Yes, marks of AI all over the place. Also the SVGs.

>No solution written, 100% score.

Its weird. Turns out that hardest problem for LLMs to really tackle is long-form text.

Maybe in one shot.

In theory I would expect them to be able to ingest the corpus of the new yorker and turn it into a template with sub-templates, and then be able to rehydrate those templates.

The harder part seems to be synthesizing new connection from two adjacent ideas. They like to take x and y and create x+y instead of x+y+z.

Most of the good major models are already very capable of changing their writing style.

Just give them the right writing prompt. "You are a writer for the Economist, you need to write in the house style, following the house style rules, writing for print, with no emoji .." etc etc.

The large models have already ingested plenty of New Yorker, NYT, The Times, FT, The Economist etc articles, you just need to get them away from their system prompt quirks.

I think that should be true, but doesn't hold up in practice.

I work with a good editor from a respected political outlet. I've tried hard to get current models to match his style: filling the context with previous stories, classic style guides and endless references to Strunk & White. The LLM always ends up writing something filtered through tropes, so I inevitably have to edit quite heavily, before my editor takes another pass.

It feels like LLMs have a layperson's view of writing and editing. They believe it's about tweaking sentence structure or switching in a synonym, rather than thinking hard about what you want to say, and what is worth saying.

I also don't think LLMs' writing capabilities have improved much over the last year or so, whereas coding has come on leaps and bounds. Given that good writing is a matter of taste which is beyond the direct expertise of most AI researchers (unlike coding), I doubt they'll improve much in the near future.

No, the failure is the human written prompt

You know, after a while this excuse is not valid anymore.

If they're that hard to prompt maybe it's easier just to write the blog posts yourself.

Someone here mentioned a whole ago that the labs deliberately haven't tried to train these characteristics out of their models, because leaving them in makes it easier to identify, and therefore exclude, LLM-generated text from their training corpus.

But it's odd that these characteristics are the same across models from different labs. I find it hard to believe that researchers across competing companies are coordinating on something like that.

I wonder what college freshman-level writing classes are teaching about writing voice and AI. The tell-tale patterns are pretty frustrating to read.

Agreed. The premise is interesting but reading content like this is grating.

im actually getting so tilted that people can't just be forthcoming about when they used AI to write something. 99% of readme.mds i run into now on github piss me off. out of all the things people could cede to automation, they foolishly went and self-owned their ability to communicate. smfh.

if you've worked on something diligently and understand it and have novel insight to share, let's hear _your_ damn voice.

yeah I don't hate LLM docs if they're labeled as such. but if someone wants me to use their code or read their README.md they are going to have to make it sound like a human cared about writing it, and right now Claude can't do that

Writing is still an art, and AI will never be able to do it well like all other forms of art.

What exactly is making you shudder - the writing style, or the fact that AI was used at all? Because if it's the latter, just so you know, you're going to be shuddering for the rest of your life.

Yeah. We know. That's why it's so fucking awful.