The news dropped that Google’s new implementation of AlphaGo, called AlphaGO Zero, was able to learn completely on its own. No training set was first used, rather it built it’s own training set as it played against the older AlphaGO.

Earlier versions of AlphaGo were taught to play the game using two methods. In the first, called supervised learning, researchers fed the program 100,000 top amateur Go games and taught it to imitate what it saw. In the second, called reinforcement learning, they had the program play itself and learn from the results.

AlphaGo Zero skipped the first step. The program began as a blank slate, knowing only the rules of Go, and played games against itself. At first, it placed stones randomly on the board. Over time it got better at evaluating board positions and identifying advantageous moves. It also learned many of the canonical elements of Go strategy and discovered new strategies all its own. via Quantamagazine

Imagine if you took this deep learning technology and used it on the Quantum Computer Google is developing? Amazing times we are living in.

• AI Machine Learning