Nvidia’s AI advantage is increasingly seen as extending beyond its graphics processing units (GPUs) into the wider systems needed to run enormous AI data centres efficiently. As rivals such as Amazon and Google develop their own chips, investors have questioned how defensible Nvidia’s GPU lead will be; the company’s latest earnings have instead drawn attention to its role in organising storage, networking, memory and computing at scale.

Nvidia’s forthcoming Vera Rubin architecture combines the Rubin GPU with components including the Vera CPU, inference accelerators, storage and networking racks. The Vera CPU is designed to coordinate data movement so GPUs and flash storage are not held back by bottlenecks; Nvidia says it has seen improvements of up to threefold in some operations. The article compares this with OpenAI’s Jalapeño chip, which seeks efficiency by keeping workloads within a connected system and reducing data movement altogether.