My point was that go and chess are not actually understood. We don’t actually know how they’re played. There are hacks that allow programs to get good at those games without actually understanding the patterns involved, but recognizing the patterns involved is what humans actually find interesting about the games.
That’s not really true. In the last two decades or so, there has been lots of progress in reverse-engineering of how chess masters think and incorporating that knowledge into chess engines. Of course, in some cases such knowledge is basically useless, so it’s not pursued much. For example, there’s no point in teaching computers the heuristics that humans use to recognize immediate tactical combinations where a brute force search would be impossible for humans, but a computer can perform it in a millisecond.
However, when it comes to long-term positional strategy, brute-force search is useless, no matter how fast, and until the mid-1990s, top grandmasters could still reliably beat computers by avoiding tactics and pursuing long-term strategic advantage. That’s not possible any more, since computers actually can think strategically now. (This outcome was disappointing in a sense, since it basically turned out that the human grandmasters’ extraordinary strategic abilities are much more due to recognizing a multitude of patterns learned from experience than flashes of brilliant insight.)
Even the relative importance of brute-force search capabilities has declined greatly. To take one example, the Deep Blue engines that famously matched Kasparov’s ability in 1996 and 1997 relied on specialized hardware that enabled them to evaluate something like 100-200 million positions per second, while a few years later, the Fritz and Junior engines successfully drew against him even though their search capabilities were smaller by two orders of magnitude. In 2006, the world champion Kramnik was soundly defeated by an engine evaluating mere 8 million positions per second, which would have been unthinkable a decade earlier.
Even the relative importance of brute-force search capabilities has declined greatly.
Thanks for updating me; I was indeed thinking of Deep Blue in the mid 90s. Good to know that chess programs are becoming more intelligent and less forceful.
(This outcome was disappointing in a sense, since it basically turned out that the human grandmasters’ extraordinary strategic abilities are much more due to recognizing a multitude of patterns learned from experience than flashes of brilliant insight.)
This is what I would expect; a flash of brilliant insight is what recognizing a pattern feels like from the inside.
Blueberry:
That’s not really true. In the last two decades or so, there has been lots of progress in reverse-engineering of how chess masters think and incorporating that knowledge into chess engines. Of course, in some cases such knowledge is basically useless, so it’s not pursued much. For example, there’s no point in teaching computers the heuristics that humans use to recognize immediate tactical combinations where a brute force search would be impossible for humans, but a computer can perform it in a millisecond.
However, when it comes to long-term positional strategy, brute-force search is useless, no matter how fast, and until the mid-1990s, top grandmasters could still reliably beat computers by avoiding tactics and pursuing long-term strategic advantage. That’s not possible any more, since computers actually can think strategically now. (This outcome was disappointing in a sense, since it basically turned out that the human grandmasters’ extraordinary strategic abilities are much more due to recognizing a multitude of patterns learned from experience than flashes of brilliant insight.)
Even the relative importance of brute-force search capabilities has declined greatly. To take one example, the Deep Blue engines that famously matched Kasparov’s ability in 1996 and 1997 relied on specialized hardware that enabled them to evaluate something like 100-200 million positions per second, while a few years later, the Fritz and Junior engines successfully drew against him even though their search capabilities were smaller by two orders of magnitude. In 2006, the world champion Kramnik was soundly defeated by an engine evaluating mere 8 million positions per second, which would have been unthinkable a decade earlier.
Thanks for updating me; I was indeed thinking of Deep Blue in the mid 90s. Good to know that chess programs are becoming more intelligent and less forceful.
This is what I would expect; a flash of brilliant insight is what recognizing a pattern feels like from the inside.