Yea the hypothesis seems the exact opposite of what I find with LLM writing. It’s not that it’s overly dense instead I find that it’s hard to read because it’s so information sparse. Like you’re saying it feels optimized to “good writing” not to conveying information.
I find that it’s both: filled to the brim with facts and numbers, but they’re completely useless and irrelevant. For instance I ask it to come up with some ad copy for an Unreal UI plugin I made and it focuses on things like “Supports 64-bit Windows” or “allows transparent rendering” or lists out-of-context performance numbers.
Of course it supports 64-bit Windows - every Unreal plugin does! They don’t even make 32-bit Windows anymore!
Yeah; whatever the AIs are doing I wouldn't call it "information dense" like the abstract does. I'd prefer the hypothesis that there are complex patterns in speech related to successfully communication information to a limited human brain and the AIs aren't complex enough to model them yet. Or the signal is being obscured somehow.
I'd go with "high entropy", since the text maintains the same elevated level of density all across it, regardless of the level of importance.
They're picking among most likely tokens, which are ones with least entropy and so least information per token.