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A comment on Authors Seek Meta's Torrent Client Logs and Seeding Data in AI Piracy Probe. Parent comment

Re:Authors Seek Meta's Torrent Client Logs and Seeding Data ... by visarga on Monday January 20, 2025 @11:31PM (#42776640)
Alteratively if they trained the model on synthetic data, filtered to avoid duplication, then no copyrighted material would be seen by the model. For example turn an article into QA pairs, or summarize across multiple sources of text.
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Re:Authors Seek Meta's Torrent Client Logs and Seeding Data ... by thesz on Monday January 20, 2025 @11:47PM (#42776730) 

  > trained the model on synthetic data
You get knowledge collapse [1] this way.

[1] https://arxiv.org/abs/2404.03502

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Re:Authors Seek Meta's Torrent Client Logs and Seeding Data ... by ben_w on Tuesday January 21, 2025 @08:14AM (#42779746)
You can get knowledge collapse.

But based on how often people were already doing this with buggy human-written software[0][1] — and even though there are counter-examples (e.g. learning Go from self-play based only on the rules) — IMO most people don't think about this in the right way and will therefore treat these things as magical oracles when they shouldn't.

No silver bullets.

[0] https://en.wikipedia.org/wiki/British_Post_Office_scandal

[1] https://en.wikipedia.org/wiki/Computer_says_no

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