
From Future of Go Summit AI conference today
Source https://twitter.com/webigojp/status/867228171174903808
Video https://www.facebook.com/GOking2007/vid ... 096921048/
Comment from Seigenblues in Reddit
AG Master used 10x less compute, trained in weeks vs months. Single machine. (Not 5? Not sure). Main idea behind AlphaGo Master: only use the best data. Best data is all AG's data, i.e. only trained on AG games.
Using training data (self play) to train new policy network. They train the policy network to produce the same result as the whole system. Ditto for revising the value network. Repeat. Iterated "many times".
Results: AG Lee beat AG Fan at 3 stones. AG Master beat AG Lee at three stones! Chart stops there, no hint at how much stronger AG Ke is or if it's the same as AG Master
Strong caveat here from the researchers: bot vs bot handicap margins aren't predictive of human strength, especially given it's tendency to take it's foot off the gas when it's ahead