this post was submitted on 19 Nov 2023
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Nearly everything you wrote is incorrect.
As an example, rolling context windows paired with RAG would easily allow for building an implementation of LLMs capable of writing long stories.
And I'm not sure where you got the idea that they were fundamentally incapable of originality. This part in particular tells me you really don't know how the tech is working.
A rolling context window isn't a real solution and will not produce works that even come close to matching the quality of human writers. That's like having a writer who can only remember the last 100 pages they wrote.
The tech is trained on human created data. Are you suggesting LLMs are capable of creativity and imagination? Lmao - and you try to act like I'm the one who's full of shit.
That's why you pair it with RAG.
They are trained by iterating through network configurations until there's diminishing returns on how accurately they can complete that human created data.
But they don't just memorize the data. They develop the capabilities to extend it.
So yes, they absolutely are capable of generating original content that's not in the training set. As has been demonstrated over and over. From explaining jokes not found in the training data, solving riddles not found in it, or combining different concepts to result in a new synthesis not found in the original data.
What do you think it's doing? Copy/pasting or something?