从生成式人工智能到通用人工智能：赋能图书馆知识服务模式创新

doi:10.13998/j.cnki.issn1002-1248.24-0464

Abstract

Abstract:

[Purpose/Significance] The development of artificial intelligence (AI) technology has brought huge changes and opportunities to library knowledge services. With the improvement of the multimodal capabilities of large language models, the ability of generative artificial intelligence to generate cultural images, cultural audio, and cultural video will also improve, which will effectively promote the intelligent transformation of library knowledge services and support the innovation of library knowledge services. General AI has stronger generalization ability, which can achieve functions such as complex task understanding, multimodal data learning, zero-sample reasoning, and continuous dialogue, completing the transformation from data-driven AI to natural mechanism-driven AI. By studying the theoretical foundation, system framework and application perspective of knowledge services based on artificial general intelligence, we can get new research ideas and practical references for knowledge services. [Method/Process] Based on the classification of the development history of AI, this article examines the state of research in AI for library knowledge services from the dynamic perspective of the evolution from generative AI to artificial general intelligence. This article analyzes the system framework of library knowledge services constructed with generative artificial intelligence and artificial general intelligence as technical bases, and explores the future development trend of library knowledge services based on artificial general intelligence from the aspects of space, content, mechanism and talent. [Results/Conclusions] With the continuous development and optimization of large language model technologies, the gradual implementation and widespread application of artificial general intelligence technology is an inevitable trend in the future. With the promotion of artificial general intelligence, library knowledge services will also undergo significant changes, and the traditional knowledge service model based on existing resources will gradually transform into a digital intelligence service model. Although artificial general intelligence has shown great potential in knowledge understanding and content generation, artificial general intelligence is still at an early stage of development, and its prospects for application in library knowledge services are not yet clear. In order to explore the impact of artificial general intelligence on the library knowledge service model, this article summarizes the different stages of AI technology integration in knowledge services, namely the evolution from automation to cognition and then to autonomy, and proposes an AI agent-driven library knowledge service framework. It is believed that artificial general intelligence technology will open up new development space for library knowledge services, promote academic research and practical applications in knowledge services and enter a new era of rapid development.

Key words: generative artificial intelligence, artificial general intelligence, library, knowledge services, technical architecture

CLC Number:

G250.7

Mo LI, Bin YANG. From Generative Artificial Intelligence to Artificial General Intelligence: Enabling Innovation Models in Library Knowledge Services[J].Journal of library and information science in agriculture, 2024, 36(6): 50-61.

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类别能力	决策式人工智能（DAI）	生成式人工智能（GAI）	通用人工智能（AGI）
核心能力	执行预定任务、自动化处理知识数据	生成知识内容、多轮对话、提供具体回答	独立思考、自主决策
交互方式	需要预设知识服务任务和规则，无须人工干预	通过用户Prompt进行交互，需要清晰的任务描述	给定目标后自行规划知识服务步骤和行动
应对环境变化	无法处理未知知识信息和应对环境变化	受限于训练数据和Prompt清晰度，难以应对环境变化	能够处理未知环境信息，可以自主调整
知识服务场景	适用于固定、重复性高的知识服务场景	作为助力，需要明确知识服务任务的场景	适用于需要独立决策和自主学习的知识服务场景
自主性	低，完全依赖预设知识服务规则和任务	中等，需要用户提供明确的Prompt才能生成相关知识	高，能够自我设定目标、生成Prompt、自主学习
灵活性和适应性	弱，只能在固定场景下高效工作，面对新情景需要重新配置规则	有限，主要依赖训练数据和Prompt质量，适应性取决于大模型的泛化能力	强，能通过与环境交互感知信息，适应复杂多变的知识服务流程和任务

From Generative Artificial Intelligence to Artificial General Intelligence: Enabling Innovation Models in Library Knowledge Services

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