You haven't used them enough. Everytime an LLM reduces my search from 1min to 5s, the LLM pays.

Just summary features: save me 20min of reading a transcript, turn it into 20s. That's a huge enabler.

If 20 mins of informations can legitimately be condensed into 20 seconds, it sounds like the original wasn't worth reading in the first place. Could have skipped the llm entirely.

I upvoted you, because I think you have a valid point. The tone is unnecessarily aggressive though.

Effective and information-dense communication is really hard. That doesn't mean we should just accept the useless fluff surrounding the actual information and/or analysis. People could learn a lot from the Ignoble Prize ceremony's 24/7 presentation model.

Sadly, it seems we are heading towards a future where you may need an LLM to distill the relevant information out of a sea of noise.

Didn't intend for it to be aggressive, just concise. Spare me from the llm please :)

Think of the summary of a zoom call. Or of a chapter that you're not sure if you care to read or not.

Not all content is worth consuming, and not all content is dense.

If I had a recording of the zoom call I could generate a summary on demand with better tools than were available at the time the zoom call was made.

> it sounds like the original wasn't worth reading in the first place

But if that's the only place that contained the information you needed, then you have no choice.

There's a lot of material out there that is badly written, badly organized, badly presented. LLM's can be a godsend for extracting the information you actually need without wasting 20 minutes wading through the muck.

Yeah I can see that use case, I just wouldn't trust an LLM to decide "is this worth reading". May as well flip a coin.

Overviews aren’t code though. In code, for me, they don’t pass 80/20 tests well enough, sometimes even on simple cases. (You get 50-80% of an existing function/block with some important context prepended and a comment, let it write the rest and check if it succeeds). It doesn’t mean that LLMs are useless. Or that I am antillamist or a denier - I’m actually an enthusiast. But this specific claim I hear often and don’t find true. Maybe true for repetitive code in boring environments where typing and remembering formats/params over and over is the main issue. Not in actual code.

If I paste the actual non-trivial code, it starts deviating fast. And it isn’t too complex, it’s just less like “parallel sort two arrays” and more like “wait for an image on a screenshot by execing scrot (with no sound) repeatedly and passing the result to this detect-cv2.py script and use all matching options described in this ts type, get stdout json as in this ts type, and if there’s a match, wait for the specified anim timeout and test again to get the settled match coords after an animation finishes; throw after a total timeout”. Not a rocket science, pretty dumb shit, but right there they fall flat and start imagining things, heavily.

I guess it shines if you ask it to make an html form, but I couldn’t call that life-changing unless I had to make these damn forms all day.

My experience with overviews is that they are often subtly or not so subtly inaccurate. LLMs not understanding meaning or intent carries risk of misrepresentation.