AlphaGo given honorary 9 dan rank by Korean Baduk Association(straitstimes.com) |
AlphaGo given honorary 9 dan rank by Korean Baduk Association(straitstimes.com) |
Probably one of the most exciting achievements in AI in a little while.
They used strong amateur player games from public archives.
It was also mentioned that AlphaGo needs millions of games to be trained. Even if they added a few hundred Lee Sedol games, the impact would be very small.
By the way, AlphaGo has a wikipedia page: https://en.wikipedia.org/wiki/AlphaGo
And the Nature paper is: http://www.nature.com/nature/journal/v529/n7587/full/nature1... (paywalled, but scihub can get it for you). The paper is fairly readable, and worth having a look at if you are interested in this topic.
This kind of learning doesn't work like that. It doesn't learn from specific examples, or make meaningful inferences from single data points. It learns tiny gradients from millions of examples. If we had an approach that could create a meaningfully distinct strategy depending on {whether we included or excluded {every game Lee Sedol has played in his life} from training}, that would be wildly more significant than just beating him.
I hope that Lee can adapt, but I doubt it. Lee will be training at a slow pace analyzing 4 or 5 games. AlphaGo will be playing hundreds of millions against itself - and it is a worthy competitor of itself already.
Although Go and AlphaGo are very different than Chess and DeepBlue, there is one interesting analogy... Once chess beat us, they pulled ahead very quickly and the gap isn't closing. The ELO rating of top chess programs [0] is pulling away from top humans [1]. There are natural differences between computational superiority and creativity, but it seems like AlphaGo has captured a lot of the latter.
[0] https://www.chess.com/article/view/the-best-computer-chess-e...
It was mentioned that AlphaGo was trained on so many games that the games of Lee Sedol that were used for training were not more than a drop in the ocean. This was the answer to the question about whether AlphaGo was trained specifically against Lee Sedol.