At Facebook AI, we're connecting people to what they care about, powering new, meaningful experiences, and advancing the state-of-the-art through open research and accessible tooling.
See Our ResearchRESEARCH
Our teams accelerate research breakthroughs across both existing and new learning paradigms to develop state-of-the-art AI that has a positive impact on people and society.
Understanding the visual world around us
Creating personalized and meaningful interactions
Building AI solutions to keep people safe on social platforms
Next generation text understanding and generation
Connecting people to what's most meaningful
Developing novel algorithmic, software, and hardware techniques
Laying foundations for artificial intelligence
Powering voice interfaces and audio content understanding
Building algorithms inspired by, and compatible with, human cognition
Reinforcement learning, robotics, graphics, and more coming soon
We introduce a new evaluation protocol and associated dataset (VQA-Rephrasings) and show that state-of-the-art VQA models are notoriously brittle to linguistic variations in questions.
To achieve the long-term goal of machines being able to engage humans in conversation, our models should be engaging.
This paper studies an approach that aims to make image-recognition systems robust against adversarial images by performing nearest-neighbor searches for similar images in a web-scale database of billions of unlabeled images.
TOOLS
Accelerate development with tools that enable the workflow from research prototyping to deployment.
Tap into the latest breakthroughs developed by Facebook AI and deployed in products used by billions.
Work with a broad ecosystem of open source tools and libraries designed to be modular and interoperable.
PyTorch is an open source deep learning framework built to be flexible and modular for research, with the stability and support needed for production deployment. It enables fast, flexible experimentation through a tape-based autograd system designed for immediate and python-like execution.
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