{"title":"大型语言模型和应用:企业知识管理的重生与即时图书馆的崛起","authors":"Daniel E. O’Leary","doi":"10.1109/mis.2024.3366648","DOIUrl":null,"url":null,"abstract":"This article investigates how large language systems and the apps developed for them provide a platform for enterprise knowledge management. For those resulting systems to provide consistent and accurate responses for knowledge management, enterprises are using different approaches in their prompts, such as few-shot learning, specification of purpose, and chain-of-thought reasoning. As better and more successful prompts are being built, they are being captured and prompt libraries are being created.","PeriodicalId":13160,"journal":{"name":"IEEE Intelligent Systems","volume":"16 1","pages":""},"PeriodicalIF":5.6000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large Language Models and Applications: The Rebirth of Enterprise Knowledge Management and the Rise of Prompt Libraries\",\"authors\":\"Daniel E. O’Leary\",\"doi\":\"10.1109/mis.2024.3366648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article investigates how large language systems and the apps developed for them provide a platform for enterprise knowledge management. For those resulting systems to provide consistent and accurate responses for knowledge management, enterprises are using different approaches in their prompts, such as few-shot learning, specification of purpose, and chain-of-thought reasoning. As better and more successful prompts are being built, they are being captured and prompt libraries are being created.\",\"PeriodicalId\":13160,\"journal\":{\"name\":\"IEEE Intelligent Systems\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2024-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Intelligent Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/mis.2024.3366648\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Intelligent Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/mis.2024.3366648","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Large Language Models and Applications: The Rebirth of Enterprise Knowledge Management and the Rise of Prompt Libraries
This article investigates how large language systems and the apps developed for them provide a platform for enterprise knowledge management. For those resulting systems to provide consistent and accurate responses for knowledge management, enterprises are using different approaches in their prompts, such as few-shot learning, specification of purpose, and chain-of-thought reasoning. As better and more successful prompts are being built, they are being captured and prompt libraries are being created.
期刊介绍:
IEEE Intelligent Systems serves users, managers, developers, researchers, and purchasers who are interested in intelligent systems and artificial intelligence, with particular emphasis on applications. Typically they are degreed professionals, with backgrounds in engineering, hard science, or business. The publication emphasizes current practice and experience, together with promising new ideas that are likely to be used in the near future. Sample topic areas for feature articles include knowledge-based systems, intelligent software agents, natural-language processing, technologies for knowledge management, machine learning, data mining, adaptive and intelligent robotics, knowledge-intensive processing on the Web, and social issues relevant to intelligent systems. Also encouraged are application features, covering practice at one or more companies or laboratories; full-length product stories (which require refereeing by at least three reviewers); tutorials; surveys; and case studies. Often issues are theme-based and collect articles around a contemporary topic under the auspices of a Guest Editor working with the EIC.