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Computers do not play chess well. They play chess badly, but incredibly fast. Deep Blue was capable of analyzing 200 million board positions a second, but it co

by beat 13y ago

Computers do not play chess well. They play chess badly, but incredibly fast. Deep Blue was capable of analyzing 200 million board positions a second, but it could be defeated regularly (if not a majority of the time) by a human being. I'm pretty sure Kasparov wasn't calculating 200 million board positions in his head! Pick a harder problem - the game of Go. Computers have only recently been able to beat a reasonably talented child or inexperienced adult at the game. When the data set becomes too large to brute-force (Go has many more possibilities than chess), computers can't hold a candle to human intuition. Sure, it's possible that at some point, computers will be able to produce better results than humans at some surprising real-world tasks. But that doesn't mean computers will do them well. Doing it well versus doing it very fast are two entirely different things. If you can't understand the distinction, you can't understand where humans will continue to outperform computers.

eli_gottlieb 13y ago
Deep Blue was using search-tree algorithms, not learning algorithms. Has anyone tried putting modern machine-learning engines up against professional chess players?
- beat 13y ago
  Given the incredibly well-documented history of professional chess, learning during play isn't efficient. If you're going up against a player, just program every game they've ever played professionally into the system to study their behavior. You can be sure the human players do something similar. Heck, I'm fairly certain that every master game ever recorded was shoved into Deep Blue and other high-end chess programs.
saosebastiao 13y ago
What does it matter if Kasparov had sophisticated heuristics that let him bypass considering a few hundred million positions? Deep Blue won, even with its dumb brute force approach. A self driving car may have to use billions more calculations per second in order to drive a car than I do. And yet, they have driven hundreds of thousands of miles without accident, which is more than I can claim for myself. The crazy thing about human heuristics is that they can be learned. Deep Blue was created more than 15 years ago, but in the time since, Houdini can do even better than Deep Blue, and it can do it on a dual core laptop. How? By learning heuristics from Grand Masters.

by beat 13y ago

eli_gottlieb 13y ago

Deep Blue was using search-tree algorithms, not learning algorithms. Has anyone tried putting modern machine-learning engines up against professional chess players?

beat 13y ago
Given the incredibly well-documented history of professional chess, learning during play isn't efficient. If you're going up against a player, just program every game they've ever played professionally into the system to study their behavior. You can be sure the human players do something similar. Heck, I'm fairly certain that every master game ever recorded was shoved into Deep Blue and other high-end chess programs.

saosebastiao 13y ago

What does it matter if Kasparov had sophisticated heuristics that let him bypass considering a few hundred million positions? Deep Blue won, even with its dumb brute force approach. A self driving car may have to use billions more calculations per second in order to drive a car than I do. And yet, they have driven hundreds of thousands of miles without accident, which is more than I can claim for myself. The crazy thing about human heuristics is that they can be learned. Deep Blue was created more than 15 years ago, but in the time since, Houdini can do even better than Deep Blue, and it can do it on a dual core laptop. How? By learning heuristics from Grand Masters.