![]() ![]() The AI team at Facebook was launched six years ago with Yann LeCun joining the team, recruited by Mark. Then the third pillar, which many people maybe know more about is the research pillar. There’s a lot of work to be done there and we can talk about it if you’re interested. So it’s PyTorch, it’s all the models around it, but also all the systems around PyTorch. The goal for us is really to rethink the way software engineering is done in the age of machine learning. So not only we develop this, but we actually try to engage as much as possible the community. We are the developers of PyTorch and we think this is really a community program. The second thing we do, and hopefully a lot of people have heard about it is to develop some new systems for ourselves and for the community. And then also looking at the future of things like augmented reality or some new endeavors like commerce or remote presence are two big things. Things like, ‘Hey, how do you moderate and what’s happening on Facebook automatically? How do you do a ranking recommendation for both ads and the content?’ You know when you fire up your Instagram app or your Facebook apps, this is basically determined by a pretty sophisticated deep learning algorithm. One is, we work with products to make some big product advances. My team is the core AI team, whose role is really to advance AI and we do three different things. You’re thinking of thousands of engineers and researchers who the majority of their time work on ML systems. Who’s the team, what do people do, how many offices, how many researchers?ĪI at Facebook is a pretty big endeavor. I’d love to start with what AI means at Facebook, from an organizational perspective. As always, many thanks for the Data Driven NYC team, Jack Cohen and Diego Gutierrez, as well as Karissa Domondon for the transcript.įULL TRANSCRIPT (lightly edited for brevity and clarity): ![]()
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