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NVIDIA

NVIDIA

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COMPUTEX 2026 | NVIDIA Keynote | Extreme Co-Design: Building the AI Factory

10.07.2026 9,522 views
Published: 10.07.2026 Category: Technology and AI Views: 9,522

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Extreme Co-Design: Building the AI Factory | Kevin Deierling, SVP Networking, NVIDIA | Computex 2026 In this keynote from the Computex Forum in Taipei, NVIDIA SVP of Networking Kevin Deierling breaks down what it actually takes to build an AI factory — and why extreme co-design across the entire data center stack is the only way to deliver the tokens the agentic AI era demands. Deierling opens with three converging transformations reshaping computing: the decades-long shift to accelerated computing, the explosion of generative AI, and the rise of agentic reasoning. Together, they're forcing a complete rearchitecture of the data center — from a cost center into a token revenue generator. Using Jensen Huang's "5-layer cake" framework, he walks through how NVIDIA co-designs across every layer: Energy — AI training workloads create dramatic power spikes. NVIDIA's DSX software smooths energy demand, enabling 40% more GPUs per gigawatt — and 40% more token revenue. Chips — NVIDIA's 7 co-designed chips work as one system: Rubin GPUs and Vera CPUs connected via cache-coherent links, scaling up with NVLink and out with Spectrum-X Ethernet through BlueField-4 and ConnectX SuperNICs. This extreme co-design delivers 10x more tokens at 1/10th the cost. Infrastructure — 72 GPUs unified into one giant computer via NVLink 72, running liquid-cooled and DC-powered in the same rack form factor. And with Spectrum CPO (co-packaged optics), NVIDIA brings the optics next to the ASIC to eliminate signal degradation — saving tens of megawatts across an AI factory. Networking scales from 800Gbps to 1600Gbps. Agents — Agents are AI eating its own tail: instead of waiting on humans, AIs prompt AIs, closing the loop at machine speed. The Vera CPU is built specifically for agentic tools — planning, writing programs, summarizing results. Agents need memory: KV cache for short-term (CMX) and files, objects, and vector databases for long-term (STX). This new class of AI storage delivers 5x faster token throughput and 5x better efficiency. Models & Applications — 30x performance improvement on DeepSeek…

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