LLM boosters: This is trained with all of the text and code on the public internet!

People who can fucking think: So it's extremely low quality, then?

"The average of everything on github" isn't badass code, it's unfinished student projects that never worked.
We hear "all the text on the internet" and we might think "well, they've sure digitized a lot of classic books, that must be good, right?" but then we realize that all of the books are maybe like 1% of the data. Most of it is like facebook messenger breakup arguments and semi-literate emails.
Humans are relying on computers to correct their grammar when humans don't even agree on what proper English grammar is smdh
@sidereal
I was always taught that people make grammar so i was really surprised to see people ask the machine how to do grammar
@sidereal there's major differences within the same country (for instance between Southern and Northern England).

@sidereal

Even if it was just a bunch of literature I hate to tell the LLM-pilled folks but nobody goes to the bathroom in a novel, so 🤷‍♂️

@sidereal That's kind of the thing though. What the existentialists called "bad faith", the human social fallibility that Kafka was satirizing.
@sidereal Do they even tell us, what they put in our mashed potatoes? For food, that's mandatory.
@promovicz
Has anyone made analogies, yet, between large language models and Soylent Green?
@sidereal
@sidereal they've presumably pulled all the bad fanfic as well as the Epstein Files....
@Susan_calvin @sidereal LLMs follow Sturgeon's Law
@otfrom @sidereal Sturgeon's law allows for the possibility of some good material amidst the dross. I don't think it applies to LLMs.
@sidereal I've just realised that there must be Epstein Files fanfic. Whether LLM generated or not
@sidereal It's more like public comments on Facebook and birdchan and such, which even before "AI" slop were dominated by wetware-bot slop working in troll farms producing disinformation, fraudulent engagement metrics, etc. The automated slop is literally trained on manual slop.
@sidereal one could hope they apply different weighting factors to different sources
@JessTheUnstill @sidereal mostly they don't and it is a known issue in training.