AlphaGo Zero: Approaching Perfection – Synced – Medium

DeepMind recently published a paper in Nature introducing the latest evolution of its AI-powered Go program. "AlphaGo Zero" learns in self-play games, with no human knowledge required. The program crushed previous "AlphaGo" versions (including the one that beat world-best human Ke Jie) with a record of 100 wins and zero losses, stimulating discussion in the Go and AI communities. Facebook AI researcher Yuandong Tian -- who built Facebook's Go program Darkfmcts3 in 2015 -- shared his views on AlphaGo Zero with Synced: Deep Mind's paper Mastering the Game of Go Without Human Knowledge is much better than its January 2016 predecessor, Mastering the Game of Go With Deep Neural Networks and Tree Search. The new paper's method is clean and standardized, and it is surely destined to be a classic. AlphaGo Zero combines its previous versions' policy network and value network to share parameters, which is not novel.