Personally I think trained models are derived works of all the training data.
Just like a translation of a book is a derived works of the original. Or a binary compiled output is a derived works of some source code.
Just like a translation of a book is a derived works of the original. Or a binary compiled output is a derived works of some source code.
Translation of a book is non-transformative and retains the original author's artistic expression.
As a counter example - if you write an essay about Picasso's Guernica painting, it is derivative according to our colloquial use of the term, but legally it's an original work.
> In copyright law, a derivative work is an expressive creation that includes major copyrightable elements of ... the underlying work
A trained model fails that on two counts, doesn't it? Both the "includes" part, and the fact that a model is itself not an expressive work of authorship.
There's nothing creative about the act of a compiler, it is automatic, just like the training run of an LLM.
And no part of the original source code is in the binary output.
And yet, binaries are a derived work from the source code that went into them.
So something is up! I am not a lawyer though.
It's not about whether the binary includes the raw text of the source, but whether it copies the expressive content. Anything expressive (i.e. copyrightable) in a compiled binary must have come from the sourcecode, so that's what makes it a derived work.
But the same isn't true of LLMs, which are more like "data about their inputs", than "a transformed version of their inputs".