Alphabet’s London-based DeepMind loosed AlphaZero, its AI-powered system that can master games without human intervention, on Stockfish, the highest rated chess game engine, and crushed it. DeepMind developed the self-training method, dubbed deep reinforcement learning, specifically to attack strategy board game “Go,” and an earlier iteration of the system beat one of the world’s best “Go” players, although it needed human guidance. AlphaZero trained itself in chess in three days, rejecting red-marked moves after a mere 1,000 simulations. Continue reading DeepMind’s AlphaZero Defeats Leading Chess Game Engine

DeepMind recently released the full evaluation of AlphaZero, a single system capable of playing “Go,” chess, and shogi (Japanese chess). This new project builds on AlphaGo, a program that beat one of the best players in the world at the board game “Go” in 2016, and AlphaGo Zero, software capable of mastering the game from first principles. AlphaZero represents a dramatic step forward in AI research as it is one of the first intelligent systems capable of generalizing solutions to new problems with little to no human input. Continue reading DeepMind’s Learning Algorithm Could Prove a Game-Changer

OpenAI, an artificial intelligence research group backed by Elon Musk, stated that its software can beat “teams of five skilled human players” in Valve’s video game “Dota 2.” If verified, the achievement would be a milestone in computer science and a leap beyond other AI researchers working on mastering complex games. IBM’s software mastered chess in the late 1990s, and Alphabet’s DeepMind created software that dominated “Go” in 2016. “Dota 2” is a multiplayer sci-fi fantasy game where teams advance through exploration. Continue reading OpenAI Beats Human-Player Team at Complex Video Game