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English(EN) I, reluctantly, began including LLM's into my coding workflow about a year ago. I felt gross about it but as the months went on I def could see gains in output,

工程师引用哈佛研究,质疑大语言模型在编码方面的生产力提升

一位软件工程师回顾了过去一年将大语言模型(LLM)融入其编码工作流程的经历,他最初有些不情愿,但最终看到了产出和开发速度的提升。然而,他发现大语言模型生成的代码通常需要大量修改,并且会削弱编程的创造性方面。工程师引用了哈佛大学和Jellyfish的数据,指出研究表明大语言模型并未带来生产力提升或减少员工数量,这引发了对经验较少用户所生产代码质量的担忧。 AI

影响 引发了对大语言模型在软件开发中实际生产力效益的质疑,可能影响其采纳策略。

排序理由 该条目是对大语言模型在编码中使用情况的个人反思和观点文章,引用了外部研究,但并未提出新的发现或主要发布。

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工程师引用哈佛研究,质疑大语言模型在编码方面的生产力提升

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该条目是对大语言模型在编码中使用情况的个人反思和观点文章,引用了外部研究,但并未提出新的发现或主要发布。
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  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    大约一年前,我开始不情愿地将LLM纳入我的编码工作流程。我对此感到不适,但随着时间的推移,我确实看到了产出的提升,

    I, reluctantly, began including LLM's into my coding workflow about a year ago. I felt gross about it but as the months went on I def could see gains in output, speed of development, etc. However I learned quickly that LLM code is half shit and so I often would write patterns fir…