Releases

Hugging Face released an open-source PyTorch implementation and pretrained checkpoints for BERT, the project that evolved into the Transformers library.

NVIDIA launched RAPIDS as an open-source GPU-accelerated data science and machine-learning suite.

Microsoft releases the first public preview of ML.NET, bringing cross-platform machine learning to .NET developers.

Microsoft researchers introduce Fairlearn to assess and mitigate unfairness in machine-learning systems.

OpenAI released code for training reinforcement-learning agents from human feedback.

OpenAI released Baselines, open-source high-quality implementations of reinforcement-learning algorithms.

Facebook released the Caffe2 deep-learning framework for scalable cross-platform training and deployment.

Facebook AI Research released FAISS for efficient similarity search and clustering of dense vectors.

Facebook AI Research released PyTorch, a Python-first tensor and dynamic neural-network framework.

Facebook AI Research released fastText, a library for efficient text classification and word representations.

Scale launched an API that let developers submit human-powered data tasks with one line of code, establishing the foundation of its AI data business.

Amazon open-sourced its Deep Scalable Sparse Tensor Network Engine for recommendation workloads.

Microsoft releases its Computational Network Toolkit under an open-source license for deep neural-network training.

Amazon opened Alexa to developers through the Alexa Skills Kit and Alexa Voice Service.

NVIDIA released the first version of its GPU-accelerated deep neural network primitives library.

NVIDIA introduced CUDA and a C programming environment, opening its GPUs to general-purpose parallel computing.