In this paper, we introduce LLMind, an AI framework that utilizes large language models (LLMs) as a central orchestrator. The framework integrates LLMs with domain-specific AI modules, enabling IoT devices to collaborate effectively in executing complex tasks. The LLM engages in natural conversations with human users via a user-friendly social media platform to come up with a plan to execute complex tasks. In particular, the execution of a complex task, which may involve the collaborations of multiple domain-specific AI modules and IoT devices, is realized through a control script. The LLM generates the control script using a Language-Code transformation approach based on finite-state machines (FSMs). The framework also incorporates semantic analysis and response optimization techniques to enhance speed and effectiveness. Ultimately, this framework is designed not only to innovate IoT device control and enrich user experiences but also to foster an intelligent and integrated IoT device ecosystem that evolves and becomes more sophisticated through continuing user and machine interactions.

翻译：本文介绍了LLMind，一个将大语言模型（LLMs）作为中央编排器的AI框架。该框架将LLMs与领域特定的AI模块集成，使物联网设备能够有效协作执行复杂任务。LLM通过用户友好的社交媒体平台与人类用户进行自然对话，制定执行复杂任务的计划。具体而言，涉及多个领域特定AI模块和物联网设备协作的复杂任务执行，通过控制脚本实现。LLM采用基于有限状态机（FSMs）的语言-代码转换方法生成控制脚本。该框架还融合了语义分析与响应优化技术，以提升速度与效果。最终，本框架不仅旨在创新物联网设备控制、丰富用户体验，还致力于培育一个智能集成的物联网设备生态系统，该生态系统通过持续的用户与机器交互不断演进并变得更加精密。