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You can understand his biography and analyses about how shakespeare might have written. You can apply this knowledge to modify your writing process.

The LLM does not model text at this meta-level. It can only use those texts as examples, it cannot apply what is written there to it's generation process.

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no it does and what you said is easily falsifiable.

can you provide a _single_ example where LLM might fail? lets test this now.


Yes, what I said should be falsifiable. The burden is on you to give me an example, but I can give you an idea.

You need to show me an LLM applying writing techniques do not have examples in its corpus.

You would have to use some relatively unknown author, I can suggest Iida Turpeinen. There will be interviews of her describing her writing technique, but no examples that aren't from Elolliset (Beasts of the sea).

Find an interview where Turpeinen describes her method for writing Beasts of the Sea, e.g.: https://suffolkcommunitylibraries.co.uk/meet-the-author-iida...

Now ask it to produce a short story about a topic unrelated to Beasts of the Sea, let's say a book about the moonlanding.

A human doing this exercise will produce a text with the same feel as Beasts of the Sea, but an LLM-produced text will have nothing in common with it.


>You need to show me an LLM applying writing techniques do not have examples in its corpus.

why are you bringing this constraint?


Because the entire point is the LLM cannot understand text about text.

If someone has already done the work of giving an example of how to produce text according to a process, we have no way of knowing if the LLM has followed the process or copied the existing example.

And my point of course is that copying examples is the only way that LLMs can produce text. If you use an author who has been so analyzed to death that there are hundreds of examples of how to write like them, say, Hemingway, then that would not prove anything, because the LLM will just copy some existing "exercise in writing like Hemingway".


>Because the entire point is the LLM cannot understand text about text.

you have asked for an LLM to read a single interview and produce text that sounds similar to the author based on the techniques on that single interview.

https://claude.ai/share/cec7b1e5-0213-4548-887f-c31653a6ad67 here is the attempt. i don't think i could have done much better.


There is no actual short story behind the link? moon_landing_turpeinen.md cannot be opened.

You could not have done better? Love it. You didn't even bother rewriting my post before pasting it into the box. The post isn't addressed as a prompt, it's my giving you the requirements of what to prompt.

Also, because you did that, you've actually provided evidence for my argument: notice that my attitudes about LLMs are reflected in the LLM output. E.g.:

  "Now — the honest problem the challenge identifies: I'm reconstructing a description of a style, not internalizing the rhythm and texture of actual prose. A human who's read the book would have absorbed cadences, sentence lengths, paragraph structures, the specific ratio of concrete detail to abstraction — all the things that live below the level of "technique described in interviews.""

That's precisely because it can't separate metatext from text. It's just copying the vibe of what I'm saying, instead of understanding the message behind the text and trying to apply it. It also hallucinates somewhat here, because it's argument is about humans absorbing the text rather than the metatext. But that's also to be expected from a syntax-level tool like an LLM.

The end result is... nothing. You failed the task and you ended up supporting my point. But I appreciate that you took the time to do this experiment.


my bad, apprently claude doesn't share the Md. here it is https://pastebin.com/LPW6QsLE

> "Now — the honest problem the challenge identifies: I'm reconstructing a description of a style, not internalizing the rhythm and texture of actual prose. A human who's read the book would have absorbed cadences, sentence lengths, paragraph structures, the specific ratio of concrete detail to abstraction — all the things that live below the level of "technique described in interviews.

a human would have to read all the text, so would an LLM but you have not allowed this from your previous constraint. then allow an LLM to reproduce something that is in its training set?

why do you expect an LLM to achieve something that even a human can't do?




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