We're advancing the state-of-the-art in artificial intelligence through fundamental and applied research in open collaboration with the community.

Notable Papers



GrokNet: Unified Computer Vision Model Trunk and Embeddings For Commerce

Sean Bell

Yiqun Liu

Sami Alsheikh

Yina Tang...



Live Face De-Identification in Video

Oran Gafni

Lior Wolf

Yaniv Taigman

International Conference on Computer Vision (ICCV)


Single-Network Whole-Body Pose Estimation

Gines Hidalgo

Yaadhav Raaj

Haroon Idrees

Donglai Xiang...

International Conference on Computer Vision (ICCV)


A Universal Music Translation Network

Noam Mor

Lior Wolf

Adam Polyak

Yaniv Taigman

International Conference on Learning Representations (ICLR)

Latest Publications

March 08, 2023


The Casual Conversations v2 Dataset

Bilal Porgali, Vítor Albiero, Jordan Ryda, Cristian Canton Ferrer, Caner Hazirbas

March 08, 2023

February 23, 2023


LLaMA: Open and Efficient Foundation Language Models

Faisal Azhar, Hugo Touvron, Armand Joulin, Aurelien Rodriguez, Baptiste Rozière, Eric Hambro, Gautier Izacard, Guillaume Lample, Marie-Anne Lachaux, Naman Goyal, Thibaut Lavril, Timothee Lacroix, Xavier Martinet, Edouard Grave

February 23, 2023

February 21, 2023



ArchRepair: Block-Level Architecture-Oriented Repairing for Deep Neural Networks

Felix Xu, Fuyuan Zhang, Hua Qi, Jianjun Zhao, Jianlang Chen, Lei Ma, Qing Guo, Zhijie Wang

February 21, 2023

February 20, 2023



UNIREX: A Unified Learning Framework for Language Model Rationale Extraction

Maziar Sanjabi, Aaron Chan, Hamed Firooz, Lambert Mathias, Liang Tan, Shaoliang Nie, Xiaochang Peng, Xiang Ren

February 20, 2023

Fundamental & Applied Research

At Facebook AI, we conduct both fundamental and applied research to advance our understanding and impact product experiences. We publish our discoveries in peer reviewed academic journals and conferences, and build AI technologies used by billions of people around the world.

Fundamental Research

FAIR seeks to further our fundamental understanding in both new and existing domains, covering the full spectrum of topics related to AI, with the mission of advancing the state-of-the-art of AI through open research for the benefit of all.

Along with the key principles of Facebook AI - openness, collaboration, excellence, and scale - we believe FAIR researchers also need to have the freedom and autonomy to design and follow their own research agendas so they can take on the most impactful work and develop the most disruptive projects, all while sharing their results with the community.

Applied Research

Facebook AI Applied Research engages in cutting-edge research that can improve and power new product experiences at huge scale for our community. Building on Facebook AI's key principles of openness, collaboration, excellence, and scale, we make big, bold research investments focused on building social value and bringing the world closer together.

Our Values

We align our fundamental and applied research efforts and applications around a few key principles:


We believe the latest advancements in AI should be published and open-sourced for the community to learn about and build upon.


We collaborate openly with both internal and external partners to share knowledge and cultivate diverse perspectives and needs.


There is no shortage of new areas to explore in AI - our researchers focus on the projects that we believe will have the most positive impact on people and society.


To bring the benefits of AI to more people and improve accessibility, our research must account for both large scale data and computation needs.

Request for Proposals

Meta AI is pleased to invite university faculty to submit proposals that will help accelerate research and advance the state-of-the-art in artificial intelligence.

Help Us Pioneer the Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.