This opinion piece argues that nuclear power, particularly modern small modular reactors, is essential for meeting the explosive energy demands of AI infrastructure sustainably. It critiques reliance ...
The AI industry’s reliance on GPUs for data center infrastructure is a strategic risk amid supply chain fragility and power demands. Silicon diversification—embracing AI accelerators, ASICs, and speci...
Advances in indium phosphide, silicon photonics, co-packaged optics, and optical circuit switches are driving a rapid shift from electrical to fully optical interconnects in AI data centers within fiv...
Power infrastructure is emerging as a critical bottleneck in scaling AI data centers. Beyond GPUs and cooling, challenges around energy delivery, storage, and innovative cooling methods are reshaping ...
As AI workloads drive a projected fourfold increase in data center energy demand, innovations in nuclear power, ocean-based energy, and integrated liquid cooling are emerging as key enablers of sustai...
Q1 2026 reveals a strategic shift in AI infrastructure driven by accelerated chip innovation, supply chain compression, and hybrid cloud adoption. This analysis details how investments by Cerebras, Qu...
In 2026, breakthroughs in compute, power, and orchestration are converging to drive the rise of agentic AI. This blog explores how innovations like NVIDIA’s multimodal models, Meta and AWS’s chip part...
Accelerated GPU product cycles and the expanding role of CPUs in agentic AI workloads are transforming AI infrastructure. This analysis explores how compressed GPU refresh intervals and hybrid CPU-GPU...
Agentic AI systems are emerging alongside complex multi-vendor partnerships, creating new challenges for data center power management. As AI workloads grow, infrastructure must evolve beyond tradition...
Agentic AI’s autonomous capabilities present unprecedented opportunities but also expose critical vulnerabilities in identity management and security. Without robust, transparent frameworks, AI agents...