181–184 of 184 posts
Great, now next match against blue spot[0], starting even and adjusting the handicap each game. Blue spot is an adversarial ai and it's managed to beat average professionals on five handicaps, which is absolutely insane. [0]: https://codenamebluespot.com/
What does "on five handicaps" mean? The human received a 5-stone handicap?
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 tac…
You can choose which piece it's missing. It's humbling to lose starting up a queen
Earlier quoted context omitted.
Yes, I can understand why absolute ratings are impossible to extract. However, since the population maintains some continuity over time (players gradually enter and then leave over time), would it not be possible to reconstruct relative ratings between players that didn't play during the same era?
Only if you were to assume that a player's prowess remains constant throughout their career, which we generally know to be false. (I'm completely inventing dates here) If Fisher played Kasparov in 1990 and Kasparov played Carlsen in 2020, you can only compare Carlsen to Fisher if you assume Kasparov's skill was about the same for this entire duration, which no one believes to be the case.
Chess requires you to be really sharp. Experience increases with age, but there's some cross-over point at which the decline in calculating speed is more important than increasing experience. Heck, I'm measurably better at chess tactics in the morning after a good night's sleep than in the evening after work.
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.