Facebook Research at Facebook
Facebook AI Research Launches Partnership Program
by Serkan Piantino, Florent Perronninon Thursday
Facebook AI Research (FAIR)
Blog
We announced a new initiative called the Facebook AI Research Partnership Program.
Teaching Machines To See and Understand
by Ari Entinabout 3 months ago
Facebook AI Research (FAIR)
Blog
Facebook's Artificial Intelligence team is working to build smart systems that can enhance people's lives. Watch this video to learn about how we're approaching AI research and the impact this work...
Facebook AI Research Partnership Program Application
by Ari Entinon Thursday
Facebook AI Research (FAIR)
Blog
Apply for the Facebook AI Research Partnership Program.

Highlights

Facebook AI Research Launches Partnership Program
by Serkan Piantino, Florent Perronninon Thursday
Blog post
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
by Alec Radford, Luke Metz, Soumith Chintalaabout 2 months ago
Publication

About Facebook AI Research (FAIR)

We’re committed to advancing the field of machine intelligence and developing technologies that give people better ways to communicate. In the long term, we seek to understand intelligence and make intelligent machines. How will we accomplish all this? By building the best AI lab in the world.

Research at the lab covers the full spectrum of topics related to AI, and to deriving knowledge from data: theory, algorithms, applications, software infrastructure and hardware infrastructure.

Our long-term objectives of understanding intelligence and building intelligent machines are bold and ambitious. But making significant progress towards AI can't be done in isolation, and will require the full engagement of the international research community. Everyone at Facebook strongly believes that scientific and technological progress comes from open interactions within the research community. In that spirit, Facebook AI researchers are expected to contribute to the research community through publications, open source software, participation in technical conferences and workshops, and through collaborations with colleagues in academia.

Publications

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
We stabilize Generative Adversarial networks with some architectural constraints and visualize the internals of the networks.
by Alec Radford, Luke Metz, Soumith Chintala2016 International Conference on Learning RepresentationsJanuary
Simple bag-of-words baseline for visual question answering
Environment for simple 2D maze games, designed as a sandbox for machine learning approaches to reasoning and planning
by Bolei Zhou, Yuandong Tian, Sainbayar Sukhbaatar, Arthur Szlam, Rob FergusArXiv PrePrintDecember 2015
A Roadmap towards Machine Intelligence
We describe one possible roadmap how to develop intelligent machines with communication skills that can perform useful tasks for us.
by Tomas Mikolov, Armand Joulin, Marco BaroniArXiv PrePrintNovember 2015
View more publications

Topics and Resources

  • Mathematics of data representation and analysis
  • Learning theory
  • Optimization
  • Learning principles
  • Learning architectures and algorithms
  • Knowledge representation
  • Reasoning and inference
  • Image, text, speech, audio, and video analysis and understanding
  • Distributed systems and software environments for AI
  • …and many related domains



"If your dream is to solve AI, then Facebook— with its incredible infrastructure, rich data and top talent—is simply the most exciting place to be."
Director, Facebook AI Research

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