's not a comparison of the worth of the games (I play both, though I'm better at Go, and prefer it), but the dynamic range of Go is larger.
That said, any cross-game/sport comparisons of this kind are pretty tough to do properly.
>Go grandmaster Shin defeats AI KataGo with a two-stone handicap
English is not my first language but for clarity perhaps the title should be:
Go grandmaster Shin with a two-stone handicap defeats AI KataGo
Depends on what chess rating you're talking about. Online at fast time controls, where many many more games get played at than OTB classical, the top super GMs are rated in the 3400-3600 range.
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 of Lee Changho, so that there are now 20 players stronger than him).
The problem is ambient go knowledge. A top 100 player would easily beat time traveling Lee Changho in his first few matchups. Of course give peak Lee Changho a fortnight to prep with Katago and … well that would be something!
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 pool of players (including all the amateurs who compete at lower levels) was in the year 2014 vs. 1999.
The only way to actually anchor the Elo system over long periods of time would be to have rated humans occasionally play against a set of unchanging computer players, which could then serve as static rating calibrators. You could use those games to then calibrate Elo ratings from different time periods to a common scale, by asserting that the computer ratings don't change.
Could you just have superhuman Go AI just how good humans are somewhat more objectively?
Not without flaws of course, but probably interesting
> Katago (almost certainly significantly stronger than AlphaGo)
Interesting KataGo is an open sourced Go program written primarily by David Wu in C++ and recently heavily vibe coded by Claude. It's running on four Nvidia RTX-3090 GPUs with 96GB VRAM. [1]
[1] https://github.com/lightvector/KataGo
I had to read your comment five times thinking "how it is written in C++ if it's a go program?" Do'h!
It significantly predates Claude, and has been one of, if not the best engine in the world for many years.
Important to note that KataGo was double-handicapped. 20 seconds per move maximum; it couldn’t read deep. Against an amateur, it doesn’t matter, but against a historically strong pro it matters a lot.
...on a 4x 3090 rig. The game ran 299 moves, giving katago 100 minutes if it exhausted time on each move (which must be the optimal strategy under that time control). Shin used about 205 minutes, over twice as much time and of course had leeway to spend more time on difficult moves.
Based on the youtube video, it looks like katago was only using 16 seconds per move, is that right? https://www.youtube.com/watch?v=-86zF4mTWOY
Is 20 seconds on that hardware really overkill and well into the diminishing-returns curve, as a top-level comment suggested, or is it plausible katago could have played better if given 40 seconds per move?
match details: https://gostonebase.com/blog/shin-jinseo-vs-katago-kishin-ma...
Deep link to Shin Jinseo's strength graph
https://www.goratings.org/en/players/1313.html
It would be interesting to find out what insight he discovered about the game to consistently rise like that.
It can't be just play like AI.
Any other Korean on the Korean Go program could have done the same.
In fact, many did when AlphaGo was the pinnacle of AI.
For another comparison, top world class chess players will have solid odds to beat Leela Chess Zero when given a knight odds handicap (Leela Chess Zero starts with 1 fewer knight). For human vs human, I think this would be somewhere in the ballpark of the ~10,000th best chess player having fair odds against Magnus.
I wonder if this means the best Go play is closer to theoretically perfect play or if it just happened the current computer methods didn't manage to get much farther than humans. Go has vastly more valid games but also a simpler ruleset, so I'm not sure if there is really a good way to tell beyond "keep trying and find out"?
I don't think it's solely a matter of raw strength, but as Shin said, a willingness not to play to the program's strengths. I mean, one thing that rankled me about original Lee Sedol match was that Lee had no access to the program's "record" while the machine by the nature of the AI training process had effectively studied Lee's games in great detail.
I recall a while back someone came up with a set of "anti-computer" strategies that allowed even an amateur to defeat a strong go program. These moves weren't anything like ordinary go moves (and perhaps the "loophole" has been closed now) but imo, their existence suggests that a study of programs may reveal other unexpected weakness.
In a march 2026 interview David Wu (lightvector, Katago’s creator at Jane Street) noted that he doesn’t have a systematic solution for the cyclic group problem, but adding examples to the training set mostly ensures Katago during MCT rollout figures it out. I don’t think there has been a post mid 2024 verified exploit.
https://gomagic.org/david-wu-on-building-katago/
I saw the same things when the OpenAI Dota bots could eviscerate humans 1v1 - even pros lost!
Until a more average player confuses the AI with an unseen behaviour (pulling creeps between the towers etc) to get an advantage.
We saw this with AlphaStar too, but ultimately it feels like simply an exploit. I expect even a relatively simple modern LLM/model working with the custom transformer would have been able to address these exploits after a game.
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Probably a better comparison from the chess world(in reasonably modern times, though perhaps players like Capablanca and Lasker could be mentioned as well. Alas, I don't think FIDE rating existed back then) is Bobby Fischer. In the july 1972 FIDE rating list he held a rating of 2785, the highest in history at the time, with Spassky in second sitting at a "measly" 2660, and only 13 players being above 2600 even.
For a non-Go player, do you think this trend will persist, or is it more of a dead-cat/human bounce?
On one hand, Shin Jinseo is an outlier player of this generation. On the other hand, the newest generation of new pros will have exclusively learned by using the AI to tell them what the best move is, so there's reason to believe that peak human level has yet to be reached.
Distillation of our blessed models is no fair!
Could someone sufficiently motivated invest in training Katago to be able to beat Shin Jinseo with 3 stones of handicap? Unfortunately - probably yes.
This in no way detracts from how absurd and remarkable it is that Shin Jinseo can beat KataGo (it gets a LOT of training and architecture refinements https://katagotraining.org/#eloGraphButtons) with 2 stones of handicap.