I used to be really into a good ‘ol game of chess. I still am, I suppose. But it got old. There’s only so many possibilities — Shannon’s number gives the lower bound to be only 10^3^, to be precise, and the upper bound has been calculated at less than 2^155^, which is less than 10^46.7^. That’s factoring in all possible, legal moves, and factoring out invalid or illegal moves. It doesn’t factor in that human players are not the most logical creatures and their playing can quickly become predictable. I mean, if you take a look at game theory, in “Guess Two Thirds of the Average” as played in the general population,[it’s statistically shown that humans do not think beyond three logical iterations]. Chess is grand, and a good match is always appreciated. But it just got old after a while.
Lately, I’ve been really into playing Go. Go is amazing, and I still suck at it. I could probably waste my life away learning Go strategy, and still not master the game. To compare it with chess, the maximum number of legal moves in Go is 2.08168199382×10^170^, more than 130 orders of magnitude higher. That’s also more than double the amount of particles in the universe. While super chess computers, such as Deep Blue, can beat World Champion chess players, young children can often beat even the best Go computers. However, as artificial intelligence continually develops to higher levels,that trend is beginning to change, which makes a computer’s aptitude for the game a useful measurement of its capability for human-like thought.
From the Wired Science article on Go-playing AIs:
read moreFaced with such extraordinary complexity, our brains somehow find a path, navigating the possibilities using mechanisms only dimly understood by science. Both of the programs that have recently defeated humans used variations on mathematical techniques originally developed by Manhattan Project physicists to coax order from pure randomness.
Called the Monte Carlo method, it has driven computer programs to defeat ranking human players six times in the last year. That’s a far cry from chess, the previous benchmark of human cognitive prowess, in which Deep Blue played Garry Kasparov to a panicked defeat in 1997, and Deep Fritz trounced Vladimir Kramnik in 2006. To continue the golf analogy, computer Go programs beat the equivalents of Chris Couch rather than Tiger Woods, and had a multi-stroke handicap. But even six victories was inconceivable not too long ago, and programmers say it won’t be long before computer domination is complete.
There is, however, an asterisk to the programs’ triumphs. Compared to the probabilistic foresight of our own efficiently configured biological processor — sporting 10^15^ neural connections, capable of 10^16^ calculations per second, times two — computer Go programs are inelegant. They rely on what Deep Blue designer Feng-Hsiung Hsu called the “substitution of search for judgment.” They crunch numbers.
“People hoped that if we …
