用户对大型语言模型中的“代币”概念感到困惑和沮丧。他们质疑模型在接受了大量文献训练后，如何使用这些代币来生成输出。用户暗示，鉴于其训练数据，模型应该能够产生更连贯的短语，并使用双关语来表达他们的怀疑。 AI
排序理由 用户用非正式语言和双关语表达了对LLM代币经济学和输出质量的看法和困惑。
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用户质疑LLM的代币经济学和输出连贯性
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
- 用户用非正式语言和双关语表达了对LLM代币经济学和输出质量的看法和困惑。
- 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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所以你向这些模型的拥有者/运营者支付“代币”。这些模型使用“代币”来生成更多“代币”。或者这是如何运作的？他们偷了字面意义上的
So you pay "tokens" to the owners/operators of these models. These models use them "tokens" to produce more "tokens". Or how does this work? They stole literally ALL of humanity's literature ever and can't come up with coherent phrases? I am still not quite token (pun intended) w…