DeepMind - AlphaCode
AlphaCode Attention Visualization. Hover over tokens in the solution to see which tokens the model attended to when generating the solution. Click a token to select it; clicking in empty space will deselect.
Deepmind
Explore how moves played by AlphaGo compare to those of professional and amateur players. This tool provides analysis of thousands of the most popular opening sequences from the recent history of Go, using data from 231,000 human games and 75 games that DeepMind's AlphaGo played against human players
Ithaca | Restoring and attributing ancient texts using deep neural …
This work shows how models like Ithaca can unlock the cooperative potential between AI and historians, transformationally impacting the way we study and write about one of the most significant periods in human history.
AlphaGo 教学： 探索围棋创新思路 - Deepmind
主页; 关于. 关于 WGo.js player 2.0; 关于 DeepMind AlphaGo; 感谢. 6,000 种开局变化来自于 超过 230,000 盘人类对局: 来自 Go4Go 的 65,000 局职业比赛 (1980-2017) 来自 GoBase 的 36,000 局职业比赛 (1960-1990) 野狐围棋 的 130,000 盘野狐围棋9段棋手对局; 75 盘 AlphaGo 与人类棋手对 …
AlphaGo 学習ツール: 新たな囲碁の楽しみを - Deepmind
AlphaGo と棋士たちの手を比較してみましょう。このツールは、よくある序盤パターンを、人同士が打った 231,000 局と、DeepMind 開発の AlphaGo が人と対局した 75 局の棋譜データから分析することができます。
AlphaGo教學: 探索圍棋創新思路 - Deepmind
首頁; 關於. 關於WGo.js player 2.0; 關於DeepMind AlphaGo; 感謝. 6,000 種開局變化來自於 超過 230,000 盤人類對局: Go4Go 的 65,000 局職業比賽 (1980-2017) GoBase 的 36,000 局職業比賽 (1960-1990) 野狐圍棋 的 130,000 盤野狐圍棋9段棋手對局; 75 盤 AlphaGo 與人類棋手對局 (前 30 …