The release of ChatGPT, Bard, and other large language model (LLM)-based chatbots has drawn huge attention on foundations models worldwide. There is a growing trend that foundation models will serve as the fundamental building blocks for most of the future AI systems. However, incorporating foundation models in AI systems raises significant concerns about responsible AI due to their black box nature and rapidly advancing super-intelligence. Additionally, the foundation model's growing capabilities can eventually absorb the other components of AI systems, introducing the moving boundary and interface evolution challenges in architecture design. To address these challenges, this paper proposes a pattern-oriented responsible-AI-by-design reference architecture for designing foundation model-based AI systems. Specially, the paper first presents an architecture evolution of AI systems in the era of foundation models, from "foundation-model-as-a-connector" to "foundation-model-as-a-monolithic architecture". The paper then identifies the key design decision points and proposes a pattern-oriented reference architecture to provide reusable responsible-AI-by-design architectural solutions to address the new architecture evolution and responsible AI challenges. The patterns can be embedded as product features of foundation model-based AI systems and can enable organisations to capitalise on the potential of foundation models while minimising associated risks.
翻译:ChatGPT、Bard和其他基于大型语言模型(LLM)的聊天机器人的发布引起了全球对基础模型的巨大关注。越来越多的人认为,基础模型将成为未来大多数人工智能系统的基本构建块。然而,将基础模型纳入人工智能系统中,由于其黑匣子本质和快速发展的超级智能,引发了负责任人工智能的重要关切。此外,基础模型日益增长的功能最终可以吸收人工智能系统的其他组件,引入了架构设计中的移动边界和接口演进挑战。为了解决这些挑战,本文提出了一种面向模式的负责任人工智能设计参考架构,用于设计基于基础模型的人工智能系统。特别地,本文首先介绍了基于基础模型的人工智能系统的架构演进,从“基础模型作为连接器”到“基础模型作为单个架构”。然后,本文确定了关键的设计决策点,并提出了面向模式的参考架构,以提供可重用的负责任人工智能设计架构解决方案,以解决新的架构演进和负责任人工智能挑战。这些模式可以嵌入到基于基础模型的人工智能系统的产品功能中,并使组织能够充分利用基础模型的潜力,同时最小化相关风险。