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arXiv:2302.03494cs.CL

A Categorical Archive of ChatGPT Failures

Ali Borji

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

Large language models have been demonstrated to be valuable in different fields. ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation by comprehending context and generating appropriate responses. It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries, with fluent and comprehensive answers surpassing prior public chatbots in both security and usefulness. However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study. Eleven categories of failures, including reasoning, factual errors, math, coding, and bias, are presented and discussed. The risks, limitations, and societal implications of ChatGPT are also highlighted. The goal of this study is to assist researchers and developers in enhancing future language models and chatbots.

arXiv comments
Journal reference
DOI
Subjects
cs.CLComputation and Language cs.AIArtificial Intelligence cs.LGMachine Learning

On Hacker News

Linked by 1 identifiable commenter in 2 comments across 2 threads, from Mar 2023 to Mar 2023. Found in 1 HN submission from Feb 2023 to Feb 2023. Open submission discussions.

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Discussed in comments2 threads

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      13yearsView on HNParent context

  2. ChatGPT and the AI Apocalypse 1 comment

    • I think it is exposing how naïve it will be to go full speed into full AGI. I personally think AGI Safety in the context of AGI is an oxymoron. Primitive AI is already beyond what we can manage. “The size and complexity of deep learning models, particularly language models, have…

      13yearsView on HNParent context

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