Nvidia Publishes Multi-Agent Systems Reference Guide
Nvidia adds a detailed glossary entry on multi-agent systems, outlining how networked AI agents collaborate on complex tasks.
Nvidia has published a glossary entry on multi-agent systems, defining the architecture pattern in which multiple specialized AI agents coordinate to solve complex business problems. The reference covers how these systems leverage advanced reasoning to divide and conquer tasks that would overwhelm a single model.
The move signals Nvidia's continued investment in agentic AI as a category worth formalizing for its developer and enterprise audience. Multi-agent architectures have gained traction as organizations look to chain together purpose-built agents — each handling retrieval, planning, or execution — rather than relying on monolithic models. By codifying the concept in its official glossary alongside established terms like RAG and LLM, Nvidia is positioning multi-agent systems as foundational infrastructure rather than an experimental pattern. For teams evaluating agentic frameworks, the entry serves as a vendor-neutral primer on core concepts and design trade-offs.