artificial intelligence DeepMind Tackles Fusion Energy as AI Research Evolves March 2022 brings major AI updates, including DeepMind's breakthrough in controlling fusion plasma and new tools like PyTorch's TorchRec for recommender systems.
stylegan3 NVIDIA Fixes Glued Details in StyleGAN3 for Better Animation NVIDIA releases StyleGAN3, an updated generative adversarial network that eliminates the "sticker" effect by fixing aliasing issues in the generator. The new architecture ensures details stay attached to object surfaces rather than pixel coordinates, making it ideal for video.
microsoft Microsoft Build 2021 Highlights Azure AI and Low-Code Advances Microsoft's Build 2021 event focuses heavily on Azure cloud-native tools, a supported PyTorch Enterprise release, and new AI integrations for low-code developers.
ai Deep Learning Advances to Early Adopter Phase in 2021 AI Trends The August 2021 InfoQ trends report highlights deep learning's transition into the early adopter category and notes emerging challenges in edge deployment. The report also covers growing automation in machine learning pipelines and the steady evolution of commercial robotics platforms.
facebook ai Facebook AI Develops SEER, a Self-Supervised Vision Model That Classifies Billions of Unlabeled Images Facebook AI introduces SEER, a groundbreaking computer vision model that accurately classifies one billion random Instagram images without relying on human labels. This self-supervised system achieves an 84.4% accuracy rate by utilizing a new algorithmic pipeline.
nvidia NVIDIA and Harvard Build AI Toolkit to Enhance Genome Sequencing Accuracy Researchers from NVIDIA and Harvard University introduce AtacWorks, a deep learning toolkit that improves genome sequencing by filtering out noise from small cell samples. This PyTorch-based convolutional neural network delivers high-quality results faster than traditional methods.
facebook ai Facebook AI Unveils SEER, a Billion-Parameter Self-Supervised Vision Model Facebook AI introduces SEER, a massive self-supervised computer vision model that achieves superior results without relying on manually labeled image data.
ai Top 15 Machine Learning and AI Research Papers of 2020 Despite the global pandemic, 2020 produces incredible breakthroughs in artificial intelligence research, with GPT-3 leading the pack. This curated list highlights fifteen essential papers that shape the future of deep learning and machine learning.
aws AWS Unveils Custom AI Chips and Rapid ML Innovations at re:Invent AWS hosts its first dedicated Machine Learning keynote at re:Invent 2020, highlighting over 250 new features and introducing custom training chips like AWS Trainium. The company also announces faster distributed training capabilities for Amazon SageMaker.
artificial intelligence Leading AI Experts Share Predictions for Machine Learning in 2020 Top machine learning minds like Google's Jeff Dean and PyTorch creator Soumith Chintala forecast major developments in natural language models and a growing emphasis on ethics beyond mere accuracy.
nvidia Nvidia and Partners Release Open Source AI Framework for Medical Research Nvidia and King's College London launch Project MONAI, an open source framework designed to improve reproducibility in healthcare AI research. The alpha release integrates with PyTorch and focuses on tasks like 3D organ segmentation and brain MRI classification.
facebook Facebook Updates PyTorch 1.1 to Tackle Production Environments Facebook releases PyTorch 1.1 with a strong focus on production readiness, shifting the open-source deep learning framework beyond its research roots. The update brings enhanced distributed training, TensorBoard support, and new developer tools.
pytorch Major Tech Firms Unite to Support PyTorch 1.0 Release Facebook unveils PyTorch 1.0 with backing from cloud giants and hardware makers to streamline the path from AI research to production.
pytorch PyTorch 1.0 Aims to Bridge the Gap Between Research and Production The PyTorch Developer Conference 2018 highlights the release of PyTorch 1.0, which introduces the torch.jit module to streamline the transition of models from research to production environments.