I think you could simulate something that passes a sniff test. A writer would probably spot implausibilities in the simulation if they paid attention, but then we're back to square one, because you can spot that something was written by an LLM after you've wasted your time reading it and realize that you've been led around in circles with superficial information and no coherent train of thought, but by then your time has already been wasted.

To add to this, one can’t ignore the relationship between signal and receiver. I’d imagine most people on HN have enough pre-LLM reading experience to have a decent sense of what was written by an LLM versus a human.

And as LLMs get better at producing human-like text, that same pre-LLM reading experience, which helps people tell the two apart, will become less and less common.

> You have no idea how many false positives and how many false negatives you have in your judgement.

The default LLM style is pretty deterministic. "Not X, Not Y. Just Z", etc.

There are phrases and cadences which are very rare in human prose (<5%) but unusually common (+95% occurrences in LLM prose). It is not unreasonable to look at content which is 95% LLM tells and conclude that that an LLM authored it.

I have noted, IRL, that those people who read very little, and only read when they have to (work docs, etc) are literally unable to tell that a piece of prose sounds like an LLM even when it has about 12 occurrences of "Not X. Just Y" or "Not X, Not Y. Just Z" in as many paragraphs.

I don't think I'm special. I think many people can tell the difference.

Edit: Also, I'm surprised images have gotten to the point where I have a hard time detecting AI in some cases, and they got there more quickly than prose. I really thought prose would be the first to fall. Video is still detectable. Music still detectable (by someone that enjoys music and pays attention to it). But, AI prose still outs itself pretty quickly.

Doubtful. I read a lot of forum posts, as I maintain a popular OSS project. And, I read a lot of books from the before times. And, I read a lot of LLM prose, because I use them every day for coding and various assistant type tasks. It's still pretty obvious when an LLM writes something.

I even did post-training on Gemma 4 (a small model which has very good prose for a model, especially a small model) to try to make it able to write more like me, purely as an experiment to learn how training LoRAs works, and using data that I know is ethically sourced. It still distinctly writes like an LLM, with a few of my annoying quirks baked in: Inappropriate use of ellipses, too many parentheticals, occasionally dismissive tone. But, it can't stop doing the LLM things, either, without becoming incoherent.