Artificial Intelligence

Advancing the field of machine intelligence

We are committed to advancing the field of machine intelligence and are creating new technologies to give people better ways to communicate. In short, to solve AI.

Facebook Artificial Intelligence researchers seek to understand and develop systems with human-level intelligence by advancing the longer-term academic problems surrounding AI. Our research covers the full spectrum of topics related to AI, and to deriving knowledge from data: theory, algorithms, applications, software infrastructure and hardware infrastructure. Long-term objectives of understanding intelligence and building intelligent machines are bold and ambitious, and we know that making significant progress towards AI can’t be done in isolation. That’s why we actively engage with the research community through publications, open source software, participation in technical conferences and workshops, and collaborations with colleagues in academia.

Facebook AI researchers work from our offices around the globe: Menlo Park, New York City, Seattle, Pittsburgh, Montreal, Paris, Tel Aviv and London.

“We have incredible people in FAIR who are making significant progress in AI, but to really move the bar it’s equally as important to be outward focused. To push the envelope, push the science and technology forward, we must be actively engaged with the research community. We publish a lot of things we do, distribute a lot of code on open-source, and engage deeply with academia to drive the progress.” Yann LeCun, VP & Chief AI Scientist

Latest Publications

All Publications

ICASSP - June 6, 2021

Multi-Channel Speech Enhancement Using Graph Neural Networks

Panagiotis Tzirakis, Anurag Kumar, Jacob Donley

Innovative Technology at the Interface of Finance and Operations - March 31, 2021

Market Equilibrium Models in Large-Scale Internet Markets

Christian Kroer, Nicolas E. Stier-Moses

IJCAI - January 5, 2021

IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL

Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam

IEEE Transactions on Automatic Control - January 1, 2021

Asynchronous Gradient-Push

Mahmoud Assran, Michael Rabbat

For more information about Artificial Intelligence research at Facebook, visit facebook.ai.

Open Research Awards

View All Open Research Awards
February 24, 2021

Request for proposals on sample-efficient sequential Bayesian decision making

With this RFP, we hope to deepen our ties to the academic research community by seeking out innovative ideas and applications of Bayesian optimization that further advance the field. We are committed to open source and will help awardees make the products of this RFP available to the public as part of BoTorch.

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