> 2) basically outright outlaw training of interesting ML models. Saying that it’s infringement doesn’t mean we’re outlawing interesting ML. These definitely a

> 2) basically outright outlaw training of interesting ML models. Saying that it’s infringement doesn’t mean we’re outlawing interesting ML. These definitely aren’t the only two options. A few years ago, this kind of infringement wasn’t even possible, and now it’s just beginning. This stuff is in its infancy. Reliability and controllability is an issue our field has to confront as applications move from research to application. This is just another instance of that. We’re all eager to deploy this stuff as soon as it can do something cool, but that’s not enough, as all the discussion around copilot demonstrates. > I think we shouldn't forget why copyright exists in the first place… To promote the Progress of Science and useful Arts Right. It’s to encourage creators to create things. I wrote about this elsewhere [0] that the issue of generative ML models is that, as far as incentives go, you can pay a creator for use of their things, or you can throw money at AWS and get use of something like that creator’s things. The fair use equation is ‘$$$ + my stuff = your stuff,’ except that that money doesn’t go to the creators, it goes to nvidia and aws. I think we’ll need new copyright laws for this, to make a middle ground. I personally want to be able to exclude my works from being training data unless I license then openly enough. Just like with open code licenses where you opt in. That option doesn’t seem to exist right now. Wouldn’t it be great if a model benefiting from all this public data had to be public itself, or something along those lines? Wouldn’t that promote the arts and sciences even more? [0] https://news.ycombinator.com/item?id=27778042 https://news.ycombinator.com/item?id=27778042