Not really. It was invented because they were trained on natural language corpuses. It wasn't a deep, philosophical concept.
It continues to be used for models that are doing completely non-languagy stuff, such as robotics, although I expect the growing use of 'foundation model' or some other less-confusing term will likely replace it.
If it wasn't, what would we be doing here?
To some extent, those are kind of the same thing.
They are not the same thing. They are not even "kind of" the same thing, for any reasonable definition of "kind of." That should be obvious, because a lie is language, which is pretty close to the opposite of knowledge.
I mean no offense, but your hedging words are doing so much work that I think your statement counts as bullshit.
Edit: thinking about it more, I think your comment shows the particular kind of bullshit that often characterizes tech people's thinking and is so useful for hyping shit (e.g. take something hard, lossily reformulate it into something easier but vaguely similar, solve the easy thing, then declare you solved the hard thing).
Knowledge is... concepts and their relationships, typically with the implication of being grounded in objective reality (although one can be knowledgeable about things like, say, Tolkien, or Star Wars, or fantasy tropes more generally).
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Language is (a particular way of representing) knowledge, in about the same way that a particular .cpp file is (a particular way of representing) a linked list or whatever.
So, in your view, are .cpp files and linked lists "kind of" the same thing?
Language can be used to express some kinds of knowledge, but they're not even "kind of" synonymous. Language can express a lot of things that aren't knowledge, and there's knowledge that can't be expressed with language (qualia, at least).
All the more and less formal models we invent for describing "language"? This is just fitting curves to a snapshot of reality. So sure, "a lie is language, which is pretty close to the opposite of knowledge" - a lie can be expressed in the formal model. But the truth (as subjectively understood) is much more likely to be spoken or written down in practice.
Communication isn't random. Language isn't random. Learning it is picking up the patterns.
>>>> But it does mean they're about "language" rather than knowledge.
>>> To some extent, those are kind of the same thing.
>> They are not the same thing.
> Of course they are the same thing.
Language and knowledge (both broadly construed) are obviously not the same thing. Language can encode non-knowledge like nonsense or lies, and there is knowledge (e.g. of the experience of qualia) that can't be expressed in language.
I think the point up-thread is true: something that knows only about how language is unreliable source of knowledge. Even if all its input is true knowledge, it can still blindly combine that input in linguistically plausible but false ways.
you can use language as a proxy for knowledge in some cases, but doing so guarantees generating bullshit, which is the entire point of the OP.
it does mean they're about "language" rather than knowledge
Correct. But it does mean they're about "language" rather than knowledge. It's meant to read, parse and generate language, no matter if it includes prose, facts, knowledge or whatever.
> Clearly, they aren't as likely to generate "Colorless green ideas sleep furiously" as "It's important to feed your dog".
Clearly, as the training set probably contains much more instances of the latter, than the first example. And if it's more probable to generate, that's the text it'll generate. It doesn't understand why or how, just that it's more likely, so that's the way it's going.