NVIDIA Expands AI Infrastructure with New Digital Twin and Agent Deals

Yahoo Finance ·

On October 28, 2026, NVIDIA announced expanded partnerships to accelerate global artificial intelligence infrastructure and agentic applications across various sectors. NVIDIA and Oracle plan to scale multi-gigawatt AI cloud superclusters using NVIDIA Vera Rubin GPUs and Vera CPUs for advanced training and inference workloads. Meanwhile, Schneider Electric and AVEVA reported successful pilots of a digital twin built on the NVIDIA Omniverse DSX Blueprint at the SINES Data Campus, and NVIDIA deepened its collaboration with Meta to support high-performance Muse AI agents. These alliances align with NVIDIA's broader transition from selling standalone chips to delivering comprehensive full-stack AI factory platforms. However, analysts note that export controls, hyperscaler custom chips, and component costs remain key risks that could impact future high-margin data center revenue as competitors like AMD advance.

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NVIDIA announced expanded large-scale AI infrastructure and digital twin partnerships with Oracle, Meta, and Schneider Electric. The introduction of Vera Rubin GPUs is expected to increase revenue opportunities per gigawatt from about $18 billion for Hopper to approximately $40 billion. Investors must closely examine profitability improvements from the full-stack AI factory transition alongside regulatory and competitive risks.

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NVIDIA's recent collaborations demonstrate the evolution of its business model from selling individual chips to providing full-stack AI factory platforms. In particular, the introduction of the Vera Rubin system significantly increases revenue opportunities per gigawatt, enhancing earnings growth visibility.

The bullish scenario assumes accelerated infrastructure investment by cloud and enterprise customers, maintaining high-margin data center revenues, while the bearish scenario involves big tech companies developing custom chips (ASICs) and export control risks putting pressure on margins. Future attention should be paid to large cloud order backlog trends and competitor movements.

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