Some of ai's recent achievements stand as extraordinary milestones of its progress, and others have insinuated themselves almost invisibly into our daily routines. In between these extremes, AI programs have become important tools in science and commerce. These three categories provide a useful way of organizing the state of AI today. First, I'll look at some of the headline-making systems appearing just before and just after the beginning of the twenty-first century, beginning with AI game-playing programs.

Games

Although getting computers to excel at games, such as chess and checkers, is thought by some to be a somewhat frivolous diversion from more serious work, computer game-playing has served as a laboratory for exploring new AI techniques–especially in heuristic search and in learning. In a previous chapter, for example, I explained how reinforcement learning methods were used to develop a championship-level backgammon program. From the earliest days of AI, people worked on programs to play chess and checkers, and now, mainly by using massive amounts of heuristically guided computation, computers are able to play these and other games better than humans can.

Chess

The big news in 1997 was the defeat of the world chess champion, Garry Kasparov, by IBM's “Deep Blue” chess-playing computer. (See Fig. 32.1.) The first time Kasparov played Deep Blue, in February 1996, Deep Blue won the first game but lost the match. But on May 11, 1997, a hardware-enhanced 1997 version (unofficially nicknamed “Deeper Blue”) won a six-game match (under regular chess tournament time controls) by two wins to one with three draws.