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It's more complex than that, they are trained to model their language and understanding of a concept to match the author. There is not enough memory in the netw
by tinco 3y ago
It's more complex than that, they are trained to model their language and understanding of a concept to match the author. There is not enough memory in the network to remember the actual text.
It's like giving a talented an artist a day with a painting, and then a day later ask them to precisely copy the painting from memory. Would they come close enough for it to be considered a forgery, or will it be a transformative reinterpretation? It will probably depend on the skill of the artist, and I feel it might go either way.
- bugglebeetle 3y agoWhether a human artist can do this is largely irrelevant to the question of copyright, however. Selling a close copy of another artists’ work (unless they’re long dead) would likely be infringement.
- underlipton 3y agoI think the distinction is that you don't arrest someone for merely having the capability of reproducing a work, but after they've reproduced it and attempted to use it in an infringing manner. I don't know how applicable the analogy is given that LLMs don't "think", of course.
- torginus 3y agoyou might say that, but the literal benchmark of LLMs (or any supervised learning algorithm for that matter) is loss, or how much 'distance' is between their output, and the validation set, when seeded with the training set. With a loss of well below 1%, which is typical, it means it can pretty much recreate the training data.
- tinco 3y agoI've not seen that number before, what paper is that where there's a loss of less than 1% on the validation/test set?