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I would say that it probably is. If you trained a network using illegal data (e.g. cp images) then not only did you have to have that data once, which is of course illegal, but the data itself is at least partially encoded in the network weights which I think should make it illegal.

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I guess you might be able to get around this if you train only on legal content and can interpolate into content that would be illegal if a real recording.

However, I'm not sure whether there are any other applications for this specific interpolation scenario that would lead to it being developed, as the effort required to make it work is likely much higher.

Having the model produce realistic interpolations through areas of the latent space that had no associated training data is surely something that people will be trying to make happen.

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