Ultimately what convinced me to proceed is that there are immense forces pressuring ML models to become SaaS companies. It's very difficult to offer an ML model for extended periods without being a company. E.g. https://6b.eleuther.ai/ is down. Eleuther failing illustrates just how hard it is –– we were all working as hard as we could to design something that would last a long time, and a long time turned out to be two short years. Contrast that with other kinds of hacking (e.g. webdev, gamedev, hardware...) where the end result lasts basically forever.
So if ML models aren't copyrightable, I think it'll hurt companies a lot more than individuals. In fact the goal is the other way around: to protect individuals. All I did was publish Facebook's own GPL download script to github, and it got DMCA'd. If we don't push back on that kind of behavior now, companies will get used to the idea that they control "their" model –– even when their model is anything but theirs.
- Grammarly. Clear value prop, if weights can't be adequately protected then that's a significant headwind against doing processing on the client.
- Adobe Firefly. Could run locally, they understand the technical challenges well, same headwind.
- GitHub Copilot. Same.
Copyright protection is probably not a single deciding issue in their product strategy but all of those are use cases that would for most users be better run locally as hardware can support that and are not going to because it's too much of a risk. Better to limit distribution and protect as trade secret.
The most powerful force for openness I see has nothing to do with copyright eligibility and everything to do with companies wanting to showcase their research arms to build brand and support recruiting. That leads me to believe it's probably better for models to be eligible for copyright and considered derivatives of all of the constituent training data. In some ways the better parallel is sampling in the music industry. It'll be interesting to see how this plays out.
I think it would be a shame to try to build legislation around the notion of the sass melting pot application of machine learning and in the process destroy all sorts of other use cases.
No, because we already do not treat all work as copyrightable. A plumber doesn't get copyright on his piping job. It has to be original enough. So while your own skill might be original enough to warrant copyright, distilling it into a model might not.
Yes. So it's like creating a machine that can create art.
Perhaps it shouldn't be copyrightable, but patentable. I think I would be OK with ML models (weights) being patentable rather than copyrightable.