Releases

AWS introduced pretrained models and solution templates to accelerate machine-learning deployment.

NVIDIA introduced a deskside AI system with four A100 GPUs for workgroups.

NVIDIA doubled A100 accelerator memory to 80GB using HBM2e.

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.

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.

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

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.

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

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

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.