Psyching Out Computer Chess Players

Chess programs keep getting better, but grandmasters have learned to anticipate their game

3 min read

The more deeply a computer chess program is allowed to calculate, the better it plays, and with the inexorable march of Moore's Law, the programs have gotten much better over the years. Why, then, do the very best grandmasters still hold their own against the silicon beasts?

A few months ago, in New York City, Garry Kasparov, the top-rated player in the world, drew a match against a leading chess program from Germany that runs on an Intel Xeon server with four 2.8-GHz processors and 4GB of RAM. Kasparov faced a special, three-dimensional-display version of his opponent [see photo, " 3-D Chess"]. The previous year he had drawn the Israeli program Deep Junior in the same venue. Sometime before that match, Vladimir Kramnik, ranked second worldwide, had drawn an earlier version of Fritz.

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Why Functional Programming Should Be the Future of Software Development

It’s hard to learn, but your code will produce fewer nasty surprises

11 min read
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A plate of spaghetti made from code
Shira Inbar
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You’d expectthe longest and most costly phase in the lifecycle of a software product to be the initial development of the system, when all those great features are first imagined and then created. In fact, the hardest part comes later, during the maintenance phase. That’s when programmers pay the price for the shortcuts they took during development.

So why did they take shortcuts? Maybe they didn’t realize that they were cutting any corners. Only when their code was deployed and exercised by a lot of users did its hidden flaws come to light. And maybe the developers were rushed. Time-to-market pressures would almost guarantee that their software will contain more bugs than it would otherwise.

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