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
Our PeopleView All People
Vice President of Artificial Intelligence
Artificial Intelligence, Machine Learning, Natural Language Processing & Speech
Artificial Intelligence, Computer Vision
Director, Research Science
Managing Director, FAIR
Chief AI Scientist
Latest PublicationsAll Publications
IJCAI - January 5, 2021
Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
IEEE Transactions on Automatic Control - January 1, 2021
Mahmoud Assran, Michael Rabbat
COLING - December 8, 2020
Zhenpeng Zhou, Ahmad Beirami, Paul A. Crook, Pararth Shah, Rajen Subba, Alborz Geramifard
COLING - December 8, 2020
Best Practices for Data-Efficient Modeling in NLG: How to Train Production-Ready Neural Models with Less Data
Ankit Arun, Soumya Batra, Vikas Bhardwaj, Ashwini Challa, Pinar Donmez, Peyman Heidari, Hakan Inan, Shashank Jain, Anuj Kumar, Shawn Mei, Karthik Mohan, Michael White
Latest NewsAll News
For more information about Artificial Intelligence research at Facebook, visit facebook.ai.
1:01 | August 31, 2020
1:31 | August 31, 2020
2:00 | August 31, 2020
1:30 | August 24, 2020