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In reply to: The Octonion Math That Could Underpin Physics | Quanta Magazine

The recommendation problem is designed to give a recommendation for products that users will like. Consider the case of Netflix. It knows what films you’ve watched. It knows what all of its other millions of users have watched. Given this information, what are you likely to want to watch next?

You can think of this data as being arranged in a giant grid, or matrix, with movies listed across the top, users listed down the side, and values at points in the grid quantifying whether, or to what extent, each user likes each film. A good algorithm would generate recommendations by quickly and accurately recognizing similarities between movies and users and filling in the blanks in the matrix.