NVIDIA Invests $40 Billion in AI Infrastructure - 조선일보
10/10NVIDIA announced a $40 billion investment in AI infrastructure on May 11, 2026, showcasing its commitment to advancing AI technologies and expanding its AI ecosystem globally.

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NVIDIA announced a $40 billion investment in AI infrastructure on May 11, 2026, showcasing its commitment to advancing AI technologies and expanding its AI ecosystem globally.
On May 11, 2026, Nvidia unveiled a $40 billion AI investment plan aimed not only at hardware but also expanding into AI applications and services, signaling a broad strategic push beyond its core chip business.
NVIDIA announced a $2.1 billion deal with data center provider IREN on May 11, 2026, designed to redefine AI data center economics by enabling large-scale AI infrastructure deployment.
On May 11, 2026, NVIDIA and IREN partnered to develop a 5-gigawatt AI infrastructure project supporting large-scale AI workloads, enhancing data center capabilities to support industry growth.
On October 28, 2025, NVIDIA unveiled NVQLink technology connecting quantum processing units (QPUs) to GPUs, involving 17 builders and 9 U.S. labs, advancing GPU-QPU integration for improved computational performance.
On May 11, 2026, Sakana AI and NVIDIA introduced TwELL, leveraging CUDA kernels to achieve a 20.5% speedup in inference and a 21.9% speedup in training large language models, enhancing AI model performance.
Nvidia reported record revenue in Q4 FY26 on May 11, 2026, driven significantly by data center growth, and provided optimistic financial guidance for Q1 FY27 reflecting strong market demand.
A May 11, 2026 article highlights NVIDIA's collaboration with IREN on AI infrastructure deployment at scale, emphasizing NVIDIA's expanding strategic role in enterprise data center technologies.
NVIDIA's stock surged by 8.4% on May 11, 2026, fueled by investor optimism from AI infrastructure alliances and ahead of its quarterly earnings announcement.
On May 11, 2026, NVIDIA and ServiceNow extended AI governance capabilities from desktops to data centers, enhancing enterprise AI deployment management and oversight at scale.