Nvidia

OpenAI–AWS $38B AI Compute Deal

OpenAI–AWS $38B AI Compute Deal
OpenAI has signed a multi‑year, $38 billion capacity agreement with Amazon Web Services (AWS) to run and scale its core AI workloads on NVIDIA‑based infrastructure, signaling a decisive shift toward a multi‑cloud strategy and intensifying the hyperscaler battle for frontier AI. The agreement makes OpenAI a direct AWS customer for large‑scale compute, starting immediately on existing AWS data centers and expanding as new infrastructure comes online. AWS and OpenAI target the bulk of new capacity to be deployed by the end of 2026, with headroom to extend into 2027 and beyond.

SK Telecom expands AIDC for AI infrastructure in Asia

SK Telecom expands AIDC for AI infrastructure in Asia
At SK AI Summit 2025, CEO Jung Jaihun outlined plans to expand the Ulsan artificial intelligence data center (AIDC) to 1GW-class capacity, stand up a nationwide trio of hubs (Gasan in the Seoul metro, Ulsan in the south, and a new southwest site), and take the model into Southeast Asia starting with Vietnam. The operator is also deepening technology collaborations with Amazon Web Services (AWS) on Edge AI and with NVIDIA on AI-RAN and a Manufacturing AI Cloud; it intends to buy more than 2,000 NVIDIA RTX PRO 6000 Blackwell GPUs and scale Korea’s largest GPU cluster, Haein, as core compute for industrial AI workloads.

CrowdStrike & NVIDIA: Open AI Agents at the Edge

CrowdStrike & NVIDIA: Open AI Agents at the Edge
CrowdStrike and NVIDIA are aligning open models, edge inference, and agentic tooling to push real-time, autonomous cyber defense into data centers, clouds, and MEC sites where telecom and enterprise workloads actually live. By pairing CrowdStrike’s Charlotte AI AgentWorks with NVIDIA’s Nemotron open models, NeMo Data Designer, NeMo Agent Toolkit, and NIM microservices, the partners aim to shrink detection-to-response windows from minutes to milliseconds, and to do so where latency is lowest—at the edge. The companies expanded their collaboration to deliver always-on, continuously learning AI agents that defend cloud, data center, and edge environments using open and enterprise-grade NVIDIA AI components integrated with CrowdStrike’s Agentic Security Platform.

Hyundai-NVIDIA Blackwell AI Factory for Mobility and Manufacturing

Hyundai-NVIDIA Blackwell AI Factory for Mobility and Manufacturing
Hyundai Motor Group and NVIDIA are expanding their partnership to build a large-scale “physical AI” stack that fuses autonomous driving, smart factories, and robotics with national-scale infrastructure in Korea. The companies plan to stand up an AI factory built on 50,000 NVIDIA Blackwell GPUs to unify model training, validation, and deployment across vehicles and plants. Backed by an approximately $3 billion public–private investment, the effort includes a Physical AI Application Center, an NVIDIA AI Technology Center, and regional data centers developed in concert with Korea’s Ministry of Science and ICT.

Samsung AI Factory Powered by NVIDIA GPUs

Samsung AI Factory Powered by NVIDIA GPUs
Samsung and NVIDIA are scaling a 25-year alliance into an AI-driven manufacturing platform that fuses memory, foundry, robotics and networks on a backbone of accelerated computing. Samsung plans to deploy more than 50,000 NVIDIA GPUs to infuse AI across the company’s manufacturing lifecycle—from chip design and lithography to equipment operations, logistics and quality control. The “AI factory” is designed as a unified, data-rich fabric where models continuously analyze and optimize processes in real time, shrinking development cycles and improving yield and uptime. The scope goes beyond semiconductors to include mobile devices and robotics, signaling a company-wide digital transformation anchored in accelerated computing.

NVIDIA and Nokia Launch AI-RAN Platform for 6G

NVIDIA and Nokia Launch AI-RAN Platform for 6G
NVIDIA and Nokia unveiled a strategic partnership to deliver commercial AI-RAN products built on NVIDIA’s Aerial RAN Computer Pro (ARC-Pro) platform and Nokia’s RAN software portfolio, with NVIDIA committing a $1 billion equity investment in Nokia at approximately $6.01 per share, subject to customary closing conditions. The companies are targeting an AI-native RAN that runs both radio workloads and AI inference on a software-defined, accelerated platform, with a cumulative AI-RAN market opportunity that Omdia estimates will exceed $200 billion by 2030. ARC-Pro is positioned as a 6G-ready accelerated computing platform that couples connectivity, compute, and sensing, enabling upgrades from 5G-Advanced to 6G largely via software.

SoftBank and NVIDIA AI-RAN: 16-Layer MU-MIMO on GPUs

SoftBank AI-RAN Realizes - Software-only Massive MIMO on GPU
SoftBank and NVIDIA have validated a fully software-defined, GPU-accelerated AI-RAN that delivers 16-layer massive MU-MIMO outdoors—an inflection point for vRAN performance, Open RAN scalability, and AI-native RAN design. SoftBank’s AI-RAN product, AITRAS, executed the entire 5G physical layer on NVIDIA GPUs at the Distributed Unit and demonstrated stable 16-layer multi-user MIMO downlink in an outdoor trial at NVIDIA’s Santa Clara campus. The system connected to O-RAN-compliant radios via Split 7.2x and achieved roughly three times the spectral efficiency and throughput of a conventional 4-layer setup while maintaining per-user rates under high load. The field results show that software-only massive MIMO on GPUs can meet macro-radio conditions without bespoke silicon.

Qualcomm AI200/AI250 AI Chips for Data Center Inference

Qualcomm AI200/AI250 AI Chips for Data Center Inference
Qualcomm is moving from mobile NPUs into rack-scale AI infrastructure, positioning its AI200 (2026) and AI250 (2027) to challenge Nvidia/AMD on the economics of large-scale inference. The company is translating its Hexagon neural processing unit heritage—refined across phones and PCs—into data center accelerators tuned for inferencing, not training. AI200 and AI250 will ship in liquid-cooled, rack-scale configurations designed to operate as a single logical system. Qualcomm is leaning into that constraint with a redesigned memory subsystem and high-capacity cards supporting up to 768 GB of onboard memory—positioning that as a differentiator versus current GPU offerings.

SoftBank’s $30B OpenAI Investment Signals AI IPO Push

Databricks Integrates OpenAI GPT-5 in $100M AI Bet
SoftBank has reportedly approved the final $22.5 billion tranche of a planned $30 billion commitment to OpenAI, tied to the AI firm’s shift to a conventional for‑profit structure and a path to IPO. The investment completes a massive $41 billion financing round for OpenAI that began in April, making it one of the largest private capital raises in tech history. This funding and restructuring signal faster enterprise AI adoption, heavier infrastructure demand, and new platform dynamics that will ripple across networks, cloud, and edge. OpenAI is pushing deeper into enterprise tools, security features, and domain‑specific assistants.

Google Cloud G4 VMs with NVIDIA Blackwell GPUs

Google Cloud G4 VMs with NVIDIA Blackwell GPUs
The G4 family is built on NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs and targets high-throughput inference, visual computing, and simulation. Each VM can be configured with 1, 2, 4, or 8 GPUs, delivering up to 768 GB of GDDR7 memory in total. Fifth-generation Tensor Cores introduce FP4 precision to drive efficient multimodal and LLM inference, while fourth-generation RT Cores double real-time ray-tracing performance over the prior generation for photorealistic rendering. Google cites up to 9x throughput over G2 instances, positioning G4 as a universal GPU platform spanning AI inference, content creation, CAD/CAE acceleration, and robotics simulation.

Netflix Goes All-In on Generative AI

Netflix Goes All-In on Generative AI
Netflix is expanding generative AI across recommendations, ads, and production workflows, signaling how big media will operationalize AI at scale without replacing human creativity. The company highlighted recent use in final footage, de-aging in a new film, and pre-visualization for set and wardrobe design. This is not about automating storytelling; it is about compressing timelines, lowering iteration costs, and enabling more variants for testing and localization. Expect AI to touch asset creation, trailer and thumbnail generation, dubbing and subtitling, quality control, and promotional creative — all tied to measurable uplift in engagement and ad yield.

Arm and Meta Boost AI Efficiency with Neoverse

Arm and Meta Boost AI Efficiency with Neoverse
Arm and Meta have inked a multi-year partnership to scale AI efficiency from hyperscale data centers to on-device inference, aligning Arm’s performance-per-watt strengths with Meta’s AI software and infrastructure stack. Meta plans to run its ranking and recommendation workloads on Arm Neoverse-based data center platforms as part of an ongoing infrastructure expansion. The companies are co-optimizing AI software components—spanning compilers, libraries, and frameworks like PyTorch, FBGEMM, vLLM, and the ExecuTorch runtime—so models can execute more efficiently on Arm CPUs in the cloud and on Arm-based devices at the edge. The work includes leveraging Arm’s KleidiAI optimizations to improve inference throughput and energy efficiency, with code contributions flowing back to open source.

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