this post was submitted on 13 Sep 2023
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Avram Piltch is the editor in chief of Tom's Hardware, and he's written a thoroughly researched article breaking down the promises and failures of LLM AIs.

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[–] [email protected] 30 points 1 year ago* (last edited 1 year ago) (25 children)

Two things:

  1. Many of these LLMs -- perhaps all of them -- have been trained on datasets that include books that were absolutely NOT released into the public domain.

  2. Ethically, we would ask any author who parrots the work of others to provide citations to original references. That rarely happens with AI language models, and if they do provide citations, they often do it wrong.

[–] [email protected] 25 points 1 year ago (17 children)

I'm sick and tired of this "parrots the works of others" narrative. Here's a challenge for you: go to https://huggingface.co/chat/, input some prompt (for example, "Write a three paragraphs scene about Jason and Carol playing hide and seek with some other kids. Jason gets injured, and Carol has to help him."). And when you get the response, try to find the author that it "parroted". You won't be able to - because it wouldn't just reproduce someone else's already made scene. It'll mesh maaany things from all over the training data in such a way that none of them will be even remotely recognizable.

[–] [email protected] 17 points 1 year ago (14 children)

And yet, we know that the work is mechanically derivative.

[–] [email protected] 19 points 1 year ago* (last edited 1 year ago) (1 children)

So is your comment. And mine. What do you think our brains do? Magic?

edit: This may sound inflammatory but I mean no offense

[–] [email protected] 3 points 1 year ago

No, I get it. I'm not really arguing that what separates humans from machines is "libertarian free will" or some such.

But we can properly argue that LLM output is derivative because we know it's derivative, because we designed it. As humans, we have the privilege of recognizing transformative human creativity in our laws as a separate entity from derivative algorithmic output.

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