DIGITAL SOLUTIONS: TinyAgent: An End-to-End AI Framework for Training and Deploying Task-Specific Small Language Model Agents
The significant advancements in Large Language Models (LLMs) have led to the development of agentic systems, which integrate several tools and APIs to fulfill user inquiries through function calls. By interpreting natural language commands, these systems can perform sophisticated tasks independently, such as information retrieval and device control. However, much research hasn't been done on using these LLMs locally, on laptops or smartphones, or at the edge. The primary limitation is the large size and high processing demands of these models, which usually require cloud-based infrastructure to function properly. In recent research from UC Berkeley and ICSI, the TinyAgent framework
