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English(EN) Gradient ascent is superior to generate-and-test in any domain in which you have even a heuristic gradient that is sometimes wrong. Why people working on softwa

卢德分子计算机科学家质疑AI代码生成方法

一位有机计算机科学家和自称的卢德分子Anthony认为,梯度上升是优于生成-测试的软件开发方法,尤其是在处理潜在有害结果时。他质疑在敏感软件领域依赖代码生成器和测试,认为这会丢弃可靠的梯度信息。这一观点凸显了对当前AI研究的健全性和其潜在社会影响的担忧。 AI

影响 引发了对当前AI代码生成技术在敏感软件开发中的可靠性和潜在危害的担忧。

排序理由 该集群包含一篇个人观点文章,表达了对AI开发方法的批判性观点。

在 Mastodon — mastodon.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

卢德分子计算机科学家质疑AI代码生成方法

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  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Gradient ascent is superior to generate-and-test in any domain in which you have even a heuristic gradient that is sometimes wrong. Why people working on softwa

    Gradient ascent is superior to generate-and-test in any domain in which you have even a heuristic gradient that is sometimes wrong. Why people working on software where something serious is at stake would throw out known gradient to use a code generator + testing is beyond my cap…