Md. Taqi Yasir
AlphaGo, a computer series premeditated by Google DeepMind, has just a game more to go against top-ranked player of GO Lee Sedol of South Korea, in a 5 game match redolent of the 1997 fight between Deep Blue and Garry Kasparov.
AlphaGo’s success so far is exceptional, no matter the outcome of the final match. The fact that we’ve moved from teaching computers chess to training them on how to play the more complex game of Go shows the advances computer scientists have made in programming intelligence. But what happens to the chess programs of yesteryear?
The rise of AlphaGo contributed directly to the demise of at least one very interesting chess engine: Giraffe, which was developed by Matthew Lai as part of his advanced computing thesis at Imperial College London.
Giraffe ranked somewhere in the middle of the rankings for chess engines, but outclassed many of its contemporaries. While most chess engines simply run through all the possible moves sequentially as quickly as possible, Giraffe plays by simulating perception. That’s a quixotic way of saying it doesn’t just brute force the calculations, but as an alternative relies on patterns learned from chess games played by humans.
But on January 21—six days before DeepMind revealed the AlphaGo engine—Lai announced that he was discontinuing his creation. He had been hired by Google DeepMind. Machine erudition can be considered a subfield of artificial aptitude, but it has come to include so much that it’s arguably a field of its own.