Facebook AIOvjeren akaunt

@facebookai

Facebook AI focuses on connecting people to what they care about, powering meaningful and safe experiences, advancing ML, and conducting open research.

Vrijeme pridruživanja: kolovoz 2018.

Medijski sadržaj

  1. 31. sij

    We are releasing HiPlot, a lightweight interactive visualization tool to help AI researchers discover correlations and patterns in high-dimensional data.

  2. 29. sij

    In a collaboration with universities in France and Taiwan, Facebook AI is releasing Polygames, a new open source framework that enables researchers to train AI systems through self-play in a wide range of strategy games.

  3. 24. sij

    We're releasing mBART, a new seq2seq multilingual pretraining system for machine translation across 25 languages. It gives significant improvements for document-level translation and low-resource languages. Read our paper to learn more:

  4. 24. sij

    Facebook's AI Residency program, which gives residents 12 months of practical experience in AI working with leading researchers, is accepting applications until January 31st! Current residents Diana and Eric discuss their experience in this Q&A:

  5. 23. sij

    Beat the Bot, which is a game exclusively for researchers on Messenger, helps provide researchers with high-signal data. We plan to open-source our dataset to help push dialogue research forward. Watch the video to learn more:

  6. 21. sij

    We’re releasing a major update to Facebook AI’s open source AI Habitat platform for training embodied AI agents in photorealistic 3D virtual environments. AI Habitat now supports interactive objects, realistic physics modeling, and more.

  7. 21. sij

    Facebook AI has effectively solved the task of point-goal navigation by AI agents in simulated environments, using only a camera, GPS, and compass data. Agents achieve 99.9% success in a variety of virtual settings, such as houses and offices.

  8. 15. sij

    We've open sourced VizSeq, a Python toolkit that makes it easy to visualize text generation outputs. With a user-friendly interface, VizSeq improves productivity and enables fast evaluation on large data sets.

  9. 14. sij

    By restructuring math expressions as a language, Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems.

  10. 13. sij

    We have open-sourced wav2letter@anywhere, an inference framework for online speech recognition that delivers state-of-the-art performance.

  11. 8. sij

    We’re looking back at some of our most notable posts from 2019. See the highlights and learn more about our work.

  12. Learn about LIGHT, a multiplayer text adventure game that enables researchers to study language and actions jointly in a game world. We've made the complete setup open-source and available to other researchers here:

  13. Thirty-four teams entered the first fastMRI challenge, seeking to develop new ways to use AI to make MRIs 10x faster with no loss in quality. Learn about the results here:

  14. Facebook AI has released Libri-light, the largest open source data set for speech recognition to date. This new benchmark helps researchers pretrain acoustic models to understand speech, with few to no labeled examples.

  15. VizSeq is a Python toolkit that provides a unified, scalable solution for simplified visual analysis on a wide variety of text generation tasks.

  16. We've achieved state-of-the-art results in Hanabi, a collaborative card game in which players must work together. We use a new real-time search method similar to the one used in Pluribus.

  17. Facebook AI Research seeks to further our fundamental understanding across the full spectrum of AI topics. We conduct research with a focus on openness, freedom, collaboration, excellence, and scale. Watch our video to learn more:

  18. As part of the fastMRI research project to use AI to speed up MRI scans, NYU Langone Health is making a new data set of de-identified brain MRIs available to researchers and Facebook AI is sharing additional tools and resources.

  19. As part of the fastMRI research project to use AI to speed up MRI scans, NYU Langone Health is making a new data set of de-identified brain MRIs available to researchers and Facebook AI is sharing additional tools and resources.

  20. Thank you all for coming to the Deepfake Detection Challenge launch event at . Register today to download the full data set and participate in the challenge:

Čini se da učitavanje traje već neko vrijeme.

Twitter je možda preopterećen ili ima kratkotrajnih poteškoća u radu. Pokušajte ponovno ili potražite dodatne informacije u odjeljku Status Twittera.

    Možda bi vam se svidjelo i ovo:

    ·