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Ok, but what if in the future I could guarantee that my generative model was not trained on the work I want to replicate. Like say X library is the only library in town for some task, but it has a restrictive license. Can I use a model that was guaranteed not trained on X to generate a new library Z that competes with X with a more permissive license? What if someone looks and finds a lot of similarities?
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This is what Adobe ostensibly is trying to do with their GenAI image model, Firefly.

https://en.wikipedia.org/wiki/Adobe_Firefly

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I wish you luck proving it wasn't trained on the original library or any work that infringed itself.
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I think there could be a market for "permissive/open models" in the future where a company specifically makes LLM models that are trained on a large corpus of public domain or permissively licensed text/code only and you can prove it by downloading the corpus yourself and reproducing the exact same model if desired. Proving that all MIT licensed code is non-infringing is probably impossible though at that point copyright law is meaningless because everyone would be in violation if you dig deep enough.
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