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The first week of July, 16 “beautiful minds� will show up at Bar-llan University in Ramat-Gan, Israel, and pair off for a weeklong series of grueling battles that pit brilliance against genius, strategy against tactics, thinking against sheer will against gamesmanship.

The occasion is the 12th World Computer Chess Championship, a competition that matches not man versus machine, but “machine� — computer chess programs with names like Shredder 7.04, Fritz 8 and Junior 8 — against “machine,� sanctioned by the International Computer Games Association. In 2003, according to “Computer Chess History� by Bill Wall, Shredder won the tournament after a playoff with Deep Fritz in Graz, Austria.

As we reflect on computer chess wizardry, three things come to mind. The first that may be tough to remember is that it's human intelligence, not artificial intelligence, combined with lightning speed in the search engines that enables Shredder or Fritz or IBM's famed Deep Blue to compete at world-class levels. Under the skin of those Athlon microprocessor chips and untold gobs of RAM, people are the ones that actually write the programs that evaluate and map out the moves four, five, six or 30 moves deep. Tel Aviv programmers Amir Ban and Shay Bushinksy took 10 years to program Deep Blue's offspring Deep Junior.

The second thing to keep in mind about computer chess expertise is that a player has an average of 38 moves to make from every position. From there, the math gets complex. For instance, when Deep Blue played — and lost to — Garry Kasparov in Philadelphia in 1996, the computer was calculating 50 billion positions every 3 minutes. Kasparov was calculating 10 positions every 3 minutes. For the rematch in May the following year, Deep Blue evaluated 200 million moves per second, and Kasparov lost.

Third realization: despite all that warp speed calculation power, the notion of truly learning from one's mistakes is beyond fancy mathematical processes of elimination.

These thoughts actually arise in connection with the intriguing perspective Rob Frasca, president of Affinnova brings to our analysis of the challenges market research faces in Senior Editor Louise Witt's article on consumer intelligence's immediate future, “Inside Intent.� Affinnova, like the other thought leaders who comment on what it takes to truly know consumers, has begun to realize that quantitative and qualitative techniques and methodologies most likely need to be integrated and interactive to get at the real meanings of consumer behavior and real ways to influence it.

If there's an average of 38 options a chess player has for every position he's in, imagine the matrix of choices consumers have for every buying decision they make. Even as technological wonders come to market research, no artificial intelligence exists that will lead an organization to absolute predictions about those decisions. So, beautiful minds will continue to team up with fabulous machines as clients of market research look for just one thing: results now.

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