So on point 1 I agree with you. I think point 2 is pretty iffy though. Unless there has been some recent legal proceeding that I am unaware of, point 2 isn't true.
Oh yeah, I'm not sure either are true legally as I'm not a lawyer - just my opinion.
The reasoning I follow for point 2 is:
That if a neural network is not derivative of its inputs, and given a sufficiently large gan, you could "launder" inputs into copy-write free outputs. That's also not been done as far as I know, but I know it's starting to be an issue in NLP.
The reasoning I follow for point 2 is: That if a neural network is not derivative of its inputs, and given a sufficiently large gan, you could "launder" inputs into copy-write free outputs. That's also not been done as far as I know, but I know it's starting to be an issue in NLP.