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...
NVIDIA’s recent hardware-software innovations in 2026 are reshaping AI infrastructure by improving efficiency in training and inference. Their new low-precision format NVFP4 and optimized compiler int...
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...
NVIDIA’s integrated approach to AI infrastructure—combining precision format innovations like NVFP4, extreme hardware-software co-design, and enhanced programming frameworks—delivers substantial gains...
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 ...
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...
In 2026, AI infrastructure is evolving through improved GPU utilization, strategic outsourcing by telecom operators, and advancements in 25G Ethernet networking. These trends collectively optimize res...