How DeepMind's AlphaGo Defeated Lee Sedol | Two Minute Papers #53
5:56

How DeepMind's AlphaGo Defeated Lee Sedol | Two Minute Papers #53

Two Minute Papers 15.03.2016 16 015 просмотров 409 лайков

Machine-readable: Markdown · JSON API · Site index

Поделиться Telegram VK Бот
Транскрипт Скачать .md
Анализ с AI
Описание видео
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/

Оглавление (2 сегментов)

Segment 1 (00:00 - 05:00)

dear fellow Scholars this is two-minute papers with carool a few months ago alphago played and defeated fan Hui a twood Dan master and European Champion player in the game of Go however the next opponent Lisa doll is a nan master and World Champion player just to give an intuition of the difference Lisa doll is expected to beat fan Hui 97 times out of 100 games Google Deep Mind had 6 months of preparation for this bout five matches were played over 5 days in my time zone the matches started around 400 a. m. and the results would usually pop up exactly a few minutes after I woke up it was amazing I could barely fall asleep I was so excited for the results and when I woke up I kissed my daughter and immediately ran to my computer to see what was going on most people were convinced that Lisa doll was going to beat the machine 5 to0 and I was stunned to see that alago triumphed over lisad doll in the first match and then the second and then the third huge respect for both cou Deep Mind for putting together such a spectacular algorithm and for lisad doll who played extremely well under enormous pressure he's indeed a true champion the game of Go has a stupendously large search space that makes it completely impossible to check every move and choose the best what is also not often talked about is that processing through many moves is one thing but judging which move is advantageous and which is not is just as difficult as the search itself the definition of the best move is not clearcut by any stretch of the imagination we also have to look into the future and simulate the moves of the opponent I think it is easy to see that the difficulty of this problem is completely out of this world a neural network is a crude approximation of the human brain just like a stick figure is a crude approximation of a human being in this work neuron networks are used to reduce the size of the search space and value networks are used to predict the expected outcome of a move this value Network basically tries to determine who will win if a sequence of moves is made to defeat alphago or any computer opponent playing non-traditional moves that it surely hasn't practiced sounds like a great idea however there is no database involved per se this technique is simulating the moves until the very end of the game so non-traditional weird moves won't throw it off it is also very important to note that the structure of alphago is not like deep blue for chess deep blue was specifically designed to maximize metrics that are likely to lead to victory such as Pawn Advantage King safety Tempo and more alphago doesn't do any of that it is a general technique that can learn to solve a large number of different problems I cannot overstate the significance of this almost the entirety of computer science research revolves around creating algorithms that are specifically tailored to one task different research projects different algorithm imagine how empowering it would be to have a general algorithm that can solve a large amount of problems it's incredible just as people who don't speak a word of Chinese can write an artificial intelligence program to recognize handwritten Chinese text someone who hasn't played more than a few games can write a chess or go program that is beyond the skill of most professional players this is a wonderful Testament of the power of mathematics and science it was quite surprising to see that alphago played seemingly suboptimal moves when it was ahead to reduce the variance and maximize its chance of Victory take a look at Deep mind's other technique by the name deep Q learning that plays Space Invaders on a superhuman level this shot at first looks like a blunder but if you wait it out you'll see how brilliant it really is a move that seems like a blunder at a time maybe the optim move in the grand scheme of things it is not a blunder it is a move from someone whose Brilliance is Way Beyond the capabilities of even the best human players there is an excellent analysis of this phenomenon on the go Reddit I've put a link in the description box check it out I'd like to emphasize that the technique learns at first by looking at a large number of games by amateurs but the question is how can it get beyond the level of amateurs after looking at these games it will learn the basics and will play millions of games against itself and learn from them and to be emphasized nothing in this algorithm is specific to go nothing it can be used to solve a number of different problems without significant changes it would be immensely difficult to overstate the significance of that shout out to Brady Daniels who has an excellent go educational Channel he has very fluid enjoyable and understandable explanations highly recommended check it out there's a link to one of his videos

Segment 2 (05:00 - 05:00)

in the description box it is a possibility that the first go Grandmaster to reach 10 Dan may not be a human but a computer my mind is officially blown Insanity one more Cobblestone has been laid on the path to artificial general intelligence this achievement I find to be of equivalent magnitude to landing on the moon and this is just a beginning I can't wait to see this technique being used for research in medicine huge respect for Demis s and Lisa doll who were both respectful and humble both in Victory and in defeat they are true champions of their craft thanks so much for Deep Mind for creating this rivetingly awesome event my daughter Yasmin was born one day before this glorious day what an exciting time to be alive thanks for watching and for your generous support and I'll see you next time

Другие видео автора — Two Minute Papers

Ctrl+V

Экстракт Знаний в Telegram

Экстракты и дистилляты из лучших YouTube-каналов — сразу после публикации.

Подписаться

Дайджест Экстрактов

Лучшие методички за неделю — каждый понедельник