Marvell Technology forecasted strong fiscal 2028 revenue growth driven by demand for its AI-focused chips and interconnect technologies, following a first-quarter earnings beat. The company’s outlook ...
Telecom operators are increasingly outsourcing AI infrastructure to cloud providers to manage soaring costs and scalability challenges. This shift improves flexibility but raises questions about laten...
AI data centers in the US are rapidly increasing electricity demand, putting strain on the power grid comparable to large cities. While efficiency efforts help, the scale of AI workloads requires new ...
The Mesh argues that for edge AI hardware, energy efficiency has become more critical than minimizing chip size due to stringent power constraints in real-world devices. Prioritizing power consumption...
Marvell Technology’s $5.5 billion investment in networking and security silicon marks a strategic shift in AI infrastructure, emphasizing connectivity and chip-level security alongside compute. This m...
Recent advances in AI chip security, optical interconnects, and ultra-high bandwidth memory are driving a fundamental shift in semiconductor design. These innovations address emerging AI integrity thr...
Unified AI infrastructure at the edge integrates compute, connectivity, and power management within micro data centers, enabling real-time AI workloads with ultra-low latency and improved power effici...
Marvell Technology’s recent earnings and growth forecast highlight a shift in AI data center infrastructure toward specialized chips and interconnects. This trend reflects broader industry moves towar...
This blog highlights three key AI infrastructure trends for 2026: NVIDIA’s NVFP4 low-precision format, the growing role of edge data centers, and new security guidance for autonomous AI systems. Toget...
In 2026, edge data centers, on-chip security, and AI inference agents are converging to overcome latency, power, and security challenges in AI deployment. This trio is reshaping where and how AI opera...