Helping build shared standards for advanced AI

Helping build shared standards for advanced AI

Increasingly capable models can strengthen cyber defense, accelerate scientific discovery, and expand access to expertise. But they can also create safety and security risks if their capabilities are misunderstood, their safeguards are inadequate, or governments lack the information they need to respond. To realize the benefits safely and confidently, societies will need institutions with the…

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How Businesses Are Building Specialized AI They Can Trust

How Businesses Are Building Specialized AI They Can Trust

Editor’s note: This post is part of the Nemotron Labs blog series, which explores how the latest open models, datasets and training techniques help businesses build specialized AI systems and applications on NVIDIA platforms. Each post highlights practical ways to use an open stack to deliver real value in production — from transparent research copilots…

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NVIDIA and AWS Collaborate to Bring AI to Production at Scale

NVIDIA and AWS Collaborate to Bring AI to Production at Scale

Building AI systems at scale is demanding, requiring low-latency inference, fast vector search, strong GPU price-performance and infrastructure that can grow without multiplying operational complexity.  NVIDIA’s latest work with Amazon Web Services (AWS) addresses each of those constraints. Across Amazon OpenSearch and Amazon EC2, NVIDIA AI infrastructure is giving enterprises more practical paths to deploy…

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Introducing computer use in Gemini 3.5 Flash

Introducing computer use in Gemini 3.5 Flash

Making computer use safe in 3.5 Flash To mitigate some of the prompt injection risks for agents operating in live environments, we use targeted adversarial training for computer use in Gemini 3.5 Flash. We’re also releasing two optional enterprise safeguard systems that enable enterprises to: Require explicit user confirmation for sensitive or irreversible actions. Automatically…

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