Inside the (deep) mind of AlphaZero

It was a long time coming, but the wait is over. After nearly a full year, being ping-ponged from one peer reviewer to the next, the final paper on AlphaZero is out, shedding light on a number of hitherto unknown or misunderstood elements in its construction, not to mention some clarifications and corrections. These include sample code to help implement their work and all the games of the match against Stockfish, of which 20 were specially chosen by GM Matthew Sadler. | Graphic: Deep Mind

DeepMind's AlphaZero AI Helps Design New Chess Rules, by Chintan Trivedi, deepgamingai

DeepMind's Game-playing AI Improves Human-devised Algorithms - AIFT

How AlphaZero has rewritten the rules of game play on its own

Deepmind AlphaZero - Mastering Games Without Human Knowledge

Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost

Google DeepMind's Go AI Has Mastered Chess And Shogi

Game Changer: AlphaZero's Groundbreaking by Sadler, Matthew

Training AlphaZero for 700,000 steps. Elo ratings were computed from

Monte Carlo Tree Search Tutorial (MCTS) : DeepMind AlphaGo

Deepmind Introduces 'AlphaTensor,' An Artificial Intelligence (AI) System For Discovering Novel, Efficient And Exact Algorithms For Matrix Multiplication - MarkTechPost