Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost

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

Four Deep Learning papers from late 2021 that will have a significant impact on 2022, by Leonardo Tanzi

AlphaZero Explained · On AI

Acquisition of chess knowledge in AlphaZero

Acquisition of chess knowledge in AlphaZero

DeepMind, Google Brain & World Chess Champion Explore How AlphaZero Learns Chess Knowledge

UK Category - Page 9 of 10 - MarkTechPost

How AlphaZero Learns Chess

Leonardo Tanzi on LinkedIn: Four DL papers on text-to-image synthesis, brain representation, and…

Acquisition of chess knowledge in AlphaZero

Acquisition of chess knowledge in AlphaZero

Understanding AlphaZero Neural Network's SuperHuman Chess Ability - MarkTechPost