Screenshot of this question was making the rounds last week. But this article covers testing against all the well-known models out there.
Also includes outtakes on the ‘reasoning’ models.
Screenshot of this question was making the rounds last week. But this article covers testing against all the well-known models out there.
Also includes outtakes on the ‘reasoning’ models.
But natural language in service of what? If they can’t produce answers that are correct, what’s the point of using them? I can get wrong answers anywhere.
I’m not here defending the practical value of these models. I’m just explaining what they are and what they’re not.
As OP said, LLMs are really good at generating text that is fluid and looks natural to us. So if you want that kind of output, LLMs are the way to go.
Not all LLM prompts ask factual questions and not all of the generated answers need to be correct.
Are poems, songs, stories or movie scripts ‘correct’?
I’m totally against shoving LLMs everywhere, but they do have their uses. They are really good at this one thing.
It’s a valid point that they can produce natural language. The Turing Test has been a thing for awhile after all. But while the language sounds natural, can they create anything meaningful? Are the poems or stories they make worth anything? It’s not like humans don’t create shitty art, so I guess generating random soulless crap is similar to that.
The value of language produced by something that can’t understand the reason for language is an interesting question I suppose.