Maximizing the value of AI infrastructure demands deep visibility into GPU utilization. Yet many platform teams running AI workloads on Kubernetes operate with...

Maximizing the value of AI infrastructure demands deep visibility into GPU utilization. Yet many platform teams running AI workloads on Kubernetes operate with limited visibility into how their GPUs are used. Most don’t know who’s consuming them, how much memory is in use, and whether Kubernetes pods are pending or silently idle. Without a signal, GPU fleets are routinely underutilized and slow to…

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Telcos around the world are building sovereign AI factories based on the NVIDIA Cloud Partner (NCP) reference architecture, giving governments, enterprises, and...

Telcos around the world are building sovereign AI factories based on the NVIDIA Cloud Partner (NCP) reference architecture, giving governments, enterprises, and startups access to in‑country AI infrastructure with the right controls, trust, and performance. But infrastructure alone doesn’t get you to high-margin, production-ready enterprise AI services. Model sizes and reasoning workloads…

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Autonomous AI agents are becoming more capable. Open models, Model Context Protocol (MCP)-connected tools, and portable skills are also making agents easier to...

Autonomous AI agents are becoming more capable. Open models, Model Context Protocol (MCP)-connected tools, and portable skills are also making agents easier to extend.But scaling agent use with structural transparency and operational integrity requires more than runtime guardrails. Organizations and teams need to understand and trust the skills, or instructions, an agent is using.

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Evaluating an AI model and evaluating an AI agent are related—but they answer fundamentally different questions. A model benchmark tests the capability of a...

Evaluating an AI model and evaluating an AI agent are related—but they answer fundamentally different questions. A model benchmark tests the capability of a foundation model (how well it understands language, follows instructions, or solves problems on static tasks). An agent evaluation tests the behavior of a system operating end-to-end—planning, calling tools, handling uncertainty…

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A massive-scale X-ray free-electron laser (XFEL) enables tracking structural and electron dynamics in novel systems, including fusion materials, semiconductors,...

A massive-scale X-ray free-electron laser (XFEL) enables tracking structural and electron dynamics in novel systems, including fusion materials, semiconductors, batteries, and catalysis. It produces ultrashort X-ray pulses that can record the movements of atoms and electrons. These instruments can detect the smallest change in material structure caused by defects and other influences.

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An agentic exchange must preserve a structured interaction: assistant turns interleave reasoning with one or more tool calls, and subsequent user turns return...

An agentic exchange must preserve a structured interaction: assistant turns interleave reasoning with one or more tool calls, and subsequent user turns return the corresponding tool results to the model context. Reasoning replay is model- and turn-dependent: some reasoning should be retained, while some should be dropped. The inference engine is responsible for supporting this more expressive…

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