If you’re executing a NN algorithm in your mind, or via pen & paper, then you are copying from the training samples, because that’s what the algorithm does. During training you compute errors against the samples, and update your weights to reduce error. During inference or generation, you use the weights (the results you remembered across all your training data) to produce an output. When your training samples are clustered in the latent space, the network will only remember an average of the samples, but samples that are sparse and don’t have close neighbors are sometimes remembered verbatim because there’s nothing nearby to average from. You can legally run the algorithm all you want on your own. Once you run it and then distribute the output, it might be in violation of Copyright Law if you accidentally reproduced one of the samples. Same is true for traditional human learning, you can free copy ideas legally, but reproducing too closely something that someone else made may be against the law, even if it was accidental.