Jensen Huang Just Crowned the Next $1 Trillion AI Company — and It Doesn't Make a Single GPU

2026-06-04 · Source: Towards AI - Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure · Depth: Intermediate, quick

Summary

NVIDIA CEO Jensen Huang recently declared Marvell "the next trillion-dollar company" at Computex in Taipei on June 2, causing Marvell's stock to jump approximately 33% in a single day. This endorsement is significant because Marvell does not produce GPUs or frontier AI models, yet Huang deemed it "essential." The article explains that Huang's logic centers on the critical role of connectivity in disaggregated, distributed computing problems within the AI stack. As AI workloads, particularly LLMs and agents, become more distributed across data centers, the infrastructure for data flow and inter-component communication is emerging as a key bottleneck, making companies like Marvell, which specialize in this connectivity, indispensable for the next phase of AI development.

Key takeaway

For AI architects and engineers designing scalable infrastructure for LLMs and agents, recognize that network connectivity is a critical, often overlooked, component. Your focus should extend beyond raw compute power to optimizing the data flow and communication fabric within your data centers. Prioritizing robust, high-speed interconnects will be crucial for preventing bottlenecks and ensuring efficient, scalable AI deployments, impacting overall system performance and cost-effectiveness.

Key insights

Connectivity is the emerging bottleneck and essential component in disaggregated, distributed AI computing infrastructure.

Principles

• Distributed computing requires robust connectivity.
• AI infrastructure extends beyond GPUs and models.

Topics

• AI Infrastructure
• Network Connectivity
• Data Center Architecture
• Marvell
• Jensen Huang
• Distributed Computing

Best for: Investor, CTO, VP of Engineering/Data, AI Engineer, Machine Learning Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Towards AI - Medium.