Debatable I would argue. It's definitely not 'just a statistical model's and I would argue that the compression into this space fixes potential issues differently than just statistics.

But I'm not a mathematics expert if this is the real official definition I'm fine with it. But are you though?

its a statistical term, a latent variable is one that is either known to exist, or believed to exist, and then estimated.

consider estimating the position of an object from noisy readings. One presumes that position to exist in some sense, and then one can estimate it by combining multiple measurements, increasing positioning resolution.

its any variable that is postulated or known to exist, and for which you run some fitting procedure

See this video

https://youtu.be/D8GOeCFFby4?si=AtqH6cmkOLvqKdr0

I'm disappointed that you had to add the 'metamagical' to your question tbh

It doesn't matter if ai is in a hype cycle or not it doesn't change how a technology works.

Check out the yt videos from 1blue3brown he explains LLMs quite well. .your first step is the word embedding this vector space represents the relationship between words. Father - grandfather. The vector which makes a father a grandfather is the same vector as mother to grandmother.

You the use these word vectors in the attention layer to create a n dimensional space aka latent space which basically reflects a 'world' the LLM walks through. This makes the 'magic' of LLMs.

Basically a form of compression by having higher dimensions reflecting kind a meaning.

Your brain does the same thing. It can't store pixels so when you go back to some childhood environment like your old room, you remember it in some efficient (brain efficient) way. Like the 'feeling' of it.

That's also the reason why an LLM is not just some statistical parrot.