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In October 2012 AlexNet, a deep neural network built by a University of Toronto team, won the ImageNet image-classification challenge by a wide margin. Its result showed that large neural networks trained on GPUs could outperform hand-designed vision methods.
On 13 April 2010, Fei-Fei Li announced the first ImageNet Large Scale Visual Recognition Challenge, a 1,000-category image categorization benchmark. It ran for eight editions, from 2010 to 2017.
An open competition run by Netflix from 2006 to 2009 that offered $1,000,000 to any team able to improve its movie recommendation algorithm by 10%, and released 100 million anonymous ratings for contestants to work with.
