Comment by Gormo
2 hours ago
> This is extremely false. Copyright additionally grants you exclusive control over the production and distribution of derivative works.
A derivative work is a work that itself includes copyrighted content from the original work.
That is to say that for something to be a derivative work, some measure of its content must be "CTRL-C, CTRL-V" from the originating work.
Something that's merely inspired by another work, or draws underlying themes or factual knowledge from it, is not a derivative work.
> A training set is just an anthology,
Which might make the training set itself a derivative work, but works created by using the model trained on that anthology are a different matter.
> and the training process is condensation.
No, it isn't. It's the creation of a new work that represents patterns extrapolated or interpolated from the data set, without the resulting model actually including any of the copyrighted elements of the work.
The underlying ideas and facts in the original work were never protected by copyright. Only the specific fixed form of expression is copyrightable.
Someone who looks at a dozen code examples in public repos to learn how to do e.g. a quick sort, then upon understanding the logic flow of the quick sort algorithm, writes his own quick sort implementation is not creating a derivative work of the code in the repos he exampled. And the way LLMs work is much more similar to that process than to the "compressed anthology" concept you're describing.
> A derivative work is a work that itself includes copyrighted content from the original work.
If you put a GPL C program through Emscripten to run in a browser the output doesn't include the original C code but it's surely a derivative work.
> Someone who looks at a dozen code examples in public repos to learn how to do e.g. a quick sort, then upon understanding the logic flow of the quick sort algorithm, writes his own quick sort implementation is not creating a derivative work of the code in the repos he exampled. And the way LLMs work is much more similar to that process than to the "compressed anthology" concept you're describing.
This is undoubtedly the core of the disagreement. Humans can learn from what they have seen, appreciate it, understand it, and draw on that experience in what they create. They do this without being considered ripoff artists, so why not machines that simulate the "same" thing automatically?
To me the answer is simply that humans are special. Human thought and human effort makes it creativity when a human does it, copying when a machine does it. It's a double standard I am perfectly willing to accept. I am unabashedly biased in this regard.
That may seem remarkably unfair to the machines, or like a cop-out. I just carved out a hardcoded special case for humans, and my whole philosophical reasoning is "because I said so". But how fair do we want to be? After all, if you want to treat a machine exactly like a human who learns from prior art to create new art, then the ownership of the new art would also belong to the machine. Not to the person who prompts it.