Tool Usage

Tool usage in artificial intelligence focuses on enabling AI agents, particularly large language models (LLMs), to effectively utilize external tools and resources to solve complex tasks beyond their inherent capabilities. Current research emphasizes efficient tool selection strategies, often employing reinforcement learning and Markov Decision Processes to optimize tool usage and minimize computational costs, as well as developing frameworks for integrating LLMs with diverse toolsets, including cheminformatics tools and codebases. This research is significant for advancing AI capabilities in various domains, from robotics and software engineering to scientific discovery, by enabling more robust, adaptable, and efficient AI systems.