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| Photo: JumpStory |
It was a war of titans you likely never heard about. One year ago, two of the world’s strongest and most radically different chess engines fought a pitched, 100-game battle to decide the future of computer chess.
On one side was Stockfish 8. This world-champion
program approaches chess like dynamite handles a boulder—with sheer
force, churning through 60 million potential moves per second. Of these
millions of moves, Stockfish picks what it sees as the very best
one—with “best” defined by a complex, hand-tuned algorithm co-designed
by computer scientists and chess grandmasters. That algorithm values a
delicate balance of factors like pawn positions and the safety of its
king.
On the other side was a new program
called AlphaZero (the "zero" meaning no human knowledge in the loop), a
chess engine in some ways very much weaker than Stockfish—powering
through just 1/100th as many moves per second as its opponent. But
AlphaZero is an entirely different machine. Instead of deducing the
“best” moves with an algorithm designed by outside experts, it learns
strategy by itself through an artificial-intelligence technique called
machine learning. Its programmers merely tuned it with the basic rules
of chess and allowed it to play several million games against itself. As
it learned, AlphaZero gradually pieced together its own strategy...
British chess grandmaster Matthew Sadler and mathematician and
chessmaster Natasha Regan are still piecing together how AlphaZero’s
strategy works in their new book, Game Changer.
We’re breaking open two moves in just one of the games to show the
aggressive style, what it does, and what humans can learn from our new
chess champion.
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| Game Changer: AlphaZero's Groundbreaking Chess Strategies and the Promise of AI |
