Netflix contest to improve recommendation engine--ILSes should follow suit

Netflix is holding a contest to improve their recommendation.  The sum of $1 million will go to the first person to improve the accuracy of its personal-preference-profile-based movie recommendations.  From the NY Times article:

To win the prize...a contestant will have to devise a system that is more accurate than the company’s current recommendation system by at least 10 percent. And to improve the quality of research, Netflix is making available to the public 100 million of its customers’ movie ratings, a database the company says is the largest of its kind ever released.

Can you imagine what would happen if III or other ILS vendors conducted a similar contest?  Make our relevancy ranking work better, please.  Reduce the clunk and clutter in our code, please.  Add RSS to our services, please.  Make our products more usable and clearer, please.

As Netflix admits in the article, they don't know how to do it themselves--otherwise they would have done it already.  Same with the ILSes.  Clearly they don't know how to do it on their own, so why not tap the prize-money-driven world of coders and software engineers who could help you?