Nvidia’s H100 processor became closely associated with training large artificial-intelligence models.
Jensen Huang, Chris Malachowsky, and Curtis Priem founded Nvidia in 1993. The company initially focused on graphics processors for personal computers and video games. Its graphics processing units became important because they can perform many calculations in parallel.
Nvidia’s CUDA software platform helped developers use its GPUs for general-purpose computing, not just graphics. That foundation made Nvidia hardware especially useful for machine learning, where huge numbers of matrix operations are performed.
The H100 is a data-center GPU based on Nvidia’s Hopper architecture. It is not a consumer graphics card and is not itself an AI model. Nvidia’s market capitalization surged as cloud providers and AI developers invested in accelerated computing infrastructure.