
Much More Efficient Self-Play Learning in Go - jedharris
https://blog.janestreet.com/accelerating-self-play-learning-in-go/
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jedharris
The author's most recent version of KataGo averages about 50 times greater
learning efficiency from self-play.

See <[https://blog.janestreet.com/deep-learning-the-hardest-go-
pro...](https://blog.janestreet.com/deep-learning-the-hardest-go-problem-in-
the-world/>). This covers developments since the initial post, plus the
headline problem (which is still open).

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jedharris
Related demos, repositories, papers and posts:

More recent and extensive post: [https://blog.janestreet.com/deep-learning-
the-hardest-go-pro...](https://blog.janestreet.com/deep-learning-the-hardest-
go-problem-in-the-world/)

Site to play against KataGo: [https://online-
go.com/player/592684/](https://online-go.com/player/592684/)

Arxiv paper on KataGo design:
[https://arxiv.org/abs/1902.10565](https://arxiv.org/abs/1902.10565)

GitHub repository of KataGo:
[https://github.com/lightvector/KataGo](https://github.com/lightvector/KataGo)

Another writer commenting on the history of Go AI, and significance of KataGo:
[https://brantondemoss.com/writing/kata.html](https://brantondemoss.com/writing/kata.html)

