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Building for the Rising Complexity of Agentic Systems with Extreme Co-Design

Generative AI’s explosive first chapter was defined by humans sending requests and models responding. The agentic chapter is different.Β  Agents don't...

Generative AI’s explosive first chapter was defined by humans sending requests and models responding. The agentic chapter is different. Agents don’t follow a pre-determined sequence of actions. They call tools, spawn sub-agents with different tasks and models, retain information in memory, manage their own context window, and decide for themselves when they’re finished. In doing so…

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Powering AI Factories with NVIDIA Enterprise Reference Architectures

A person working on a data center rack.The next wave of enterprise productivity is being built on AI factories. As organizations deploy agentic AI systems capable of reasoning, automation, and...A person working on a data center rack.

The next wave of enterprise productivity is being built on AI factories. As organizations deploy agentic AI systems capable of reasoning, automation, and real-time decision-making at scale, competitive advantage increasingly depends on the infrastructure that supports them. Success requires more than raw compute. It demands a scalable, predictable foundation that can orchestrate intelligent…

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Scaling Biomolecular Modeling Using Context Parallelism in NVIDIA BioNeMo

For decades, computational biology has operated under a reductionist compromise. To fit complex biological systems into the limited memory of a single GPU,...

For decades, computational biology has operated under a reductionist compromise. To fit complex biological systems into the limited memory of a single GPU, researchers have had to deconstruct them into isolated fragmentsβ€”single proteins or small domains. This created a context gap, where larger proteins or complexes could not be folded zero-shot due to GPU hardware memory constraints. Now…

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