The Netflix Prize, a computing challenge that's been compared to scaling Mount Everest and flummoxed programmers for more than three years, has been summited. Two front runners in the contest, Team Pragmatic Theory and Team Bellkor in Chaos, joined forces and submitted an algorithm that was 10.05 percent better than the one Netflix uses to recommend movies to its subscribers. The result was published on the Netflix Prize leader board on Friday (June 26).
Assuming the results are verified, that's enough to edge the 10 percent improvement requirement by a hair and qualify them to win a $1 million prize, first announced in February 2006. The contest is an example of so-called Prize economics, where competitive incentives are offered as an alternative to in-house research and development. Netflix has said that winning a 10 percent improvement on its recommendation algorithm for $1 million would be a tremendous bargain.
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