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Ironically, this almost makes it more human. It's a surprisingly common experience for music students to excitedly tell everyone they know about a new piece of
by adrianmonk 4y ago
Ironically, this almost makes it more human.
It's a surprisingly common experience for music students to excitedly tell everyone they know about a new piece of music they've been composing, saying it is probably the best thing they've ever written, and then a friend or teacher has to say, "I don't know how to break it to you, but you've 'composed' the Xth movement of Beethoven's Yth symphony."
And sometimes they will say, "I have? I don't think I've ever heard Beethoven's Yth symphony." But of course they have, just without realizing it. It was in the background of some movie they watched or something like that.
Unlike humans, I don't think AIs have any belief about whether their work is original or not, but it's the same type of error. And with similar legal consequences: people have been sued for stealing a melody (presumably not always consciously). The difference with AIs is they can produce much more output than humans, and it's muddier what is actually doing the creating (AI authors? users?).
- unixlikeposting 4y ago>Ironically, this almost makes it more human. not really, no. It's more the case that a NN is an encoding of a large dataset space, and if you go far enough away from the average you may find yourself on an island with an individual outlier. This is why you simply get back the training example, it's regurgitating all that it was fed. For example, try to train a model using a single image, with a space as wide as a sole point you will find that all you get back is that point. A human being re-inventing without remembering the source is distinct from remembering the source and returning it when lacking other data.