- 영상 수
- 1,111
- 구독자
- 184만
- 총 조회수
- 1.7억
- 최근 업로드
- 2026. 11. 14.
- 독립 페이지
- Machine Learning
- 콘텐츠 언어: 영어
- 지역: 헝가리
이 페이지는 Youtop이 운영하는 독립 디렉터리 페이지입니다. Two Minute Papers 또는 YouTube가 운영, 후원, 보증하지 않습니다. 수정 제안하기. 이 크리에이터 본인이신가요? 페이지 소유 신청
Loading
이 페이지는 Youtop이 운영하는 독립 디렉터리 페이지입니다. Two Minute Papers 또는 YouTube가 운영, 후원, 보증하지 않습니다. 수정 제안하기. 이 크리에이터 본인이신가요? 페이지 소유 신청
Two Minute Papers · 2016년 3월 15일 게시
This time around, Google DeepMind embarked on a journey to write an algorithm that plays Go. Go is an ancient chinese board game where the opposing players try to capture each other's stones on the board. Behind the veil of this deceptively simple ruleset, lies an enormous layer of depth and complexity. As scientists like to say, the search space of this problem is significantly larger than that of chess. So large, that one often has to rely on human intuition to find a suitable next move, therefore it is not surprising that playing Go on a high level is, or maybe was widely believed to be intractable for machines. The result is Google DeepMind's AlphaGo, the deep learning technique that defeated a professional player and world champion, Lee Sedol. What it also important to note is that the techniques used in this algorithm are general, and can be used for a large number of different tasks. By this, I mean not AlphaGo specifically, but the Monte Carlo Tree Search, the value network and deep neural networks. ______________________ The paper "Mastering the Game of Go with Deep Neural Networks and Tree Search" is available here: https://storage.googleapis.com/deepmind-data/assets/papers/deepmind-mastering-go.pdf http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html A great Go analysis video by Brady Daniels. Make sure to check it out and subscribe if you like what you see there! https://www.youtube.com/watch?v=dOQsYWxMNJQ The mentioned post on the Go reddit: https://www.reddit.com/r/baduk/comments/49y17z/the_true_strength_of_alphago/ Some clarification on what part of the algorithm is specific to Go and how: https://news.ycombinator.com/item?id=11280744 Go board image credits (all CC BY 2.0): Renato Ganoza - https://flic.kr/p/7nX4kK Jaro Larnos - https://flic.kr/p/dDeQU9 Luis de Bethencourt - https://flic.kr/p/4c5RaR WE WOULD LIKE TO THANK OUR GENEROUS SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Sunil Kim, Vinay S. Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_center?add_user=keeroyz The background of the thumbnail image is the property of Google DeepMind. Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Patreon → https://www.patreon.com/TwoMinutePapers Facebook → https://www.facebook.com/TwoMinutePapers/ Twitter → https://twitter.com/karoly_zsolnai Web → https://cg.tuwien.ac.at/~zsolnai/
