Nvidia designed the H100 graphics processor that became central to modern generative-AI computing.
Nvidia introduced the H100, based on its Hopper architecture, for demanding artificial-intelligence and high-performance-computing workloads. The processor uses specialized Tensor Cores and other features designed to accelerate matrix calculations used by neural networks. It became one of the most sought-after data-center accelerators during the rapid expansion of generative AI.
Nvidia was founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem. It first became widely known for graphics processing units used in computer games, but its CUDA software platform helped developers use Nvidia hardware for general-purpose parallel computing.
The company’s market value grew sharply as cloud providers and AI developers invested in accelerated computing. A common mix-up is treating GPUs as only gaming hardware: modern GPUs also power scientific simulations, data analytics, autonomous systems, and machine-learning training. The H100 is a data-center product, not the consumer graphics card found in most home gaming PCs.