Releases

NVIDIA doubled A100 accelerator memory to 80GB using HBM2e.

Facebook AI released M2M-100, a multilingual machine-translation model translating directly between 100 languages.

Baidu opened Apollo Go autonomous ride-hailing to public users in Beijing.

NVIDIA introduced Maxine, a cloud-native suite of GPU-accelerated AI video-conferencing and streaming software.

Palantir began trading on the New York Stock Exchange through a direct listing, marking its transition to a public company.

Scale released the core Nucleus workspace for dataset visualization, search, curation, collaboration, and model-error analysis.

Scale launched Nucleus as a dataset-management and model-debugging workspace for visualizing, curating, searching, and collaborating on machine-learning data.

Scale introduced a self-serve, pay-as-you-go product for receiving production-quality labels and instruction feedback in as little as one hour.

Microsoft spins Xiaoice into an independent company while retaining an investment interest.

Scale launched a mapping product for computer-vision and autonomous path-planning workflows.

Hugging Face began its hosted inference platform with a serverless API for models on the Hub, later expanding into dedicated endpoints and provider routing.

Hugging Face introduced a hosted API for running models from the Hub without managing serving infrastructure.

Databricks acquired open-source visualization company Redash to expand SQL analytics and collaboration.

Facebook AI introduced wav2vec 2.0 for self-supervised speech learning with limited labeled data.

OpenAI launched a general-purpose API for accessing its language models.

Microsoft Research introduces DeBERTa, improving Transformer language models with disentangled attention and enhanced mask decoding.

OpenAI published GPT-3, demonstrating few-shot learning at 175 billion parameters.

Hugging Face launched hosted dataset repositories alongside its Datasets library, creating a shared catalog for reusable machine-learning data.

Hugging Face released a unified open-source library and catalog for loading, processing, streaming, and sharing datasets.

NVIDIA began shipping DGX A100, an integrated 5-petaflop AI system with eight A100 GPUs.

NVIDIA launched the A100 Tensor Core GPU, its first Ampere data-center accelerator for training and inference.

Hugging Face made model repositories a central Hub product for versioning, documenting, discovering, and reusing pretrained models.

Hugging Face expanded from an NLP library into a Git-based collaboration platform for sharing models and machine-learning artifacts.

OpenAI released Jukebox, a neural network that generated music including rudimentary singing as raw audio.

AWS and Facebook jointly released TorchServe, an open-source model-serving library for PyTorch.

Hugging Face introduced its high-performance Rust-backed Tokenizers library for production-scale text preprocessing.

Microsoft open-sources DeepSpeed with the ZeRO optimizer to reduce the compute and memory cost of large-model training.

Oracle launched a managed collaborative environment for building, training and deploying machine-learning models.

Microsoft introduces Turing-NLG, a 17-billion-parameter generative language model and, at the time, the largest published language model.

Databricks articulated the lakehouse architecture, combining data-lake openness with data-warehouse management and performance.

Foundry ML capabilities became available for operational machine learning.

Model Studio became available for developing and operationalizing machine-learning models.

Foundry added managed coding environments for data science and software work.

Baidu released its open NLP development library for PaddlePaddle.

CoreWeave established a managed, multi-tenant Kubernetes cloud running directly on bare metal for GPU-accelerated machine-learning and inference workloads.

Scale began supporting U.S. defense and national-security AI programs, extending its data infrastructure into government missions.

Hugging Face raised $15 million in a Series A led by Lux Capital to expand its open-source natural-language-processing platform.

AWS launched automated model building with full visibility into generated models and notebooks.

AWS launched a web-based integrated development environment for machine learning.

AWS introduced managed human-review workflows for machine-learning predictions.

AWS introduced an intelligent enterprise-search service using machine learning and natural-language queries.

AWS introduced ML-powered code review and performance recommendations.

AWS made Inferentia-powered EC2 instances generally available for machine-learning inference.

AWS introduced a generative-AI learning service and musical keyboard.

CoreWeave launched its specialized cloud business around on-demand NVIDIA GPU infrastructure for compute-intensive workloads.

After the cryptocurrency downturn, the company redirected its GPU fleet toward accelerated cloud workloads and changed its name to CoreWeave, Inc.

OpenAI completed the staged GPT-2 release with the 1.5-billion-parameter model and accompanying research.

Microsoft organizes Project Turing to develop large language models shared across Bing, Office, Dynamics and Azure.

Google researchers publish the T5 approach and Colossal Clean Crawled Corpus, framing diverse NLP tasks in one text-to-text format.

Databricks raised $400 million in Series F financing at a $6.2 billion valuation.