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NVIDIA Vera Rubin and Blackwell Set a New Standard for Agentic AI Performance per Watt 

AI agents have expanded inference from single-turn interactions into multi-step workflows that reason, invoke tools, coordinate subagents, and carry growing…

AI agents have expanded inference from single-turn interactions into multi-step workflows that reason, invoke tools, coordinate subagents, and carry growing context from one turn to the next. The scale of this shift is now visible in raw consumption: across 100 trillion tokens of real-world usage, OpenRouter’s State of AI report found that average prompt tokens per request grew roughly fourfold…

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Giga-Scale AI and the Ethernet Evolution: How Spectrum-X Ethernet Rewrites the Rules

The massive growth of generative AI has fundamentally altered data center design. As distributed model training scales to span hundreds of thousands of GPUs,…

The massive growth of generative AI has fundamentally altered data center design. As distributed model training scales to span hundreds of thousands of GPUs, the scale-out network connecting these nodes has emerged as a first-order performance bottleneck. For decades, traditional off-the-shelf Ethernet has been the undisputed king of enterprise and cloud networking. It is cheap, standardized…

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GPU-Accelerated Clustering for Financial Instruments at Scale

Use AdaptGrow, a GPU-accelerated matrix factorization algorithm, to turn rolling correlation and tail-dependence matrices into hard clusters, soft factor…

Use AdaptGrow, a GPU-accelerated matrix factorization algorithm, to turn rolling correlation and tail-dependence matrices into hard clusters, soft factor loadings, and structural-break signals at single-GPU and multi-node scale Quant strategies routinely group instruments for portfolio construction, risk aggregation, statistical arbitrage, and trade surveillance. Incorrect groupings can make…

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Maximizing AI Factory Performance per Watt with NVIDIA DSX MaxLPS

AI factories are power-constrained industrial systems. The question is no longer how many GPUs fit in a data center, but how much AI output each available…

AI factories are power-constrained industrial systems. The question is no longer how many GPUs fit in a data center, but how much AI output each available megawatt can deliver. For AI inference workloads, this makes application-level performance per watt the key metric for measuring AI factory efficiency. Not every megawatt translates to revenue-generating compute. Power distribution, cooling…

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NVIDIA AVO Reaches 100% on ARC-AGI-3, Demonstrating a Frontier-Level General-Purpose Architecture for Long-Horizon Autonomous Agents

A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives…

A frontier language model is only one component of an AI agent. The surrounding agent system—often called a harness—determines how the model receives context, uses tools, maintains state, responds to feedback, recovers from failure, and sustains progress over long-running tasks. The challenge is how to build the agent architecture that makes frontier language models work reliably on extended…

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Where Security Fits in an AI Agent Stack

As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important….

As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important. Drawing on work with NVIDIA OpenShell, agent developers, open-source projects, and partners across the ecosystem, AI safety and security teams at NVIDIA offer their perspective on the emerging agent stack—including the role of each layer…

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Measuring benchmark optimization in speech recognition

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How Generative Recommenders Are Redefining RecSys at Scale

Recommender systems (RecSys) are one of the most ubiquitous machine learning problems in the consumer internet industry yet notoriously difficult to train and…

Recommender systems (RecSys) are one of the most ubiquitous machine learning problems in the consumer internet industry yet notoriously difficult to train and serve at scale. The advent of LLMs has inspired a shift from the traditional embedding-similarity-based objective to a generative one, where the goal is to predict the next action or item in a large catalog given a sequence of user histories.

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Up to 3.2x Faster Inference with LFM2.5-DSpark

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Bring the Fire: Play Games on GeForce NOW With New Firefox Browser Support

It’s a new way into the cloud.  GeForce NOW welcomes Firefox support to the cloud, opening up another way to jump into high-performance PC gaming straight from the browser, starting today. Whether on a school laptop or everyday PC, it’s now even easier to play supported PC games without downloading a dedicated app. Plus, discover […]