The next phase of AI infrastructure will not be defined by a single destination called “the cloud” or “the edge.” ...

The funding will support the development of Sherpa.ai's AI platform and accelerate its international expansion across key ...

AI infrastructure spending is broadening beyond model training into inference, edge distribution, and data center ...

Autonomous AI post-training reached frontier scale for the first time: NVIDIA researchers published a paper showing an AI ...

One seismometer is often not enough to reliably detect earthquakes or human activity such as underground nuclear tests.

Learn why scalable AI needs balanced servers, storage, networking, and data access to support training, inference, and RAG at ...

The dancers had used music generated by AI. Whatever model was involved had likely been trained on “You Get What You Give” ...

China’s Meituan open-sources massive LongCat-2.0 AI model, saying it was trained on domestic chips - SiliconANGLE ...

Artificial intelligence (AI) can put together readings from multiple sensors more effectively than classic technology, ...

Enterprise conversations around artificial intelligence are beginning to shift noticeably. For the past few years, much of ...

While large-scale training models often capture public attention, it is AI inference—the continuous, real-time execution of trained models—that is rapidly reshaping how digital infrastructure must be ...

As agentic AI systems scale across cloud and datacenter environments, CPUs remain the control plane coordinating performance ...