Month: June 2025

Imagine you’re leading security for a large enterprise and your teams are eager to leverage AI for more and more projects. There’s a problem, though. As…

Imagine you’re leading security for a large enterprise and your teams are eager to leverage AI for more and more projects. There’s a problem, though. As with any project, you must balance the promise and returns of innovation with the hard realities of compliance, risk management, and security posture mandates. Security leaders face a crucial challenge when evaluating AI models such as those…

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As AI progresses toward greater autonomy, the emergence of AI agents capable of independent decision-making marks a significant milestone. To function…

As AI progresses toward greater autonomy, the emergence of AI agents capable of independent decision-making marks a significant milestone. To function effectively in complex, real-world environments, these agents must go beyond pattern recognition and statistical predictions. This is driven by the adoption of reasoning models, designed to process information, apply logic, and make decisions…

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The shift to end-to-end planning models for powering autonomous vehicles (AVs) is increasing the demand for high-quality, physically-based sensor data. These…

The shift to end-to-end planning models for powering autonomous vehicles (AVs) is increasing the demand for high-quality, physically-based sensor data. These models must have a general understanding of multi-modal datasets, along with the relationships between sensor datasets, vehicle trajectories, and driving actions to help with downstream training and validation tasks. By adapting and post…

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Enterprise data is exploding—petabytes of emails, reports, Slack messages, and databases pile up faster than anyone can read. Employees are left searching for…

Enterprise data is exploding—petabytes of emails, reports, Slack messages, and databases pile up faster than anyone can read. Employees are left searching for answers in a sea of information, as “68% of available data in an organization goes unused,” according to market researcher Gartner1. That’s now possible with today’s availability of AI-Q, an open-source NVIDIA Blueprint that puts your…

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Autonomous vehicle (AV) stacks are evolving from a hierarchy of discrete building blocks to end-to-end architectures built on foundation models. This transition…

Autonomous vehicle (AV) stacks are evolving from a hierarchy of discrete building blocks to end-to-end architectures built on foundation models. This transition demands an AV data flywheel to generate synthetic data and augment sensor datasets, address coverage gaps and, and ultimately, build a validation toolchain to safely develop and deploy autonomous vehicles. In this blog post…

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Integrating large language models (LLMs) into a production environment, where real users interact with them at scale, is the most important part of any AI…

Integrating large language models (LLMs) into a production environment, where real users interact with them at scale, is the most important part of any AI workflow. It’s not just about getting the models to run—it’s about making them fast, easy to manage, and flexible enough to support different use cases and production needs. With a growing number of LLMs, each with its own architecture…

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Modern products often consist of millions of parts and require intricate design and collaboration. The industrial world is facing significant challenges in…

Modern products often consist of millions of parts and require intricate design and collaboration. The industrial world is facing significant challenges in managing their complexity, with traditional visualization tools failing to render these large, multi-CAD assemblies with the true-to-life realism required to fully benefit from digital twins. To address these struggles…

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Businesses make thousands of decisions every day—what to produce, where to ship, how to allocate resources. At scale, optimizing these decisions becomes a…

Businesses make thousands of decisions every day—what to produce, where to ship, how to allocate resources. At scale, optimizing these decisions becomes a computational challenge. Linear programming (LP), mixed-integer programming (MIP), and vehicle routing problems (VRP) provide structure, but solving them fast is where the bottleneck begins. NVIDIA cuOpt brings GPU acceleration to decision…

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As enterprise adoption of agentic AI accelerates, teams face a growing challenge of scaling intelligent applications while managing inference costs. Large…

As enterprise adoption of agentic AI accelerates, teams face a growing challenge of scaling intelligent applications while managing inference costs. Large language models (LLMs) offer strong performance but come with substantial computational demands, often resulting in high latency and costs. At the same time, many development workflows—such as evaluation, data curation…

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