Digital Infrastructure Monthly Insights

Bell Canada will start building a large-scale AI data centre near Regina, Saskatchewan this spring, in partnership with the Saskatchewan government and George Gordon First Nation, with a reported ~$1.7 billion investment and positioning as the largest AI facility in Canada.

BCE intends to build an artificial-intelligence data centre outside Regina, Saskatchewan, expanding its AI infrastructure as part of efforts to diversify revenue streams.

At GTC, NVIDIA detailed local agentic AI on RTX PCs and the DGX Spark desktop supercomputer, releasing open Nemotron 3 models (Nano 4B and Super 120B), optimizations for Qwen 3.5 and Mistral Small 4, an open-source NemoClaw stack for OpenClaw, and easier fine-tuning via Unsloth Studio; models run locally with Ollama, LM Studio, and llama.cpp on RTX GPUs with quantized inference, with DGX Spark’s 128GB unified memory supporting >120B-parameter models.

SoftBank detailed an AI-RAN strategy centered on its AITRAS Orchestrator (with the open-sourced Dynamic Scoring Framework), ran a joint PoC with Ericsson to optimize low-latency, high-reliability connectivity for robots, is deploying AITRAS in edge data centers with Mitsubishi Heavy Industries for secure industrial AI inference, and joined the Linux Foundation’s OCUDU initiative while aligning with vendors like Ericsson and Nokia to promote an open, distributed AI ecosystem.

Delta Electronics presented power, cooling, and microgrid offerings at NVIDIA GTC, emphasizing support for NVIDIA’s proposed 800 VDC power architecture for AI factories.

Nvidia announced the BlueField-4 STX architecture targeted at next-generation AI storage, with leadership highlighting a need to rethink storage systems for the agentic AI era.

Supermicro highlights its Super AI Station within a broad GPU-accelerated systems portfolio (1U–10U GPU servers, twin and blade architectures, and edge systems), featuring options such as NVIDIA Grace CPU Superchip-based storage, NVMe E3.S PCIe Gen5, liquid cooling, and high-speed Ethernet/InfiniBand networking to support AI training and inference on-premises.

Marvell and Lumentum plan to demonstrate optical circuit switching (OCS) for data center AI clusters, targeting higher bandwidth and lower latency interconnects versus purely electrical Ethernet fabrics. The demo underscores integrating OCS into AI scale-up infrastructure to improve fabric efficiency and power utilization.

Intel is presenting its Xeon 6 CPU family as the compute foundation for AI-enabled telecom infrastructure, targeting network workloads and AI inference across telco edge and core environments on a global basis.

AMD highlights the role of CPUs for agentic AI workloads in AI data centers and signals expanded AI efforts for telco networks, referenced at MWC2026.

Foxconn indicates sustained high capex by global cloud service providers is making AI servers and data center infrastructure the ICT supply chain’s main growth engine, and forecasts an 80:20 market mix between GPU-based and ASIC-based AI servers.

Nscale announced a collaboration with NVIDIA and Microsoft to build a new AI data hub at the Monarch Compute Campus in Mason County, United States, using the NVIDIA Vera Rubin DSX AI Factory reference design. The announcement indicates an on-premise AI infrastructure focus; detailed capacity, timelines, and specific Microsoft platform elements were not provided in the excerpt.

AT&T announced a collaboration with Cisco and NVIDIA to provide network-integrated edge AI capabilities for enterprise customers, combining AT&T’s network with Cisco infrastructure and NVIDIA AI platforms. The effort targets enterprise edge deployments in the United States.

ZEDEDA and Submer announced a partnership to offer rapidly deployable, integrated edge AI infrastructure aimed at simplifying field installation and management of AI workloads. The solution combines ZEDEDA's edge orchestration with Submer-provided hardware infrastructure for remote and distributed environments.

Palantir and Nvidia introduced the Palantir AI OS Reference Architecture, a hardened Kubernetes-based blueprint that supports end-to-end AI workflows from hardware acquisition to application deployment. The design runs training and inference on Nvidia Blackwell Ultra systems (eight GPUs per node) with Spectrum-X Ethernet, integrates Palantir AIP, Foundry, Apollo, Rubix, and AIP Hub, and includes Nvidia AI Enterprise, CUDA-X Libraries, Nemotron open models, and Magnum IO. Management and security are delivered via Palantir Rubix (zero-trust Kubernetes) and Apollo (autonomous deployment/lifecycle), enabling on-prem, edge, and sovereign cloud deployments with data/model control.

Cisco, in partnership with NVIDIA, broadened the Cisco Secure AI Factory with NVIDIA from core data centers to the edge, adding support for NVIDIA RTX Pro 4500 Blackwell Server Edition GPUs across Cisco UCS and Unified Edge portfolios, while leveraging N9100 switches with NVIDIA Spectrum-X Ethernet and NVIDIA AI Enterprise software under Cisco Validated Designs with a security-led focus.