The rapid adoption of agentic AI is reshaping the requirements for computing infrastructure, as AI systems increasingly perform complex tasks that require continuous processing, high-speed data movement and efficient inference.

NVIDIA is positioning its NVLink Fusion platform as a key technology for this next phase of AI infrastructure. The platform enables hyperscalers and AI-native companies to integrate custom processors, including XPUs and CPUs, with NVIDIA’s rack-scale architecture. This approach is designed to help organisations build more flexible and scalable AI factories while reducing the complexity involved in developing specialised infrastructure.

The shift is particularly significant as AI moves beyond model training towards large-scale inference and agentic workloads. AI agents require infrastructure capable of handling sustained workloads, rapid communication between computing components and increasingly demanding memory requirements.

NVIDIA has also expanded NVLink Fusion with NVHBM, a high-bandwidth memory technology intended to improve memory performance and efficiency for custom AI processors. The company says the technology can provide up to 30% higher memory bandwidth and reduce HBM power consumption by up to 15% compared with standard HBM4E.

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The growing ecosystem around NVLink Fusion includes companies such as MediaTek, Amazon’s Annapurna Labs and d-Matrix, reflecting increasing industry interest in semi-custom AI infrastructure.

As agentic AI adoption accelerates, the evolution of compute, networking, memory and rack-scale systems is expected to become increasingly important for delivering AI services at scale.

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