G. Bharathi Mohan, R. Prasanna Kumar, P. Vishal Krishh, A. Keerthinathan, G. Lavanya, Meka Kavya Uma Meghana, Sheba Sulthana, Srinath Doss
{"title":"An analysis of large language models: their impact and potential applications","authors":"G. Bharathi Mohan, R. Prasanna Kumar, P. Vishal Krishh, A. Keerthinathan, G. Lavanya, Meka Kavya Uma Meghana, Sheba Sulthana, Srinath Doss","doi":"10.1007/s10115-024-02120-8","DOIUrl":null,"url":null,"abstract":"<p>Large language models (LLMs) have transformed the interpretation and creation of human language in the rapidly developing field of computerized language processing. These models, which are based on deep learning techniques like transformer architectures, have been painstakingly trained on massive text datasets. This study paper takes an in-depth look into LLMs, including their architecture, historical evolution, and applications in education, healthcare, and finance sector. LLMs provide logical replies by interpreting complicated verbal patterns, making them beneficial in a variety of real-world scenarios. Their development and implementation, however, raise ethical concerns and have societal ramifications. Understanding the importance and limitations of LLMs is critical for guiding future research and ensuring the ethical use of their enormous potential. This survey exposes the influence of these models as they change, providing a roadmap for researchers, developers, and policymakers navigating the world of artificial intelligence and language processing.</p>","PeriodicalId":54749,"journal":{"name":"Knowledge and Information Systems","volume":"6 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Knowledge and Information Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10115-024-02120-8","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Large language models (LLMs) have transformed the interpretation and creation of human language in the rapidly developing field of computerized language processing. These models, which are based on deep learning techniques like transformer architectures, have been painstakingly trained on massive text datasets. This study paper takes an in-depth look into LLMs, including their architecture, historical evolution, and applications in education, healthcare, and finance sector. LLMs provide logical replies by interpreting complicated verbal patterns, making them beneficial in a variety of real-world scenarios. Their development and implementation, however, raise ethical concerns and have societal ramifications. Understanding the importance and limitations of LLMs is critical for guiding future research and ensuring the ethical use of their enormous potential. This survey exposes the influence of these models as they change, providing a roadmap for researchers, developers, and policymakers navigating the world of artificial intelligence and language processing.
期刊介绍:
Knowledge and Information Systems (KAIS) provides an international forum for researchers and professionals to share their knowledge and report new advances on all topics related to knowledge systems and advanced information systems. This monthly peer-reviewed archival journal publishes state-of-the-art research reports on emerging topics in KAIS, reviews of important techniques in related areas, and application papers of interest to a general readership.