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by supriyo-biswas 871 days ago
In another adjacent thread, people are talking about the implications of a neural network conforming to the training data with some error margin with regards to copyright.

Many textbooks on information theory already call out the content-addressable nature of such networks[1], and they’re even used in applications like compression due to this purpose[2][3], and therefore it’s no surprise that the NYT prompting OpenAI models with a few paragraphs of their articles reproduced them nearly verbatim.

[1] https://www.inference.org.uk/itprnn/book.pdf

[2] https://bellard.org/nncp/

[3] https://pub.towardsai.net/stable-diffusion-based-image-compr...

1 comments

Yes! This is a consequence of empirical risk minimization via maximum likelihood estimation. To have a model not reproduce the density of data it trained on would be like trying to get a horse and buggy to work well at speed, "now just without the wheels this time". It would generally not necessarily go all that well, I think! :'D