NVIDIA Becomes Central to the AI Infrastructure Boom

By late 2024, NVIDIA’s role in AI had expanded far beyond selling individual GPUs. Major cloud providers and AI laboratories were deploying large H100, H200, and early Blackwell-based clusters connected with NVIDIA networking and software.

CUDA remained a major competitive advantage because deep-learning frameworks and optimized libraries were already built around it. NCCL handled multi-GPU communication, TensorRT optimized inference, and NVLink/NVSwitch connected accelerators at much higher bandwidth than ordinary server networking.

This software-and-interconnect ecosystem made switching hardware harder than comparing one chip’s FLOPS figure. AI infrastructure had become a full-stack problem involving compilers, kernels, networking, memory, cluster scheduling, power, and cooling.