Nvidia CEO Jensen Huang & Dell CEO Michael Dell on Agentic AI, Memory Demand and China

2026-05-18 · Source: Bloomberg Tech · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Cloud Computing & IT Infrastructure · Depth: Intermediate, long

Summary

Dell CEO Michael Dell and Nvidia CEO Jensen Huang discussed the rapid growth and future of AI at Dell World in Las Vegas, highlighting that supply chain constraints, particularly memory and advanced node semiconductors, remain the biggest bottleneck despite surging global demand, including "incredible" demand from China. They noted a shift from AI testing to production, with companies like Eli Lilly and Samsung deploying thousands of GPUs for on-premise agentic AI. Nvidia is launching the Grace Blackwell and Vera CPU, designed for agentic AI, which runs on CPUs and uses a new Dell AI Data Platform for long-term memory. Both executives anticipate a decade-long build-out for AI, moving from digital to physical agents, and expect the supply chain to quadruple annually to meet demand.

Key takeaway

For CTOs and AI Architects evaluating enterprise AI deployments, recognize that on-premise agentic AI is moving into production, demanding significant CPU and GPU resources. Your strategy should prioritize securing supply chain partnerships for memory and advanced semiconductors, as demand will outstrip supply for at least a decade, and plan for distributed intelligence across cloud, on-prem, and edge devices.

Key insights

Agentic AI is shifting from cloud-centric testing to on-premise production, driving demand for specialized hardware and integrated solutions.

Principles

• Intelligence must be produced at the point of context.
• AI agents will vastly outnumber humans, using tools constantly.
• Supply chain vision must be conveyed upstream and downstream.

Method

Nvidia and Dell are integrating GPU brains (Grace Blackwell), high-performance CPUs (Vera CPU), and a new Dell AI Data Platform for long-term memory, all networked with Nvidia technology, to create agentic AI solutions.

In practice

• Deploy AI agents on-premise for secure, proprietary data.
• Utilize agentic AI for 10x-100x workflow improvements.
• Consider hybrid AI models running on powerful PCs.

Topics

• Agentic AI
• On-Prem AI
• AI Supply Chain
• Memory Demand
• China AI Market

Best for: CTO, VP of Engineering/Data, AI Architect, Executive, Director of AI/ML, Investor

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Editorial summary, takeaway, and curation by AIssential. Original article published by Bloomberg Tech.