Releases

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.

NVIDIA introduced the Volta architecture and V100 GPU, including Tensor Cores built for deep learning.

The Pascal-based Tesla P100 accelerator debuted alongside DGX-1 for deep learning and HPC.

NVIDIA unveiled DGX-1, its first integrated deep-learning supercomputer.

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

AlexNet, trained on NVIDIA GPUs, won the ImageNet competition and helped catalyze modern deep learning adoption.

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