Recent research from KAUST and Compumacy demonstrates that multi-workload co-optimization significantly enhances the energy efficiency and versatility of in-memory computing (IMC) AI accelerators. By ...
In early 2026, the AI accelerator industry is shifting toward heterogeneous silicon platforms, in-memory computing, and enhanced data movement via 25G Ethernet. Broadcom’s $100 billion investment in s...
US data centers' electricity demand, driven by rapid AI infrastructure growth, is nearing levels comparable to several major cities combined, posing significant challenges for grid stability. This ana...
GE Vernova announced a contract to upgrade 1.1 GW of onshore wind turbines across the U.S., enhancing renewable capacity to meet rising electricity demands from AI and technology sectors. The upgrades...
As agentic AI systems gain greater autonomy, their execution environments face heightened security risks that traditional methods cannot fully address. This analysis examines how integrating practical...
NVIDIA’s recent AI advancements focus on smarter precision with NVFP4, improved long-context training through JAX and XLA, and reducing inference costs for real-time game agents. These developments si...
AI infrastructure is undergoing a transformation driven by the integration of processing units with connectivity components and the expansion of edge and micro data centers. This shift addresses laten...
NVIDIA is shifting its AI infrastructure strategy from raw power to smarter, more efficient designs. Their innovations in low-precision formats, software optimizations, and sovereign AI hardware point...
NVIDIA's NVFP4 low-precision format significantly enhances AI model training and inference by boosting throughput and energy efficiency without sacrificing accuracy. This analysis explores NVFP4's tec...
NVIDIA’s NVFP4 low-precision training and support for long-context models, combined with OpenAI and Oracle’s Project Stargate, are driving a new era in AI infrastructure. This shift emphasizes integra...