North America

America's AI Boom
Data Centers

Not In My Backyard: AI Infrastructure Meets Local Resistance

The AI infrastructure NIMBY backlash is emerging as artificial intelligence moves from abstract software into physical reality. Across parts of the United States, data centers built to power AI workloads have become highly visible fixtures, tied directly to land use, electricity demand, and water access. As these facilities expand, they increasingly face the same local resistance once reserved for power plants, pipelines, and heavy industrial sites.

AI Infrastructure Expansion
AI & Machine Learning

Nvidia Deepens CoreWeave Bet With $2 Billion Investment For AI

Nvidia has committed $2 billion to CoreWeave, deepening a partnership that both companies say will accelerate the global buildout of AI-focused data centers. The investment, made through the purchase of CoreWeave Class A shares at $87.20 per share, anchors a broader plan to construct more than 5 gigawatts of AI factory capacity by 2030. The move signals Nvidia’s intent to push harder into the physical layer of AI computing as demand for GPU-intensive workloads continues to surge. Rather than relying solely on traditional cloud providers, Nvidia is strengthening ties with a specialist operator that designs, builds, and runs infrastructure purpose-built for artificial intelligence.

AI data center energy demands
Power & Energy Grid

America’s Power Grid Strains Under Escalating AI Energy Demands

Rising Electricity Costs Spotlight AI’s Energy Footprint

America’s power grid strains under escalating AI energy demands as data centers continue to expand rapidly. Recent figures reveal that these high-demand facilities have contributed $6.5 billion to electricity costs following the December auction held by PJM Interconnection LLC. These facilities, which power cloud services, AI systems, and other digital operations, are emerging as some of the nation’s largest consumers of electricity, raising concerns over the sustainability of grid infrastructure.

PJM, the regional grid operator covering nearly 20% of the U.S. population, now projects electricity costs for data centers between June 2025 and May 2028 to reach $23.1 billion, almost half of the $47.2 billion recorded in previous auctions. As these numbers rise, the financial impact on both businesses and households becomes increasingly apparent, prompting debate over how energy-intensive AI technologies should be managed.

AI infrastructure training versus inference
AI & Machine Learning

Inside the Structural Reset of AI Infrastructure

The future of AI infrastructure is being shaped by a quiet but consequential split: training versus inference.

Training large models demands massive, power-dense campuses, often located in remote, energy-rich regions. Inference workloads- the engines behind real-time applications, pull infrastructure in the opposite direction, toward users, networks, and urban demand centers. This divergence is giving rise to two distinct data center archetypes, each with its own requirements for power, cooling, and siting.

As inference begins to overtake training as the dominant AI workload, hyperscalers are being forced to rethink their infrastructure strategies, balancing scale, speed, and resilience under mounting energy constraints.

data center energy efficiency
Data Centers

Keeping data centers resilient amid rising AI demand

The Rise of Micro Data Centers

The rise of micro data centers marks a shift in how digital infrastructure is deployed, managed, and scaled. Organizations are seeing a transition away from fully centralized compute footprints toward smaller, modular, and highly localized environments. These compact facilities support the growing demand for rapid data processing across distributed ecosystems. They enable enterprises to position compute power closer to users, applications, and devices. As a result, they shape new architectural patterns and operational models across industries.

Why Micro Data Centers Are Reshaping Deployment Models

The expansion of connected systems, remote work, and real-time applications has influenced how organizations design infrastructure strategies. Micro data centers offer a controlled and self-contained environment capable of supporting essential workloads.

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