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Might be related to their fingerprinting of llm output they said earlier in the week.
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> if I was talking to a person who constantly used a phrase they liked I would notice it and it is possible I might get irritated by it

There are sociological reasons why this happens less with humans:

1. You cycle your dumb repetitive jokes with everyone you meet, so nobody hears it twice

2. Those who know you well will notice when you're just repeating ("dad jokes")

3. As a person's idiosyncrasies are beginning to wear on their social circles, they will be getting small clues to stop saying those things. Agents don't get these social between-the-lines cues to stop a certain behavior, they endlessly repeat. Perhaps between model version releases, frontier labs can harvest the web and ask "What Claudisms do people mention negatively?" but I don't think they do that yet.

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One reason is that one person’s idiosyncracies are limited in scope, but LLM-produced text is now everywhere. Also, filler words and mannerisms in speech we’re quite good at filtering out, but in written text the stand out much more.
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> I am curious why LLM writing has such an uncanny valley feel to it.

Because they are HEAVILY trained to give addictive responses.

They don't want to just answer your question. They want to sycophantically make you feel like a genius for being smart enough to use them.

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This makes some good intuitive sense, but to me the sycophancy feels like it is an emergent property of turning a next word predictor into a conversational chatbot whether or not it’s intentionally trained that way. Your prompt and its earlier responses is all it has in its context window, so of course it lends undue importance to everything you say. Does that seem like a contributing factor to you?
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This seems to be the load-bearing point that matters.
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It’s the repetitiveness of style, the attempt to make everything seem as impactful as possible, the use of short sentences (too much Hemingway in the training data?), and obvious patterns like “it’s not this, it’s that” and several others.

Real human writing doesn’t follow such strict rules. When the same small set of rules is applied over and over throughout a text, it becomes obviously strange and machine-like.

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Wikipedia's own "Signs of AI Writing" page distills it nicely:

    - The subject becomes simultaneously less specific and more exaggerated.
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