Nvidia’s H100 graphics processors became central to modern generative artificial intelligence.
The H100 is a data-center graphics processing unit, or GPU, based on Nvidia’s Hopper architecture. It was designed for demanding parallel workloads, including training and running large artificial-intelligence models. Its tensor-processing capabilities and high-speed memory make it suitable for the matrix calculations used in machine learning.
Nvidia was founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem. The company originally focused on graphics chips for personal computers and video games. Its CUDA software platform later helped developers use Nvidia GPUs for general-purpose parallel computing, creating an important advantage in AI infrastructure.
The H100 is not itself a generative-AI chatbot or model. It is hardware used by data centers that train and operate models. Nvidia’s strong position in AI accelerators helped drive a dramatic rise in its market value and placed it among the world’s richest companies by market capitalization.