Natural language problem solving could be applied to any number of disciplines. In UC, I think it can spur advancements in social networking.

I'm a big time Jeopardy fan, so I was planted squarely in front of the TV for the three-day challenge between IBM’s Watson and two of the most enduring champions in the famed show's history. What we got to see was a world-class demonstration of computer technology taking on some of the most difficult challenges in natural language processing- and beating the pants off two really smart guys. More than an academic exercise however, Watson demonstrated capabilities that could open the door to whole new realms of computer applications that fall right in the middle of UC.

The first round that stretched over two days ended with Watson's total at $35,734 crushing 74-game winner Ken Jennings ($4,800) and top money winner Brad Rutter ($10,400). After the second game, a final score was $77,147 for Watson, $24,000 for Jennings, and $21,600 for Rutter. Jennings was in the second game up to the Final Jeopardy question, but all three contestants got Bram Stoker, author of Dracula, as the question for "An Account of the Principalities of Wallachia and Moldovia inspired this author's most famous novel."

We all know computers can add up numbers, but the more human-like the task, the more challenging it becomes for a computer to compete. Watson combines the ability to access terabytes of information, process the subtleties of human language (along with the puns and wordplay Jeopardy questions are renowned for), and present three likely answers with probabilities in a matter of seconds. Combine that with a smart human, and you’ve got a killer problem solver.

The technical challenges were enormous. Nova ran a program on the development and fine tuning of Watson's decision algorithms, where you got a real look at what’s involved in teaching a computer to recognize the types of subtle distinctions that the human brain makes unconsciously. Of course when Watson misses, it's in monumental fashion. Example: "What do grasshoppers eat?" Answer: "Kosher."

While taking on Jeopardy was great PR coup for IBM, it was far more than a trivial pursuit. With the masses of new data people are faced with each day, the value of this development is truly awesome. Watson's "Artificial Intelligence" is clearly distinct from "thinking". What Watson is doing is isolating key words, looking for associations, searching databases, applying probabilities, and arriving at a likely conclusion. James Hendler, professor of computer and cognitive science at Rensselaer Polytechnic Institute hit it on the head when he said, "Using what humans are good at and what Watson is good at, together we can build systems that solve problems that neither of us can solve alone."

That type of natural language problem solving (or more correctly "problem assisting") ability could be applied to any number of disciplines. Medical diagnosis was one application immediately identified, but in UC I think it can spur advancements in social networking. Social systems today can search databases for key words and use that information to link people with similar interests or capabilities. We are seeing elements of that in UC systems, but Watson's working at a level way beyond that. I don't think it was a coincidence that at IBM's recent Lotusphere event in Orlando, the theme was "Get Social. Do Business".

IBM has become king of the "big idea" as evidenced by their Smarter Planet advertising campaign. No one doubts the company's ability to operate on that level, but their challenge will be to translate those ideas into marketable products they can use to best their competitors.

Jeopardy champions brains and wit, so the most enduring image was David Ferrucci from IBM's Thomas J. Watson Research Center and the rest of the PhDs on the IBM team watching Watson’s performance and acting like a bunch of proud parents at a Little league game. That's the kind of thing that makes you proud to be a geek.