… Taiwan’s Ministry of Justice Investigation Bureau is leading the probe alongside prosecutors as officials attempt to trace how restricted AI infrastructure hardware moved through supply chains connected to Taiwanese manufacturers and exporters. …
… The company has been developing infrastructure capable of utilizing both GPUs and NPUs through dedicated execution providers, enabling applications to take advantage of available hardware acceleration while maintaining a consistent development platform. …
MSI has unveiled the MEG Vision X2 AI+, a new flagship desktop PC that combines high-end gaming hardware with a unique AI-focused user experience. The system introduces two major technologies: the LuckyClaw AI assistant and the AI Holostage, a dedicated display integrated directly into the chassis. …
… Consumer RTX GPUs are now commonly used not only for gaming, but also for AI inference, content generation, local machine learning workloads, and AI-enhanced PC applications. This overlap between gaming hardware and AI workloads likely contributed to the decision to consolidate categories. …
… Running larger models directly on client hardware remains heavily constrained by memory allocation and bandwidth, making unified memory one of the more important platform characteristics for compact AI systems. …
… AI-focused data centers and cloud providers increasingly depend on GPUs as the primary compute engine for AI training and inference workloads. While CPUs remain essential for server infrastructure, GPUs have become the core hardware resource behind modern AI deployments. …
… The Nvidia CEO further emphasized that China remains a competitive force in AI development, even without access to leading U.S. hardware. …
… AMD’s Ryzen AI 9 HX 470 processor continues the industry-wide push toward AI-enhanced PC hardware featuring integrated neural processing units designed for local inference and AI-assisted workloads. …
… While the performance level is modest compared to modern desktop-class AI hardware, the accelerator is optimized for embedded AI applications, robotics projects, industrial systems, and edge devices where power efficiency and local processing are priorities. …
… RDNA 4 architecture supports both FP8 and INT8 precision formats for AI workloads, while RDNA 3 hardware is limited to INT8 execution. …