How Small Language Models Are Key to Scalable Agentic AI
How Small Language Models Are Key to Scalable Agentic AI | NVIDIA Technical Blog
“The rapid rise of agentic AI has reshaped how enterprises, developers, and entire industries think about automation and digital productivity. From software development workflows to enterprise process orchestration, AI agents are increasingly helping to power enterprises’ core operations, especially in areas that have previously been deemed plagued by repetitive tasks.
Most of these agents depend heavily on large language models (LLMs). LLMs are often recognized for their general reasoning, fluency, and capacity to support open-ended dialogue. But when they’re embedded inside agents, they may not always be the most efficient or economical choice. In our recent position paper, we outline our observations about the role small language models (SLMs) play in agentic AI. Titled Small Language Models are the Future of Agentic AI, we highlight the growing opportunities for integrating SLMs in place of LLMs in agentic applications, decreasing costs, and increasing operational flexibility.
Our stance isn’t that LLMs will stop being useful in the context of agents. Instead, we point to the rise of heterogeneous ecosystems where SLMs play a central operational role while LLMs are reserved for situations where their generalist capabilities are indispensable…”
Source: developer.nvidia.com/blog/how-small-language-models-are-key-to-scalable-agentic-ai/