NEW YORK, Sept. 21 (UPI) -- The U.S. online movie rental service Netflix Inc. said Monday it has awarded a $1 million prize to the team that best improved its recommendation system.
The award was presented after a three-year competition that brought submissions by more than 40,000 teams variously made up of engineers, statisticians and researchers from 186 countries.
The winning team is comprised of software and electrical engineers, statisticians and machine learning researchers from Austria, Canada, Israel and the United States. All seven team members -- Bob Bell, Martin Chabbert, Michael Jahrer, Yehuda Koren, Martin Piotte, Andreas Toscher and Chris Volinsky -- attended the awards ceremony.
"We had a bona fide race right to the very end," Netflix co-founder and Chief Executive Officer Reed Hastings said in a statement. "Teams that had previously battled it out independently joined forces ... . New submissions arrived fast and furious in the closing hours and the competition had more twists and turns than 'The Crying Game,' 'The Usual Suspects' and all the 'Bourne' movies wrapped into one."
Moments after bestowing the $1 million prize, Netflix announced a second $1 million challenge, asking the world's computer science and machine-learning communities to keep the improvements coming.
"Accurately predicting the movies Netflix members will love is a key component of our service," said Chief Product Officer Neil Hunt. "This extreme level of personalization is like entering a video store with 100,000 titles and having those that are most interesting to you fly off the shelves and line up in front of you. We take the guesswork out of renting by presenting the movies and TV episodes we believe each Netflix member will most enjoy."