English(EN) I do not trust the output of LLMs because they are bad sources. Just like I would not trust a "History of the Jewish People" written by a nazi. Sometimes, a sou

作者不信任大型语言模型的输出，认为其作为信息来源不可靠

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-29 01:59

作者对大型语言模型（LLMs）表示不信任，因为它们作为信息来源不可靠。他们将此比作不信任一个纳粹写的“犹太人历史”，强调过滤掉不可信来源是事实上的必要，而非人身攻击。核心论点是，无论主题或格式如何，LLM生成的输出都不可信。 AI

影响对LLM生成内容的可靠性表示怀疑，可能影响用户信任和采用。

排序理由某位实名人士的观点文章，表达了对LLM的看法。

在 Mastodon — fosstodon.org 阅读 →

观点

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

本文如何被排名

Signal score: 3 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Commentary; 某位实名人士的观点文章，表达了对LLM的看法。
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: opinion; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Breaking (< 6h); Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准。

报道来源 [1]

Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] · 2026-10-29 01:59

我不信任大型语言模型的输出，因为它们是糟糕的来源。就像我不会信任纳粹写的《犹太人历史》一样。有时，一个来源

I do not trust the output of LLMs because they are bad sources. Just like I would not trust a "History of the Jewish People" written by a nazi. Sometimes, a source is not trustworthy, and that is not "ad hominem," that's just a fact of properly filtering out bad sources. A source…

本文如何被排名

报道来源 [1]

我不信任大型语言模型的输出，因为它们是糟糕的来源。就像我不会信任纳粹写的《犹太人历史》一样。有时，一个来源

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