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Depends on the domain.

Why did DeepMind pick Go as a challenge rather than Chess?

Because with Chess you can store the entire search space in memory. With Go you can't.



> Because with Chess you can store the entire search space in memory.

That is incorrect.

Quoting from [0] > Chess has approximately 10^120 game paths. These positions comprise the problem search space. Typically, AI problems will have a very large space, too large to search or enumerate exhaustively.

But as Go has an even larger search space, it makes sense that DeepMind sees it as a bigger challenge.

[0] - http://www.cse.uaa.alaska.edu/~afkjm/cs405/handouts/search.p...


Deep Blue brute forced that search space. With 1997 hardware. They didn't have to look at 10^120 to beat Kasprov.

"The system could search to a depth of between six and eight pairs of moves—one white, one black—to a maximum of 20 or even more pairs in some situations" - https://www.scientificamerican.com/article/20-years-after-de...


Is chess already solved?


Effectively, yes. But I attach no greater philosophical significance to that than to say drilling holes is solved because most people can go buy a nice electric drill foR $30-$40. Flying to the moon is solved, too.




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