ChatGPT 在编码中的有效性:流行大型语言模型的比较分析

Digital Pub Date : 2024-01-08 DOI:10.3390/digital4010005
Carlos Eduardo Andino Coello, Mohammed Nazeh Alimam, Rand Kouatly
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引用次数: 0

摘要

本研究探讨了由 GPT-3.5 和 GPT-4 支持的流行 OpenAI 模型 ChatGPT 在编程任务中的有效性和效率,以了解其对编程和潜在软件开发的影响。为了衡量这些模型的性能,我们采用了一种定量方法,即使用最基本的 Python 问题(MBPP)数据集。除了对 GPT-3.5 和 GPT-4 进行直接评估外,还对人工智能领域其他流行的大型语言模型(特别是谷歌的 Bard 和 Anthropic 的 Claude)进行了比较分析,以衡量和比较它们在相同任务中的能力。结果凸显了 ChatGPT 模型在编程任务中的优势,为人工智能界,特别是开发人员和研究人员提供了宝贵的见解。随着人工智能的普及,这项研究将成为人工智能辅助编程领域的早期研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effectiveness of ChatGPT in Coding: A Comparative Analysis of Popular Large Language Models
This study explores the effectiveness and efficiency of the popular OpenAI model ChatGPT, powered by GPT-3.5 and GPT-4, in programming tasks to understand its impact on programming and potentially software development. To measure the performance of these models, a quantitative approach was employed using the Mostly Basic Python Problems (MBPP) dataset. In addition to the direct assessment of GPT-3.5 and GPT-4, a comparative analysis involving other popular large language models in the AI landscape, notably Google’s Bard and Anthropic’s Claude, was conducted to measure and compare their proficiency in the same tasks. The results highlight the strengths of ChatGPT models in programming tasks, offering valuable insights for the AI community, specifically for developers and researchers. As the popularity of artificial intelligence increases, this study serves as an early look into the field of AI-assisted programming.
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