Avram Piltch is the editor in chief of Tom’s Hardware, and he’s written a thoroughly researched article breaking down the promises and failures of LLM AIs.
Avram Piltch is the editor in chief of Tom’s Hardware, and he’s written a thoroughly researched article breaking down the promises and failures of LLM AIs.
Every human work isn’t mechanically derivative. The entire point of the article is that the way LLMs learn and create derivative text isn’t equivalent to the way humans do the same thing.
It’s complete and utter nonsense and they’re bad people for writing it. The complexity of the AI does not matter and if it did, they’re setting themselves up to lose again in the very near future when companies make shit arbitrarily complex to meet their unhinged fake definitions.
But none of it matters because literally no part of this in any way violates copyright law. Processing data is not and does not in any way resemble copyright infringement.
This issue is easily resolved. Create the AI that produces useful output without using copyrighted works, and we don’t have a problem.
If you take the copyrighted work out of the input training set, and the algorithm can no longer produce the output, then I’m confident saying that the output was derived from the inputs.
There is literally not one single piece of art that is not derived from prior art in the past thousand years. There is no theoretical possibility for any human exposed to human culture to make a work that is not derived from prior work. It can’t be done.
Derivative work is not copyright infringement. Straight up copying someone else’s work directly and distributing that is.
This is false. Somebody who looks at a landscape, for example, and renders that scene in visual media is not deriving anything important from prior art. Taking a video of a cat is an original creation. This kind of creation happens every day.
Their output may seem similar to prior art, perhaps their methods were developed previously. But the inputs are original and clean. They’re not using some existing art as the sole inputs.
AI only uses existing art as sole inputs. This is a crucial distinction. I would have no problem at all with AI that worked exclusively from verified public domain/copyright not enforced and original inputs, although I don’t know if I’d consider the outputs themselves to be copyrightable (as that is a right attached to a human author).
And that’s what the training set is. Verbatim copies, often including copyrighted works.
That’s ultimately the question that we’re faced with. If there is no useful output without the copyrighted inputs, how can the output be non-infringing? Copyright defines transformative work as the product of human creativity, so we have to make some decisions about AI.
If they’ve seen prior art, yes, they are. It’s literally not possible to be exposed to the history of art and not have everything you output be derivative in some manner.
Processing and learning from copyrighted material is not restricted by current copyright law in any way. It cannot be infringement, and shouldn’t be able to be infringement.
I respectfully disagree. You may learn methods from prior art, but there are plenty of ways to insure that content is generated only from new information. If you mean to argue that a rendering of landscape that a human is actually looking at is meaningfully derivative of someone else’s art, then I think you need to make a more compelling argument than “it just is”.
Seeing how other pictures are framed is exactly identical to seeing how other stories are written.
The person who painted that landscape has certainly been influenced by prior artists, is not the first person to have painted a landscape, and is creating a work directly derivative of nature itself. They didn’t appear from thin air a fully-formed human being and start painting the hills. The person filming a cat video has seen videos before. They know to hold their phone at a certain angle and in a certain orientation to get the view they want of the cat, and that also does not spring from a vacuum. These two artists are each the sum total of their own experiences, their training sets. The difference between inference and extrapolation in this context is only a matter of complexity.