Releases

NVIDIA made ACE generative AI microservices generally available for cloud-based digital-human applications.

NVIDIA entered a definitive agreement to acquire AI workload orchestration provider Run:ai.

NVIDIA and AWS announced broader Blackwell infrastructure and generative AI software integrations.

NVIDIA and Microsoft expanded integrations spanning Azure AI, NIM, Omniverse and enterprise generative AI.

NVIDIA introduced the Blackwell GPU architecture, B100, B200 and GB200 Grace Blackwell Superchip for generative AI.

NVIDIA launched NIM, containerized optimized inference microservices for generative AI deployment.

NVIDIA announced DGX GB200 and a Blackwell-powered DGX SuperPOD reference architecture.

NVIDIA launched Earth-2 cloud APIs and AI models for high-resolution weather and climate simulation.

NVIDIA announced a general-purpose foundation model initiative for humanoid robots.

NVIDIA introduced production generative AI microservices for interactive digital humans.

NVIDIA market capitalisation at end of calendar year 2023, up 240% year-over-year, driven by explosive demand for AI training GPUs following the ChatGPT-led generative AI boom.

NVIDIA introduced H200, adding HBM3e memory to the Hopper platform for generative AI and HPC.

NVIDIA publicly released its open-source TensorRT-LLM library for optimized large-model inference.

NVIDIA expanded Omniverse with generative AI tools and deeper OpenUSD workflows for industrial digitalization.

NVIDIA introduced the L40S data-center GPU for generative AI, inference, training and graphics workloads.

NVIDIA introduced AI Workbench for creating and moving generative AI projects across local, data-center and cloud systems.

NVIDIA announced DGX GH200, connecting 256 Grace Hopper Superchips into a large shared-memory AI system.

NVIDIA launched DGX Cloud, providing browser-based access to managed AI supercomputing infrastructure.

NVIDIA announced broad H100 availability through leading cloud and server providers as generative AI demand surged.

NVIDIA introduced cloud services for enterprises to build custom language and visual generative AI models.

NVIDIA market capitalisation at end of calendar year 2022, down 51% from the prior year amid a broader semiconductor and tech sector downturn.

NVIDIA introduced BioNeMo, a generative AI service for chemistry and biomolecular research.

NVIDIA expanded TAO Toolkit integration for fine-tuning and optimizing pretrained production AI models.

NVIDIA made its end-to-end GPU-accelerated recommender AI framework generally available.

NVIDIA made its multilingual speech AI SDK generally available.

NVIDIA announced its fourth-generation DGX system powered by eight H100 GPUs.

NVIDIA launched Jetson AGX Orin for next-generation robotics and autonomous machines.

NVIDIA announced the Grace Hopper Superchip, pairing a Grace CPU with a Hopper GPU using coherent memory.

NVIDIA announced the Hopper architecture and H100 GPU with a Transformer Engine for large AI models.

NVIDIA made its AI Enterprise software suite generally available.

NVIDIA made Fleet Command generally available for centrally deploying and managing edge AI applications.

NVIDIA launched a hosted enterprise program offering immediate access to its end-to-end AI infrastructure and software stack.

NVIDIA introduced Morpheus for real-time AI-assisted threat detection using GPUs and BlueField DPUs.

NVIDIA introduced Base Command to provision, schedule and operate shared DGX SuperPOD AI infrastructure.

NVIDIA announced an enterprise software suite for virtualized AI workloads on VMware vSphere.

NVIDIA opened the Omniverse collaboration and simulation platform to beta users.

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

NVIDIA doubled A100 accelerator memory to 80GB using HBM2e.

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

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.

NVIDIA expanded EGX with certified servers, software and ecosystem support for AI, IoT and 5G at the edge.

NVIDIA introduced EGX to bring real-time AI computing to edge and industrial environments.

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

NVIDIA launched the T4 GPU and TensorRT 5 as a data-center inference platform.

NVIDIA introduced the Jetson AGX Xavier embedded AI computer for autonomous machines.

NVIDIA introduced Clara as a medical imaging and healthcare AI computing platform.

NVIDIA introduced DGX-2 with 16 V100 GPUs connected by NVSwitch for large-scale AI training.

NVIDIA launched TITAN V, bringing Volta Tensor Core AI acceleration to desktop systems.

NVIDIA introduced its GPU Cloud catalog, later branded NGC, for optimized deep-learning containers and software.