Challenges and limitations of ChatGPT and other large language models

Abstract

This article explores the challenges and limitations of large language models, focusing on ChatGPT as a representative example. We begin by discussing the potential benefits of large language models, such as their ability to generate natural language text and assist with language-related tasks. However, we also acknowledge the concerns around these models, including their environmental impact, potential for bias, and lack of interpretability. We then delve into specific challenges faced by ChatGPT and similar models, including limitations in their understanding of context, difficulty in handling rare or out-of-vocabulary words, and their tendency to generate nonsensical or offensive text. We conclude with recommendations for future research and development, including the need for increased transparency, interpretability, and ethical considerations in the creation and deployment of large language models.

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