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Facebook Artificial Intelligence Research (FAIR) seeks to understand and develop systems with human-level intelligence by advancing the longer-term academic problems surrounding AI. Our research covers theory, algorithms, applications, software infrastructure, and hardware infrastructure across deep learning, computer vision, natural language processing, speech, and reasoning.

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Open-sourcing FBGEMM and QNNPACK, foundational tools for AI performance, on engineering.fb.com, Facebook's Engineering blog

Training AI agents to solve unfamiliar tasks

Data distillation makes omni-supervised learning possible on engineering.fb.com, Facebook's Engineering blog

AI Research SEP 24, 2018

Data distillation makes omni-supervised learning possible

2018 @Scale Conference

AI Research SEP 17, 2018

2018 @Scale Conference recap

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Bayesian optimization for tuning online systems with A/B tests

AI Research SEP 17, 2018

Efficient tuning of online systems using Bayesian optimization

AI Research SEP 13, 2018

Glow: A community-driven approach to AI infrastructure

AI Research SEP 13, 2018

Finding and fixing software bugs automatically with SapFix and Sapienz

Two-step model architecture: The first step performs word detection based on Faster R-CNN. The second step performs word recognition using a fully convolutional model with CTC loss. The two models are trained independently.

AI Research SEP 11, 2018

Rosetta: Understanding text in images and videos with machine learning

Animation illustrating back-translation

AI Research SEP 7, 2018

Scaling neural machine translation to bigger data sets with faster training and inference

Unsupervised MT: A novel approach to provide fast, accurate translations for more languages on engineering.fb.com, Facebook's Engineering blog

AI Research AUG 31, 2018

Unsupervised machine translation: A novel approach to provide fast, accurate translations for more languages

NYU School of Medicine’s Department of Radiology chair Michael Recht, MD, Daniel Sodickson, MD, vice chair for research and director of the Center for Advanced Imaging Innovation and Yvonne Lui, MD, director of artificial intelligence, examine a knee MRI at NYU Langone Health in August, 2018. Radiologists from NYU School of Medicine will be embarking on a research collaboration with Facebook to speed up MRI by up to 10 times faster through artificial intelligence.

AI Research AUG 20, 2018

Facebook and NYU School of Medicine launch research collaboration to improve MRI

AI Research JUL 17, 2018

Facebook AI Research Expands With New Academic Collaborations

AI Research JUL 13, 2018

Facebook researchers win Test of Time award

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Talk the Walk: Teaching AI systems to navigate New York through language

ONNX expansion speeds AI development

Under the hood: Multilingual embeddings

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