Machine Learning at Facebook: Systems and Infrastructure at Scale

Machine Learning enables key capabilities at Facebook including ranking posts for News Feed and Instagram, speech and text translations, and photo and real-time video classification, object detection and tracking for augmented and virtual reality (VR). This talk will give an overview of the applications, the infrastructure that supports these use cases, and the systems challenges that come from usage of a diverse set of models at scale.

Bilge Acun

Bilge Acun is a Research Scientist at Facebook AI Research (FAIR). Her research interests include Systems for Machine Learning, Parallel and Distributed Computing, Energy Efficient Computing, High Performance Computing (HPC). She received her Ph.D. degree in 2017 at the Department of Computer Science at Universtiy of Illinois at Urbana-Champaign. Her dissertation received the 2018 ACM SigHPC Dissertation Award Honorable Mention. Before joining Facebook, she worked at the IBM Thomas J. Watson Research Center as a Research Staff Member.