LLMs are modeling outputs, not replicating a process, as a result the output looks the same but it isn't made of the same stuff.
It is a plastic banana.
There is nothing inherently wrong with a plastic banana but as soon as you claim you can use it to solve world hunger people are going to be upset and it doesn't matter how much it looks right.
I might have agreed before I read the NY Case ChatGPT generated cases, but now having read that and to be frank legal documents produced by copying and pasting by people with no domain knowledge I can say, not it isn't the same thing at all, at least in this case.
Because the person understands what they are trying to do. Prompts don't replicate that.
Understanding, thinking and having a narrative of events matter and have a lot to do with what even someone blind to the issues chooses and frankly I didn't fully understand that until I saw.what happened when they didn't.
@Vrimj Excellent, I needed that image to brighten my mood.
Lets talk to a plastic banana.
It is "word complete while typing" with entire stolen books as the next letter.
@Vrimj this is why chain of thought prompting completely surprised researchers working on LLMs. It seemed like using chain of thought replicated a process, and it possibly does for very simple processes
Figuring out how to do bigger processes is the big question now
Having a conversation with my kindergartner about legal issues is sometimes really helpful too
I don't think it means that kindergartners should be a routine part of law practice or are a monetizable tool
@Vrimj @Techronic9876 and rubber duck debugging (what you're doing with your k-gartener) is work done by you, not the k-gartener
This also applies to "step by step" reasoning with spicy autocomplete
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