How DeepMind Conquered Go With Deep Learning (AlphaGo) | Two Minute Papers #42

dear fellow Scholars this is 2minute papers with Caro here in 1997 the news

took the World by storm gari Kasparov world champion and Grandmaster chess player was defeated by an artificial intelligence program by the name deep blue in 2011 IBM Watson won first place in the famous American quiz show

Jeopardy in 2014 Google Deep Mind created an algorithm that mastered a number of Atari games by working on a raw pixel input this algorithm learned in a similar way as a human would this time around Google Deep Mind embarked on a journey to write an algorithm that plays 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 rule set 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 go on a high level is or maybe was widely believed to be intractable for machines this chart shows the skill level of previous artificial intelligence programs the green bar shows the skill level of a professional player used as a reference the red bars mean that these older techniques required a significant starting advantage to be able to contend with human opponents as you can see deep M's new program skill level is well beyond most professional players an elite pro player and European Champion fan huie was challenged to play Alpha go Google deep mind's newest invention and got defeated in all five matches they played together during these games each turn it took approximately 2 seconds for the algorithm to come up with the next move an interesting detail is that these strange black bars show confidence intervals which means that the smaller they are the more confident one can be in the validity of the measurements as one can see these confidence intervals are much shorter for the artificial intelligence programs than the human player likely because one can fire up a machine and let it play a million games and get a great estimation of its skill level while the human player can only play a very limited number of matches there is still a lot left to be excited for in March the algorithm will play a world champion the rate of improvement in artificial intelligence research is accelerating at a staggering Pace the only question that remains is not if something is possible but when it will become possible I wake up every day excited to read the newest breakthroughs in the field and of course trying to add some leaves to the tree of knowledge with my own projects I feel privileged to be Al live in such an amazing time as always there's lots of references in the description box make sure to check them out thanks for watching and for your generous support and I'll see you next time