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AI Optical Networking Market to Hit $154B by 2028

AI Optical Networking Market to Hit $154B by 2028
Runaway AI training demand is pushing data center fabrics past their limits, making optical networking the bottleneck to unlock GPU-scale performance and efficiency. Scale-up connects more GPUs within a box or across tightly coupled racks to form supernodes with ultra-low-latency fabrics. A new forecast from Goldman Sachs positions optical networking as the next mega-trend in AI infrastructure, with spend growing an order of magnitude as clusters densify. CPO—integrating optical engines with switch ASICs or accelerators—features prominently in the growth outlook. Expect a technology mix that also includes pluggable 800G/1.6T optics and emerging Linear Pluggable Optics (LPO) to reduce DSP power at short reaches.

Intel and Google Advance AI Infrastructure with Xeon 6, IPUs

Intel and Google Advance AI Infrastructure with Xeon 6, IPUs
Intel and Google expanded a multiyear partnership that doubles down on Xeon CPUs and custom infrastructure processing units to scale AI with better efficiency and predictability. Google committed to multiple generations of Intel Xeon for AI, inference, and general-purpose workloads across its global cloud. The latest Xeon 6 processors are already powering Google Cloud’s workload-optimized instances, including C4 and N4, to coordinate large-scale training, serve latency-sensitive inference, and run mainstream compute. In parallel, the companies will broaden co-development of custom ASIC-based IPUs that offload networking, storage, and security from host CPUs to improve utilization and deliver more stable performance at hyperscale.

SK Telecom, Arm and Rebellions Launch Sovereign AI Inference Platform

SK Telecom, Arm and Rebellions Launch Sovereign AI Inference Platform
A new alliance between SK Telecom (SKT), Arm, and Rebellions targets the fast-growing AI inference market with a server platform designed for sovereign AI and telecom-grade data centers. SKT will validate a new AI server that combines Arm’s AGI CPU—its first Arm-designed data center processor, based on Neoverse CSS V3—with Rebellions’ RebelCard inference accelerator in live AI data center environments. The partners will co-develop the full software stack, from firmware up, and test telco-specific models and large-scale workloads, including SKT’s proprietary foundation model, A.X K1. Industry focus is shifting from training to inference at scale, where energy, latency, and total cost of ownership (TCO) are decisive.

Deutsche Telekom telco cloud cuts 5G core energy by up to 65%

Deutsche Telekom telco cloud cuts 5G core energy by up to 65%
Deutsche Telekom’s early live results showing up to 65% energy savings in its 5G core spotlight a pragmatic path to cut opex and carbon as traffic surges and standalone 5G scales. Operators have wrung out much of the easy efficiency from hardware refreshes; the next gains come from software-driven, demand-aware control. DT is applying that logic to the core, shifting components to run only when needed rather than idling at full power. The results are enabled by DT’s “Horizontal Telco Cloud,” a unified, standards-based platform that replaces fragmented stacks with one common layer for core services. Initial live-network tests have been completed, with broader rollout planned and further detail expected at MWC Barcelona 2026.

Qualcomm hit by AI-driven smartphone memory crunch

Qualcomm hit by AI-driven smartphone memory crunch
An AI‑fueled land grab for advanced memory is squeezing supply for handsets, undercutting Qualcomm’s near‑term outlook even as end‑demand for premium Android devices improves. Memory suppliers are prioritizing high‑bandwidth memory (HBM) and DDR5 for AI accelerators and data center servers, diverting wafer capacity and capex away from mobile‑grade LPDDR5/5X and UFS storage. The result is a classic allocation cycle: supply chases the highest‑margin demand (HBM and enterprise SSDs), while downstream categories like smartphones and some edge devices face tighter availability and rising component costs. For Qualcomm, whose Snapdragon platforms anchor premium Android devices, the constraint limits upside volume and mix in the near term.

SpaceX xAI merger: beyond space data centers

SpaceX xAI merger: beyond space data centers
The merger creates a $1.25 trillion private giant that fuses launch, satellites, and AI, but the strategic logic goes beyond orbiting data centers. SpaceX brings rockets, Starship scale, and the world’s largest NGSO broadband network via Starlink. xAI brings models, AI R&D, and a brand in the hottest capital market category. Together, they present a single story to investors: own the stack from compute to constellation to connectivity, on and off Earth. Consolidation gives Musk freedom to reallocate cash flows and simplifies the roadshow pitch.

Nvidia OpenAI investment: Huang rejects $100B stall

Nvidia OpenAI investment: Huang rejects $100B stall
Nvidia’s CEO is publicly reaffirming confidence in OpenAI even as reports suggest the companies may narrow the scope of an ambitious, nonbinding plan announced last fall. During a visit to Taipei, Nvidia CEO Jensen Huang dismissed talk of friction with OpenAI and said Nvidia will participate in OpenAI’s next funding round. Recent reporting suggested Nvidia has emphasized the nonbinding nature of its plan to invest up to $100 billion and build roughly 10 GW of compute for OpenAI, and that both parties are re-examining scope and terms.

Nvidia China Sales Halt Exposes AI Market Split

Nvidia halts H20 AI chips for China amid security review
Nvidia’s CEO has warned that U.S. export controls have effectively halted the company’s China business, sharpening the stakes for AI leadership, supply chains, and enterprise buyers. He indicated the company is modeling China sales at effectively zero for the next two quarters under current rules, acknowledging that the revenue loss constrains reinvestment in R&D and manufacturing capacity. The message was blunt: a prolonged lockout weakens the U.S. AI stack abroad and cedes room to rivals at home and overseas. Huang pegged China’s accelerator market at roughly $50 billion today with potential to reach up to $200 billion by decade’s end.

Nvidia $57B revenue fuels AI infrastructure boom

Nvidia $57B revenue fuels AI infrastructure boom
Nvidia’s latest quarter signals that AI infrastructure spending is not cooling and is, in fact, broadening across clouds, sovereigns, and enterprises. Nvidia delivered $57 billion in revenue for the quarter, up more than 60% year over year, with GAAP net income reaching $32 billion; the data center segment accounted for roughly $51.2 billion, dwarfing gaming, pro visualization, and automotive combined. Management guided next-quarter sales to about $65 billion, exceeding consensus by several billion and underscoring that supply remains tight for cloud GPUs even as deployments ramp across hyperscalers, GPU clouds, national AI initiatives, and large enterprises.

SoftBank Sells Nvidia Stake to Fund AI Infrastructure Bets

SoftBank Sells Nvidia Stake to Fund AI Infrastructure Bets
SoftBank has exited Nvidia and is redirecting billions into AI platforms and infrastructure, signaling where it believes the next phase of value will concentrate. SoftBank sold its remaining 32.1 million Nvidia shares in October for approximately $5.83 billion, and also disclosed a separate $9.17 billion sale of T-Mobile US shares as part of a broader reallocation into artificial intelligence. The proceeds are earmarked for a significant expansion of SoftBank’s AI portfolio, including a major investment in OpenAI and potential participation in “Stargate,” a next-generation AI data center initiative co-developed by OpenAI and Oracle. Despite exiting Nvidia’s equity, SoftBank retains about 90% ownership of Arm.

Google AI chips: 4x TPU boost and Anthropic deal

Google AI chips: 4x TPU boost and Anthropic deal
Google has unveiled next‑generation TPU accelerators with up to a 4x performance boost and secured a multiyear Anthropic commitment reportedly worth billions, signaling a new phase in AI infrastructure competition. Google introduced new Tensor Processing Units that deliver roughly four times the performance of prior generations for training and inference of large models. Beyond speed, the design targets better performance-per-watt, a critical lever as AI energy costs surge. Anthropic has secured access to Google Cloud TPU capacity at massive scale, with reports citing availability up to one million TPU chips over the term of the agreement.

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.

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