对比四款AI编程助手，评估其代码生成能力与适用场景
Programming with AI: Evaluating ChatGPT, Gemini, AlphaCode, and GitHub Copilot for Programmers
- 对比ChatGPT、Gemini、AlphaCode和Copilot在多语言代码生成表现
- 各模型在Python/Java/C++任务中准确率差异显著，且存在语法错误率偏高问题
- 适合开发者选型参考，也提示需关注模型可靠性与伦理使用
现代软件开发日益依赖由大型语言模型（LLMs）驱动的人工智能。为评估当前主流编程助手的表现，本研究系统比较了ChatGPT、Gemini（Bard AI）、AlphaCode和GitHub Copilot在自然语言处理与代码生成任务中的表现，涵盖Java、Python和C++等编程语言。结果表明，尽管这些模型在语言理解与代码生成方面取得显著进展，但存在准确性不足、语法错误频发等问题，且不同模型在各语言上的表现差异明显。研究强调需进一步优化模型可靠性，并呼吁重视伦理开发实践，以充分释放AI在编程领域的潜力。该工作为开发者选型提供关键参考，也推动对快速演进的AI模型生态的深入讨论。
原文摘要 · Abstract (English)
Our everyday lives now heavily rely on artificial intelligence (AI) powered large language models (LLMs). Like regular users, programmers are also benefiting from the newest large language models. In response to the critical role that AI models play in modern software development, this study presents a thorough evaluation of leading programming assistants, including ChatGPT, Gemini(Bard AI), AlphaCode, and GitHub Copilot. The evaluation is based on tasks like natural language processing and code generation accuracy in different programming languages like Java, Python and C++. Based on the results, it has emphasized their strengths and weaknesses and the importance of further modifications to increase the reliability and accuracy of the latest popular models. Although these AI assistants illustrate a high level of progress in language understanding and code generation, along with ethical considerations and responsible usage, they provoke a necessity for discussion. With time, developing more refined AI technology is essential for achieving advanced solutions in various fields, especially with the knowledge of the feature intricacies of these models and their implications. This study offers a comparison of different LLMs and provides essential feedback on the rapidly changing area of AI models. It also emphasizes the need for ethical developmental practices to actualize AI models' full potential.
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