Understanding AlphaZero Neural Network's SuperHuman Chess Ability
Por um escritor misterioso
Descrição
As a common and (sometimes) proven belief, deep learning systems seem to learn uninterpretable representations and are far from human understanding. Recently, some studies have highlighted the fact that this may not always be applicable, and some networks may be able to learn human-readable representations. Unfortunately, this ability could merely come from the fact that these networks are exposed to human-generated data. So, to demonstrate their ability to learn like humans (and not that they are simply memorizing human-created labels), it is necessary to test them without any label. Following this idea, the DeepMind and Google Brain teams, together with
Google's self-learning AI AlphaZero masters chess in 4 hours
Artificial Intelligence Is Coming for Our Proteins Office for Science and Society - McGill University
Google's AlphaZero AI mastered chess in just four hours
Computer chess - Wikipedia
Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost
Understanding AlphaZero: A Basic Chess Neural Network
CB article on AlphaZero suggests AlphaZero is playing a different kind of chess. : r/chess
Acquisition of Chess Knowledge in AlphaZero – arXiv Vanity
Frontiers AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong
The interface Is the message (when you know the rules)