How DeepMind Conquered Go With Deep Learning (AlphaGo) | Two Minute Papers #42 Video
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 European champion, Fan Hui.
__________________
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
Wired's coverage of AlphaGo:
http://www.wired.com/2016/01/in-a-huge-breakthrough-googles-ai-beats-a-top-player-at-the-game-of-go/
Video coverage from DeepMind and Nature:
https://www.youtube.com/watch?v=g-dKXOlsf98
https://www.youtube.com/watch?v=SUbqykXVx0A
Myungwan Kim analysis: https://www.youtube.com/watch?v=NHRHUHW6HQE
Photo credits:
Watson - AP Photo/Jeopardy Productions, Inc.
Fan Hui match photo - Google DeepMind - https://www.youtube.com/watch?v=SUbqykXVx0A
Go board image credits (all CC BY 2.0):
Renato Ganoza - https://flic.kr/p/7nX4kK
Jaro Larnos (changes were applied, mostly recoloring) - https://flic.kr/p/dDeQU9
Luis de Bethencourt - https://flic.kr/p/4c5RaR
Detailed analysis of the games against Fan Hui and some more speculation:
https://www.reddit.com/r/MachineLearning/comments/43fl90/synopsis_of_top_go_professionals_analysis_of/
Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_center?add_user=keeroyz
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/
About the Site 🌐
This site provides links to random videos hosted at YouTube, with the emphasis on random. 🎥
Origins of the Idea 🌱
The original idea for this site stemmed from the need to benchmark the popularity of a video against the general population of YouTube videos. 🧠
Challenges Faced 🤔
Obtaining a large sample of videos was crucial for accurate ranking, but YouTube lacks a direct method to gather random video IDs.
Even searching for random strings on YouTube doesn't yield truly random results, complicating the process further. 🔍
Creating Truly Random Links 🛠️
The YouTube API offers additional functions enabling the discovery of more random videos. Through inventive techniques and a touch of space-time manipulation, we've achieved a process yielding nearly 100% random links to YouTube videos.
About YouTube 📺
YouTube, an American video-sharing website based in San Bruno, California, offers a diverse range of user-generated and corporate media content. 🌟
Content and Users 🎵
Users can upload, view, rate, share, and comment on videos, with content spanning video clips, music videos, live streams, and more.
While most content is uploaded by individuals, media corporations like CBS and the BBC also contribute. Unregistered users can watch videos, while registered users enjoy additional privileges such as uploading unlimited videos and adding comments.
Monetization and Impact 🤑
YouTube and creators earn revenue through Google AdSense, with most videos free to view. Premium channels and subscription services like YouTube Music and YouTube Premium offer ad-free streaming.
As of February 2017, over 400 hours of content were uploaded to YouTube every minute, with the site ranking as the second-most popular globally. By May 2019, this figure exceeded 500 hours per minute. 📈
List of ours generators⚡
Random YouTube Videos Generator
Random Film and Animation Video Generator
Random Autos and Vehicles Video Generator
Random Pets and Animals Video Generator
Random Travel and Events Video Generator
Random People and Blogs Video Generator
Random Entertainment Video Generator
Random News and Politics Video Generator
Random Howto and Style Video Generator
Random Education Video Generator