As AI workloads become more intense and mission-critical, data centers are undergoing a fundamental redesign to support high power densities, advanced cooling, and environmental sustainability. This a...
The rapid growth of AI workloads is significantly increasing data center power consumption, putting strain on the U.S. electrical grid. This analysis explores how AI's unique power demands challenge t...
In 2026, AI infrastructure is undergoing a transformative shift driven by NVIDIA's NVFP4 low-precision training format, the expansion of edge and micro data centers, and innovative high-density data c...
The rapid growth of AI data centers in the U.S. is placing unprecedented strain on the national power grid, threatening reliability and environmental goals. This editorial calls for urgent, coordinate...
Marvell Technology's focused investment in AI-specific data center interconnects, including silicon photonics and custom chips, is driving its strong financial performance and market positioning. By s...
Marvell Technology’s dedicated focus on AI interconnect silicon has driven its recent financial success amid hyperscalers’ massive investments in AI data centers. This analysis explains why Marvell’s ...
The expansion of AI workloads in US data centers is intensifying power grid strain while operators achieve higher GPU utilization efficiencies. This analysis explores how these intersecting trends cre...
In March 2026, AI infrastructure is evolving through NVIDIA’s hardware-software co-design, the rise of unified intelligence models, and a transforming semiconductor industry. These trends point toward...
The Mesh argues that the semiconductor industry must prioritize power efficiency over die area in next-generation edge GPU design. This power-first approach is essential to meet the strict constraints...
Northern Data’s recent report of 85% GPU allocation efficiency highlights a pivotal shift in AI infrastructure economics in 2026. This analysis explores how improved GPU utilization enhances profitabi...