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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

#171

Post by harshreality »

dist-epoch wrote: post #121
harshreality wrote: post #56

Earlier quoted context omitted.

...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=-86z…

Considering the original AlphaGo ran on a full Google TPU rack, and here KataGo seems to run on a $10k computer, and won with 2 stones handicap, this is showing just how much advance there was in computer go

AlphaGo Master, the much stronger[1] one that beat Ke Jie a year later in 2017, ran on a single 4x TPU (v2?) workstation.

[1] From wikipedia, citing deepmind's paper: 4858 Elo vs 3739 Elo

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

#172

Post by bawolff »

i_no_can_eat wrote: post #139
bawolff wrote: post #127

Earlier quoted context omitted.

fwiw, as a native speaker, your revised version sounds wrong. I'm terrible at grammer, but i think it's because when you put the "with" early in the sentence, it acts as a preposition modifying the noun, where later in the sentence it acts as an adverbial phrase modifying the verb defeat. The handicap is describing the manner of the defeat and not a trait of the grandmaster, so the with has to go at the end of the se…

> I'm terrible at grammer Also pretty bad at spelling.

lol, you are not wrong.

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

#173

Post by ApolloFortyNine »

Last time I read about these handicapped games in Go I saw that the model isn't trained to play from behind, so while in a normal game of Go, those 50 move Joseki's or any large move combo that's an 'even trade' will inevitably let the AI claw a lead at some point, the AI is already behind.

It's similar in chess but there's a model specifically trained to play a knight down, and it's pretty cool to see the insane tactics it'll try. Though a knight down is considerably more than a 2 stone handicap in Go.

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

#174

Post by helloplanets »

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.

At least when it comes to chess, Magnus Carlsen has stated multiple times that he's been inspired by AlphaZero and adjusted his own style of play after studying its games.

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

#175

Post by kuboble »

bulletmarker wrote: post #21
kadoban wrote: post #10

Earlier quoted context omitted.

The headline is misleading, but this is still huge. 2 stones against katago is insane, I'd never have guessed we'd see that, ever.

Annoyingly misleading. I read it that the human player was handicapped.

Like many random headlines they may be targeted at people who know something about a topic.

If you know anything about go or computer go from last 10 years then it is obvious which direction the handicap goes.

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

#176

Post by KK7NIL »

shwaj wrote: post #83
somenameforme wrote: post #74

Earlier quoted context omitted.

I'm unfamiliar with Go ratings, but chess ratings are based on the Elo system which is a simple mathematical prediction system. Borrowing some figures from Wiki [1] we get: 1.00 +800 0.99 +677 0.9 +366 0.8 +240 0.7 +149 0.6 +72 0.5 0 0.4 −72 0.3 −149 0.2 −240 0.1 −366 0.01 −677 0.00 −800 The second column is your rating minus your opponent's, and the left is your predicted result. So if you are rating 1849 and your o…

I was under the impression that Go also uses Elo, then I did a bit of cursory research and discovers that it varies. Two major federations are American Go Association (AGA) and European Go Federation (EGF). EGF uses an Elo-inspired update rule since 2021. AGA uses a quite-different Bayesian system without pairwise update; they provide a paper and a C++ reference impl. Asian countries don't bother with such numeric ra…

AGA and EGF are very minor federations in the Go world, all the professionals are in Asia where the game is far bigger.

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

#177

Post by kuboble »

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?

I'm 2 dan.

For a double digit kyu there are two simple things than can give you 2-3 stones boost overnight if you understand them.

- don't play aji keshi.

- endgame starts earlier than you think. If nothing is urgent, play the largest endgame in the corner / side of the board.

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

#178

Post by phatfish »

gjm11 wrote: post #167
hyperpape wrote: post #33

Earlier quoted context omitted.

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 f…

This is a bit of a digression, but: It's an interesting question what (if anything) that larger dynamic range means . One thing you'll hear people say sometimes -- I've said it myself -- is that this shows that in some sense go is a "deeper" game than chess; there's more to know and understand, more variety of possible human skill. That might well be true. It certainly feels a more elegant game, and involves longer t…

Maybe the depth of a game is related to whether it will scale. Go is played on different board sizes and still works.

If you make a Backgammon board bigger it would just be a slog and no real increase in tactical challenge.

Chess rules dictate a set size of board, which I guess has been refined over time.

If a Go board is made bigger or smaller it just adjusts the problem space, the rules and core of the game remain the same.

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

#179

Post by thangalin »

mark_l_watson wrote: post #161

I love this. I watched every game years ago between Lee Sedol, even though it was late at night. I love AI and I love Go. Off topic, but I wrote the first commercial Go program for the Apple II in the late 1970s.

Here's likely the first computer Go algorithm (in FORTRAN) and I believe the SGF is the first ever recorded human-computer game:

https://repo.autonoma.ca/repo/historical-computer-go

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

#180

Post by joelthelion »

Shorel wrote: post #120
joelthelion wrote: post #25

Is there an equivalent of LeelaKnightOdds for Go? That might be harder to tackle.

This would be exactly that. The handicap stones in go allow it, it also works between humans of different strength levels. Now, if you mean a NN specifically trained to play at disadvantage, that would be extremely interesting and I hope they make it!

That's exactly what I meant . LeelaKnightOdds is specifically trained for that, and it makes a world of difference.
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