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...
Marvell Technology’s first-quarter revenue beat highlights the surging demand for AI-focused data center chips in 2026. Beyond GPUs, Marvell’s strength in AI interconnects and networking ASICs positio...
Major hyperscalers recently signed a White House-backed pledge to fund new power generation and grid upgrades for AI data centers, signaling a shift toward sustainable AI infrastructure. Combined with...
In 2026, AI infrastructure is undergoing a strategic transformation driven by power-centric semiconductor design, network scaling via 25G Ethernet, and industry realignments emphasizing AI integrity. ...
The pledge by seven major AI hyperscalers to directly invest in power generation and grid upgrades marks a strategic shift addressing critical energy bottlenecks for AI infrastructure scaling. This an...
As AI workloads surge, providers face the challenge of maximizing GPU utilization while managing rising energy demands that strain data center power grids. Northern Data's 85% GPU allocation efficienc...
NVIDIA is advancing AI infrastructure not just through raw power but by integrating hardware and software for greater efficiency and scalability. Their NVFP4 training format, hardware-software co-desi...