DeepMind - AlphaCode
WEBThis solution stands out from other AlphaCode solutions because it inputs a tree and then traverses it with a depth-first search (DFS). Here it most likely borrowed large chunks of code from other dfs-on-tree problems, such as the "dfs" function or the I/O.
Ithaca | Restoring and attributing ancient texts using deep neural …
WEBIthaca can attribute inscriptions to their original findspot with 71% accuracy and can date them with a distance of less than 30 years from ground-truth ranges, redating key texts of Classical Athens and contributing to topical debates in Ancient History. Ithaca's experimental results.
AlphaGo Teach: Discover new and creative ways of playing Go
WEBLet the AlphaGo Teaching Tool help you find new and creative ways of playing Go. This tool provides analysis of 6,000 of the most popular opening sequences from the recent history of Go, using data from 231,000 human games and …
AlphaGo Teach: 바둑에서 새롭고 창의적인 수들을 발견해보세요
WEB알파고의 예상 승리 확률 이해하기. 알파고가 선호하는 수가 항상 가장 높은 승리 확률을 보이지는 않습니다. 이것은 알파고의 승리 확률 평가가 해당 상황에서 천만 가지 이상의 변화를 독립적으로 검색해 계산하기 때문입니다. 이 알파고의 검색에 약간의 ...
AlphaGo教學: 探索圍棋創新思路 - Deepmind
WEB通過對 AlphaGo 和職業與業餘棋手的下法進行比較，探索圍棋的奧妙。. 基於 231,000 盤人類棋手對局以及 75 盤 AlphaGo 與人類棋手對局的數據，本工具提供對圍棋近代史上數千種開局變化的分析。.
AlphaGo 教学： 探索围棋创新思路 - Deepmind
WEB通过对 AlphaGo 和职业与业余棋手的下法进行比较，探索围棋的奥妙。. 基于 231,000 盘人类棋手对局以及 75 盘 AlphaGo 与人类棋手对局的数据，本工具提供对围棋近代史上数千种开局变化的分析。.
AlphaGo 学習ツール: 新たな囲碁の楽しみを - Deepmind
WEBAlphaGo 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。
Neural scene representation and rendering - deepmind.com
WEBThere is more than meets the eye when it comes to how we understand a visual scene: our brains draw on prior knowledge to reason and to make inferences that go far beyond the patterns of light that hit our retinas. For example, when entering a room for the first time, you instantly recognise the items it contains and where they are positioned. If you see …
Highlighted research - deepmind.com
WEBOur pioneering research includes Deep Learning, Reinforcement Learning, Theory & Foundations, Neuroscience, Unsupervised Learning & Generative Models, Control & Robotics, and Safety.