Got a lot of good answers here, thanks.

My (I'm sure not even a tiny bit novel) summary of playing with current gen LLM tools is that they're likely very useful in three main situations:

One is when your task is more synthetic/creative: writing a letter, generating ad copy or creating a game, story etc etc where you need some flow of interesting human concepts (written well where that matters). I haven't tried any image stuff only text but i guess it'll be very useful there too now, since it's getting better. To be clear, I'm only guessing about this use case. Maybe creative people will find it useless, but seems unlikely.

The other is where you're doing something and aren't yet expert: an example might be learning a foreign language at intermediate level; it'll be a great practice tool. Or very similarly, learning a computer language or framework but you're not fully comfortable in it yet. The problem is that when you are expert in a technical thing, especially a less common one, then the kinds of questions you have are too difficult, and it will confidently give you answers that are *very* likely to be flat out wrong.

The third is the "donkey work" case: imagine having an intern who just graduated and remembers *all* the basics and theory but doesn't know much about the gotchas of real life in your field. You can give them tasks that would take time but are not easy to screw up. For example, writing unit tests for code (it dies seem like they are *particularly* good at software, unsurprisingly). You might still need to review the work to double check it but you saved a bunch of your time. I guess this is going to be the *main* use case until/unless AI has another quantum leap.



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 For orgs, LLM tools/APIs can also be used to generate embeddings to use for semantic search (ranked by similarity) or "find me a similar image/doc, etc" or to group similar items.   

 Yeah quite right. Search is missing from that list and it's a big one. 

 The most useful task I've found for LLMs so far was actually to walk through some physics problems to figure out what math symbols are standard for those problems.

It got the physics problems subtlely wrong in annoying ways... But it was a much easier way to figure out what the standards are; that kind of knowledge is impossible to Google. 

 Huh, interesting one. It's kind of another language learning problem.