4 ms·

"Meh" news because we had a higher profile match just recently: AlphaGo vs Lee Sedol (both much stronger than DeepZen or Cho). I mean, it's mildly interesting

by Radim 10y ago

"Meh" news because we had a higher profile match just recently: AlphaGo vs Lee Sedol (both much stronger than DeepZen or Cho). I mean, it's mildly interesting that DeepZen uses fewer resources (just ~40 CPUs and 4 GPU, compared to AlphaGo's ~2k CPU and ~200 GPUs, IIRC). But that's relevant only to hardcore Go enthusiasts who would want to run such AIs on their own hardware. In contrast, the next interesting milestones in Go AI are: * AI beating a team of cooperating top pros, say top-10 humans vs AI (easy) * solving Go (hard) * finding ways to translate insights gained from observing strong Go AI into real-life situations relevant outside of Go (my personal favourite; Go has that fascinating simple-meets-complex abstracting property [1]) [1] https://rare-technologies.com/go_games_life/ https://rare-technologies.com/go_games_life/

emptybits 10y ago
> * solving Go (hard) 1. Perfect play from any game position. 2. Proof of perfect play. #1 may be achievable with a sufficiently clever algorithm. (We may suspect it is perfect and may only later prove it.) #2 may be much much harder. Neither are suitable for brute force approaches to play or proof as some problem spaces are.
adrianN 10y ago
I think the next interesting milestone would be beating top rated humans using commodity hardware. In chess for example, programs running on cell phone processors have Elo rating around 2800. Using weaker hardware means that the algorithms need to have more insight into the game and can't rely as much on exploring the game tree.
qznc 10y ago
The next interesting non-Go milestone seems to be Starcraft ;)
pelario 10y ago
> * AI beating a team of cooperating top pros, say top-10 humans vs AI (easy) It is not clear at all that the cooperating team is more difficult to beatä > * solving Go (hard) Not only hard, but 'solving Go' it is beyond AI, and probably cannot be done. * finding ways to translate insights gained from observing strong Go AI into real-life situations relevant outside of Go (my personal favourite; Go has that fascinating simple-meets-complex abstracting property [1]) Here I fully agree, as conan noted in another thread, stylistic factors are quite important, and the art-like approach is a thing in Go, so I would love to know "what the AI thinks about it" :)

by Radim 10y ago

emptybits 10y ago

> * solving Go (hard) 1. Perfect play from any game position. 2. Proof of perfect play. #1 may be achievable with a sufficiently clever algorithm. (We may suspect it is perfect and may only later prove it.) #2 may be much much harder. Neither are suitable for brute force approaches to play or proof as some problem spaces are.

adrianN 10y ago

I think the next interesting milestone would be beating top rated humans using commodity hardware. In chess for example, programs running on cell phone processors have Elo rating around 2800. Using weaker hardware means that the algorithms need to have more insight into the game and can't rely as much on exploring the game tree.

qznc 10y ago

The next interesting non-Go milestone seems to be Starcraft ;)

pelario 10y ago

> * AI beating a team of cooperating top pros, say top-10 humans vs AI (easy) It is not clear at all that the cooperating team is more difficult to beatä > * solving Go (hard) Not only hard, but 'solving Go' it is beyond AI, and probably cannot be done. * finding ways to translate insights gained from observing strong Go AI into real-life situations relevant outside of Go (my personal favourite; Go has that fascinating simple-meets-complex abstracting property [1]) Here I fully agree, as conan noted in another thread, stylistic factors are quite important, and the art-like approach is a thing in Go, so I would love to know "what the AI thinks about it" :)