一位 Mastodon 用户对在网上分享的免费知识被大型语言模型 (LLM) 吸收表示担忧。该用户强调，网络最初是为知识共享而建立的，现在却被 LLM 利用，而原始知识创作者似乎并未从中获得补偿或益处。 AI
排序理由 来自社交媒体平台的单个条目，表达了对 LLM 的看法，而非主要事件来源。
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Mastodon 用户哀叹免费网络知识被 LLM 驱动
本文如何被排名
- Signal score
- 0 / 100
- Composite score across the factors below. Higher = stronger signal that this story matters right now.
- Newsworthiness bucket
- Meme
- 来自社交媒体平台的单个条目，表达了对 LLM 的看法，而非主要事件来源。
- 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, other
- Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
- AI-industry relevance
- Standard
- On-topic for AI-industry coverage; kept in the public index.
- 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]
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我们开始构建了一个用于分享知识的#网站，目前我们认识到所有这些免费知识都被吸收到#LLMs中
So we started with a # web that was built up for sharing # knowledge und currently we're apreciating that all this free knowledge is sucked up into # LLMs for which we pay a huge amount of money to have access back to this free knowledge. What kills all this decentral knowledge s…