by Angela Guess
Hope Reese recently wrote in TechRepublic, “It’s no longer up for debate that AI is set to have a major impact on most businesses, if it isn’t already—and any company that wants to stay ahead must figure out how to integrate the new technology into its structure. But how is a successful AI platform built? On Wednesday, at the Applied Artificial Intelligence Conference in San Francisco, hosted by BootstrapLabs, Hussein Mehanna, the director of core machine learning at Facebook, tackled this question. In Mehanna’s session, he explained how Facebook developed its own machine learning platform, and how Facebook employees are using it. In 2012, Mehanna said, Facebook’s AI platform was ‘a snowball of complexity’—a system that slowed progress down significantly. ‘We had to do something,’ he said.”
Reese goes on, “Mehanna described the development of FBLearner Flow, a machine learning platform that could take data, produce machine learning models, feed the information back to FBlearner predictor, and integrate the information back into the system. The information is then used in Facebook products like Search, Ads and News Feed… A quarter of the engineering workforce at Facebook leverages the system. ‘We made AI available to our engineers, without them having to learn more about AI,’ Mehanna said. ‘We want to make AI as simple to use as a possible, so that everybody can leverage it to build better products at Facebook’.”
Photo credit: Facebook