[kimi]

I have a pet-peeve with this. As a non-native English speaker, I find it very useful to dictate multiple notes, in different languages, and have the LLM produce clear English prose out of it. The prose may be LLM-generated, but I edit it when needed to make sure that the contents is 100% mine.

It's like dictating to a typist like they did in the 60's - he will make sure that your letter looks professional and will fix your grammar, but you will sign the letter. This is totally different from LLM spam, the kind that inflates a sentence into a three-page article full of nothing.

So - is it a problem if the language reverts to a mean? that is the point of a shared language, right?

[mvdtnz]

It's not just the language that reverts to a mean, it's the knowledge embedded in the model. If you're interested in discussing niche topics with ChatGPT, the further the model collapses the less likely you are to get meaningful results from the "tail" - the areas of knowledge that fall at the far ends of the model's bell curve.

[kimi]

Actually, both will, as they are not separate within the LLM. The thing is, one is a style issue, the other content. You can express original ideas and still use a lot of em dashes, or produce slop with a lot of typos in it.