Data Center

Reports indicate SK Group will reduce executive ranks by up to 30%, a move that would reshape decision-making across affiliates including SK Telecom (SKT). For SKT, which sits at the nexus of the group’s AI, cloud, and connectivity ambitions, executive trims would concentrate authority and compress approval chains at a sensitive time for 5G monetization and AI platform bets. Executive consolidation at a Tier-1 operator tends to reset priorities, procurement rhythms, and partner engagement models.
October’s job-cut announcements surged, with AI and cost control reshaping staffing plans across technology and adjacent sectors. Planned layoffs spiked to roughly 153,000 in October, up more than 180% from September and about 175% from a year ago, according to the latest Challenger job-cuts tally. Year-to-date announcements for 2025 have crossed 1.09 million, the highest October-through-period since the pandemic shock of 2020 and above comparable 2009 levels. The cuts reflect a pivot from growth-at-any-cost to profitability, with AI rebalancing roles and budgets across the stack. Across reasons given, cost reduction led by a wide margin, and AI adoption was the second-largest driver, underscoring both macro pressure and structural transformation.
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.
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 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.
AI buildouts have flipped a decade of flat U.S. electricity growth into a structural uptrend, with consumer price concerns rising in parallel. After years of steady demand, U.S. load is climbing as commercial and industrial users tap more power, and hyperscale data centers are now a central driver of the shift. Data centers are estimated to consume roughly 4% of U.S. electricity today—more than twice their share in 2018—and some credible scenarios place that figure in the high single digits to low teens by 2028, depending on the trajectory of AI training and inference footprints.
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.
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 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.
Ericsson, Nokia, and Fraunhofer HHI jointly demonstrated a proof‑of‑concept codec that delivers meaningfully higher compression than today’s widely deployed standards—H.264/AVC, H.265/HEVC, and H.266/VVC—without a notable rise in complexity. The partners emphasize energy efficiency and scalability, which are critical for battery‑powered devices, edge compute, and large streaming workloads. Their submission was positively received by the ITU‑T Video Coding Experts Group and ISO/IEC MPEG, the bodies that jointly steward the H.26x/MPEG lineage. The work is positioned as an on‑ramp to the next standardization phase, targeting readiness to support commercial deployment around 2029–2030, in step with 6G timelines.
Nokia delivered a stronger-than-expected third quarter, with comparable operating profit reaching €435 million against consensus of about €342 million. Group net sales rose 12% to €4.83 billion, above forecasts, driven by Optical Networks and cloud-related demand tied to AI data centers. The stock jumped double digits intraday and added billions in market value, reflecting newfound confidence after a challenging first half. The recovery now is concentrated in network infrastructure rather than mobile RAN, underscoring where customers are actually spending to handle AI-era traffic patterns. Nokia nudged its full-year operating profit outlook to €1.7–2.2 billion, with a reporting change related to scaling down passive venture investments partly in play.
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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