How Meta Uses Machine Learning

The article recaps the Fighting Abuse @Scale 2019 event, where experts from major tech companies gathered to discuss advanced technologies and strategies for combating online abuse, fraud, and spam.

The 2019 @Scale Conference brought together over 1,300 engineers to discuss challenges and innovations in building scalable applications and services.

The F8 2019 Day 2 keynote and session videos highlight advancements in AI tools, computer vision, self-supervised learning, and inclusive AR/VR frameworks.

The article announces the stable release of PyTorch 1. 0 at the NeurIPS conference, highlighting its new production-oriented features and extensive community growth.

The article celebrates the fifth anniversary of the Facebook AI Research (FAIR) group, highlighting its achievements in advancing AI through open research and collaboration.

The article provides a recap of the Data @Scale conference held in Boston, focusing on the challenges and advancements in large-scale data storage and analytics.

Facebook announced significant advancements in AI development with the release of PyTorch 1. 0, emphasizing a more robust ecosystem of partners and production capabilities.

The 2018 @Scale Conference brought together over 2,500 engineers to explore the challenges and innovations in building scalable applications and services.

Facebook research scientists Ronan Collobert and Jason Weston received the 2018 International Conference on Machine Learning (ICML) 'Test of Time Award' for their influential paper on a unified arc...

The article discusses advancements in image recognition using deep learning techniques that leverage hashtags as weakly supervised labels.

The article announces the release of PyTorch 1. 0, an open-source AI framework that bridges the gap between research and production.

The article discusses Facebook's advancements in artificial intelligence (AI) showcased at F8 2018, emphasizing open development frameworks like PyTorch 1. 0 and ONNX.

The Performance @Scale 2018 conference, hosted by Facebook, gathered over 275 performance engineering experts to discuss challenges in managing performance for large-scale services.

The article reviews Facebook's advancements in building immersive experiences in 2017, focusing on machine translation, computer vision, augmented reality (AR), and virtual reality (VR).

The article discusses the integration of art and technology through Augmented Reality (AR) at Facebook, focusing on the role of Simultaneous Localization and Mapping (SLAM) in creating immersive ex...

The Data @Scale 2017 conference brought together 350 engineers to discuss the challenges and innovations in large-scale storage systems and analytics.

The article discusses advancements in machine learning for computer vision, particularly focusing on a collaborative effort by Facebook engineers to significantly reduce the training time for the I...

The article introduces Big Basin, Facebook's next-generation AI hardware designed to enhance the performance of AI services.

The article recaps the Machine Learning @Scale 2017 conference, which brought together over 300 attendees from various companies to discuss technical challenges and advancements in large-scale appl...

The article discusses the advancements in computer vision at Facebook, focusing on the development of scalable systems like FBLearner Flow and Lumos for understanding images and videos.

The article discusses the engineering behind Facebook's Recommendations feature, which enhances local search by providing users with place suggestions based on social interactions.

The article discusses the development of Caffe2Go, a deep learning platform that enables real-time AI processing on mobile devices, specifically for style transfer in videos.

The article discusses Facebook's commitment to advancing innovation through AI, highlighting their research and development efforts in AI disciplines such as computer vision, language understanding...

The article discusses Torchnet, an open-source toolkit designed to facilitate rapid and reusable prototyping of deep learning systems using the Torch framework.

The article introduces FBLearner Flow, Facebook's machine learning platform designed to simplify and enhance the experimentation process for engineers.

The article discusses how Facebook's Applied Machine Learning (AML) team enhances user experiences through AI technologies.

The article discusses the development of Facebook's 'On This Day' feature, which allows users to relive and share memories.

The article discusses the efforts of Facebook's Connectivity Lab to improve internet connectivity in underserved areas through advanced mapping techniques.

The article announces the 2012-2013 Facebook Fellowship winners, highlighting their research areas and the support provided by Facebook to foster academic collaboration.