{"title":"企业大型语言模型的兴起与设计","authors":"Daniel E. O’Leary","doi":"10.1109/mis.2023.3345591","DOIUrl":null,"url":null,"abstract":"This article investigates a new phenomenon of enterprise large language models (ELLMs) focusing on what they are, why they are being developed, and what are some key capabilities. In addition, the article drills down on issues associated with integrating retrieval augmented generation approaches into ELLMs, including emerging research issues.","PeriodicalId":13160,"journal":{"name":"IEEE Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":5.6000,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Rise and Design of Enterprise Large Language Models\",\"authors\":\"Daniel E. O’Leary\",\"doi\":\"10.1109/mis.2023.3345591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article investigates a new phenomenon of enterprise large language models (ELLMs) focusing on what they are, why they are being developed, and what are some key capabilities. In addition, the article drills down on issues associated with integrating retrieval augmented generation approaches into ELLMs, including emerging research issues.\",\"PeriodicalId\":13160,\"journal\":{\"name\":\"IEEE Intelligent Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2024-02-28\",\"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.2023.3345591\",\"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.2023.3345591","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}
The Rise and Design of Enterprise Large Language Models
This article investigates a new phenomenon of enterprise large language models (ELLMs) focusing on what they are, why they are being developed, and what are some key capabilities. In addition, the article drills down on issues associated with integrating retrieval augmented generation approaches into ELLMs, including emerging research issues.
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.
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