"In the last few years, neural networks have become hugely powerful thanks to two advances. The first is a better understanding of how to fine-tune these networks as they learn, thanks in part to much faster computers. The second is the availability of massive annotated datasets to train the networks.Deep Learning Machine Teaches Itself Chess in 72 Hours, Plays at International Master Level | MIT Technology Review
That has allowed computer scientists to train much bigger networks organized into many layers. These so-called deep neural networks have become hugely powerful and now routinely outperform humans in pattern recognition tasks such as face recognition and handwriting recognition.
So it’s no surprise that deep neural networks ought to be able to spot patterns in chess and that’s exactly the approach Lai has taken. His network consists of four layers that together examine each position on the board in three different ways."
Tuesday, September 15, 2015
Deep Learning Machine Teaches Itself Chess in 72 Hours, Plays at International Master Level | MIT Technology Review
Not just playing games