If you're like the rest of the world, you played at least a few games of chess after binge watching The Queen's Gambit. Beth Harmon didn't have powerful computers to help her train like we do today. Ever since Deep Blue famous defeated Gary Kasparov in 1997, chess engines have become a critical part of the game.
But how do chess engines work? Is it hardcoded from a database of known moves, or is it learned through training? Could it be using both?
More importantly, what can you learn from chess engines? You should leave this session with an understanding of how modern chess engines work, a better understanding of how AI/ML can be applied to solve problems, and, with any luck, some ideas on how to use AI/ML in your daily work.
- This repository
- Node, with NPM or Yarn (download here)
The slide deck is built using Spectacle. If you want to run the slides from this talk:
- Run
npm install
oryarn
to install the dependencies - Run
npm start
oryarn start
to launch the deck