I often read as much as 1000 words thinking to myself: “this is smooth”, but then think to myself “Is this my friend Opus 4.8 or now Opus 5?.
In this case the rhetorical neatness is unmistakable especially in the beginnings and endings of paragraphs: “Here is the constructive turn, honestly ranked, with no silver bullets on offer.”
Yes: and that is actually a smoking gun.
reminds me of a Claude math paper:
"honestly sharp , no hype: cos(pi+pi)+2+2=cos(2pi)+4=1+4=5"
So why haven’t they? My theory is they see this as a sort of fingerprint, useful to not train on later. Or something. Maybe they just don’t care. Certainly feels either intentional or a result of ambivalence.
It’s certainly true today that I probably wouldn’t know an AI written article if the author went out of their way to use one of the many prompts available to tone down the AI-isms.
Maybe my understanding of LLMs is wrong, but it seems obvious to me that when you have a large corpus of LLM output you will eventually notice common tells when everyone is using the same models, weights, and base prompt.
This wiki page is updated frequently and only needs to be fed into an AI to remove its telltale writing.
I asked claude to take the above and rewrite it in it's own words and it came up with: "LLMs are essentially large-scale statistical regressors — they're built on huge volumes of text, so the rhetorical patterns, clichés, and memes (in the Dawkins sense of self-replicating cultural units) that saturate the training data show up in outputs at roughly the frequency they occur in that data.
The key limitation: a human writer naturally shifts register, tone, and style based on context — what they're writing, who it's for, the medium. An LLM doesn't really do that in the same way. Every academic paper, Buzzfeed listicle, and Reddit thread it was trained on bleeds into its output regardless of the actual writing task at hand, whereas a person adapts fluidly to the situation."
Even with the context, it still included an emdash, the rhetorical technique of threes, and "the key limitation". It's an inherent weakness of LLM's. There is no fixing it.
I think you are right that in a year or two LLMs will be able to do a good impression of many technical styles. But not Nabokov, Kundera, or Kafka for subtlety.
If one manages to channel Edsger W. Dijkstra I will be impressed and rank it high on my leaderboard.