Yeah, haikus are 17 japanese mora, and so if it doesn't come from the mora region of japan it's not a true haiku, it's just a short poem.
> I imagine that folks would typically want some correctness guarantees
Us programmers really value correctness, but the real world doesn't actually care about it in quite a few cases. In the real world, most data comes from humans, and humans make mistakes all the time, so basically any data might have some amount of error. There's a high tolerance for a few minor mistakes here and there.
In the real world, tasks are often given to interns, and they make small mistakes all the time, but it mostly ends up being okay. If AI manages to do the same, well, that's a huge swath of tasks it can do.
> I can't think of many tasks that can be done consistently well by AI that can't also be done with simpler software
Here's the thing though: "simpler software" probably isn't actually cheaper, available, or usable. It's probably not simpler to operate since, you know, english is simpler than any DSL us programmers have come up with until now.
This sort of stuff is fuzzy, even without AI. In many ways it’s about exploring the knowledge space rather than seeking specific answers. None of this requires correctness because there are no correct answers to begin with.
Even in computing, correctness is not always important. I recently asked GPT to produce a bunch of names from the Austin Powers universe in order to populate a demo database. I asked for them in JSON format and in 20 seconds I had what I needed. There is no wrong answer for that, either.
Interestingly (for me anyway) we got GPT to write the initial prompts for Midjourney.
I've dabbled in comms work, and it's very useful for that. One thing that I despise doing is writing copy and LLMs are really good for that - writing dozens of social media posts is tedious and LLMs can rephrase things so that they sound less repetitive. I'm a good writer but I'm an amazing editor so having something to start with also solves the 'staring at a blank page/doc' problem.
Likewise, generating polite answers to stupid questions. Instead of worrying 'how do I tell an ego-driven exec/politician/candidate that what they want is stupid or not possible?' I can have an LLM spit out the stupid corporate drivel the C-Suite all want from their servants. It's also good for dumbing things down but not making it sound like you're dumbing things down and therefore is good for rewriting information for different audiences.
You don't (right now) use LLMs for generating facts but they have a great deal of utility in massaging language.
As a non-business person, I imagine that folks would typically want some correctness guarantees, which seem near-impossible with today's LLMs. What kind of business use-cases do they enable? Probably a failure of imagination on my part, but I can't think of many tasks that can be done consistently well by AI that can't also be done with simpler software.