{"action":"created","issue":{"url":"https://api.github.com/repos/gcp/leela-zero/issues/1311","repository_url":"https://api.github.com/repos/gcp/leela-zero","labels_url":"https://api.github.com/repos/gcp/leela-zero/issues/1311/labels{/name}","comments_url":"https://api.github.com/repos/gcp/leela-zero/issues/1311/comments","events_url":"https://api.github.com/repos/gcp/leela-zero/issues/1311/events","html_url":"https://github.com/gcp/leela-zero/issues/1311","id":319676063,"number":1311,"title":"Facebook open sources elf opengo ","user":{"login":"kityanhem","id":22489225,"avatar_url":"https://avatars1.githubusercontent.com/u/22489225?v=4","gravatar_id":"","url":"https://api.github.com/users/kityanhem","html_url":"https://github.com/kityanhem","followers_url":"https://api.github.com/users/kityanhem/followers","following_url":"https://api.github.com/users/kityanhem/following{/other_user}","gists_url":"https://api.github.com/users/kityanhem/gists{/gist_id}","starred_url":"https://api.github.com/users/kityanhem/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kityanhem/subscriptions","organizations_url":"https://api.github.com/users/kityanhem/orgs","repos_url":"https://api.github.com/users/kityanhem/repos","events_url":"https://api.github.com/users/kityanhem/events{/privacy}","received_events_url":"https://api.github.com/users/kityanhem/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":118,"created_at":"2018-05-02T19:08:16Z","updated_at":"2018-05-03T12:33:48Z","closed_at":null,"author_association":"NONE","body":"https://research.fb.com/facebook-open-sources-elf-opengo/\r\n\r\nELF OpenGo\r\nELF OpenGo is a reimplementation of AlphaGoZero / AlphaZero. It was trained on 2,000 GPUs over a two week period, and has achieved high performance.\r\n\r\n\"ELF OpenGo has been successful playing against both other open source bots and human Go players. We played and won 200 games against LeelaZero (158603eb, Apr. 25, 2018), the strongest publicly available bot, using its default settings and no pondering. We also achieved a 14 win, 0 loss record against four of the top 30 world-ranked human Go players.\"\r\n\r\n\"We thank the LeelaZero team for their high quality work, and our hope is that open-sourcing our bot can similarly benefit community initiatives like LeelaZero\"\r\n\r\nGithub: https://github.com/pytorch/elf"},"comment":{"url":"https://api.github.com/repos/gcp/leela-zero/issues/comments/386279995","html_url":"https://github.com/gcp/leela-zero/issues/1311#issuecomment-386279995","issue_url":"https://api.github.com/repos/gcp/leela-zero/issues/1311","id":386279995,"user":{"login":"bittsitt","id":38073282,"avatar_url":"https://avatars3.githubusercontent.com/u/38073282?v=4","gravatar_id":"","url":"https://api.github.com/users/bittsitt","html_url":"https://github.com/bittsitt","followers_url":"https://api.github.com/users/bittsitt/followers","following_url":"https://api.github.com/users/bittsitt/following{/other_user}","gists_url":"https://api.github.com/users/bittsitt/gists{/gist_id}","starred_url":"https://api.github.com/users/bittsitt/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/bittsitt/subscriptions","organizations_url":"https://api.github.com/users/bittsitt/orgs","repos_url":"https://api.github.com/users/bittsitt/repos","events_url":"https://api.github.com/users/bittsitt/events{/privacy}","received_events_url":"https://api.github.com/users/bittsitt/received_events","type":"User","site_admin":false},"created_at":"2018-05-03T12:33:47Z","updated_at":"2018-05-03T12:33:47Z","author_association":"NONE","body":"> Nobody is suggesting we stop working on open source go software, I'm suggesting we look if there's something better to do than mindlessly continuing past an important milestone (superhuman performance even on modest hardware).\r\n\r\n@gcp I find this statement interesting :-) Do you have some ideas of what could be better to do?\r\n\r\nI have two (these have limited scope, so one could return to increasing strength or other task once done).Might not at all be what you had in mind:\r\n- Use a game database to train a network to mimic the play (mistakes) of an 8-kyu, 1-kyu, 4-dan etc.  I'm not sure how useful it is for a 1-dan to get his ass whopped by LZ in a regular even game, at least it is demoralising.\r\n- Train a network to estimate score (or extract it from current network). It is useful when doing analysis to know if it is a close game (w+1.5) or if w has a 25.5 point lead (winrate could be 99% for both towards the end) - this might be really trivial."}}
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