Making Large Language Models More Reliable and Beneficial: Taking ChatGPT as a Case Study

Majeed, Abdul; Hwang, Seong Oun

doi:10.1109/MC.2023.3327028

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Making Large Language Models More Reliable and Beneficial: Taking ChatGPT as a Case Study

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초록

This article suggests practical ways to make large language models more reliable and beneficial by taking ChatGPT as a case study. Specifically, we describe ChatGPT's workflow and promised services and highlight the perils requiring the immediate attention of ChatGPT stakeholders.

키워드

Large language models; Reliability engineering; Chatbots; Artificial intelligence; Human factors; Open systems; Deep learning; Context awareness; Question answering (information retrieval); Market research; Technology forecasting; Modeling; Stakeholders

제목: Making Large Language Models More Reliable and Beneficial: Taking ChatGPT as a Case Study

저자: Majeed, Abdul; Hwang, Seong Oun

DOI: 10.1109/MC.2023.3327028

발행일: 2024-03

유형: Article

저널명: Computer

권: 57

호: 3

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