The recent release of large language model (LLM) based chatbots, such as ChatGPT, has attracted significant attention on foundation models. It is widely believed that foundation models will serve as the fundamental building blocks for future AI systems. As foundation models are in their early stages, the design of foundation model based systems has not yet been systematically explored. There is little understanding about the impact of introducing foundation models in software architecture. Therefore, in this paper, we propose a taxonomy of foundation model based systems, which classifies and compares the characteristics of foundation models and design options of foundation model based systems. Our taxonomy comprises three categories: foundation model pretraining and fine-tuning, architecture design of foundation model based systems, and responsible-AI-by-design. This taxonomy provides concrete guidance for making major design decisions when designing foundation model based systems and highlights trade-offs arising from design decisions.

翻译：近期基于大语言模型（LLM）的聊天机器人（如ChatGPT）的发布，吸引了人们对基础模型的广泛关注。人们普遍认为，基础模型将成为未来人工智能系统的基本构建单元。由于基础模型仍处于早期发展阶段，基于基础模型的系统设计尚未得到系统性的探索。目前对于在软件架构中引入基础模型所产生的影响缺乏深入理解。因此，本文提出了一种基于基础模型的系统分类体系，该分类体系对基础模型的特性及基于基础模型的系统的设计选项进行了分类与比较。我们的分类体系涵盖三个维度：基础模型的预训练与微调、基于基础模型的系统架构设计，以及以实现负责任人工智能为设计导向。该分类体系为设计基于基础模型的系统时的关键设计决策提供了具体指导，并揭示了设计决策中产生的权衡取舍。