Right. LLMs are text production machines.

You can also view them as data expansion tools. They expand an input to an arbitrary long text. That text contains roughly the same amount of information as was contained in the input to begin with.

This is not very useful unless your work is content production. More useful is when the output length is shorter than the input. Then it is a (lossy) data compression tool. These are, as we all know, very useful for images and sound but now we have them for text too.

This assumes one-shot generation. I don't use it that way, and I don't think many people who find it useful do.

I use it as a colleague I'm drafting with. I'll ask how a sentence lands, tell it to make a paragraph more friendly or more dramatic, have it argue against a point I'm making. The piece comes together over many turns, and the information arriving in each turn is mine — it's not expanding one prompt, it's helping me converge on something.

The information-content framing also proves too much: a copy editor adds no information either. Neither does a translator, or a ghostwriter. What they add is form, and form is most of what makes writing good or bad.

I agree that the output is more likely to be valuable when it’s shorter than the input. And when they use tools to do research and try things, it can be a lot of input that comes from all sorts of places.

I really hate the whole thing about companies promoting using LLMs to change one-liner emails into this long multi-paragraph thing that ends up saying almost nothing ... just wasting everyone's time in reading them (with an extra sprinkling of hallucinations).

>Right. LLMs are text production machines.

I use them as text consumption machines. They read and watch a lot of the books and movies i have no time to. And from the TLDR I decide whether the full thing is worth watching.