One use-case: They help with learning things quickly by having a chat and asking questions. And they never get tired or emotional. Tutoring 24/7.
They also generate small code or scripts, as well as automate small things, when you're not sure how, but you know there's a way. You need to ensure you have a way to verify the results.
They do language tasks like grammar-fixing, perfect translation, etc.
They're 100 times easier and faster than search engines, if you limit your uses to that.
They can't help you learn what they don't know themselves.
I'm trying to use them to read historical handwritten documents in old Norwegian (Danish, pretty much). Not only do they not handle the German-style handwriting, but what they spit out looks like the sort of thing GPT-2 would spit out if you asked it to write Norwegian (only slightly better than Swedish Muppet Swedish Chef's Swedish). It seems the experimental tuning has made it worse at the task I most desperately want to use it for.
And when you think about it, how could it not overfit in some sense, when trained on its own output? No new information is coming in, so it pretty much has to get worse at something to get better at all the benchmarks.
Hah, no. They're good, but they definitely make stuff up when the context gets too long. Always check their output, just the same as you already note they need for small code and scripts.
They also generate small code or scripts, as well as automate small things, when you're not sure how, but you know there's a way. You need to ensure you have a way to verify the results.
They do language tasks like grammar-fixing, perfect translation, etc.
They're 100 times easier and faster than search engines, if you limit your uses to that.