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Authors Are Furious After Finding Their Works on List of Books Used To Train AI (www.themarysue.com)
submitted 3 years ago by to c/technology@lemmy.world
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Authors using a new tool to search a list of 183,000 books used to train AI are furious to find their works on the list.

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[–] 32 points 3 years ago* (14 children)

That's an interesting take, I didn't know software could be inspired by other people's works. And here I thought software just did exactly as it's instructed to do. These are language models. They were given data to train those models. Did they pay for the data that they used to train for it, or did they scrub the internet and steal all these books along with everything everyone else has said?

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  • [–] 3 points 3 years ago (8 children)

    Well, now you know; software can be inspired by other people's works. That's what AIs are instructed to do during their training phase.

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  • [–] 0 points 3 years ago (3 children)

    Does that mean software can also be afraid, or angry? What about happy software? Saying software can be inspired is like saying a rock can feel pain.

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  • [–] 4 points 3 years ago* (1 child)

    Does that mean software can also be afraid, or angry?

    If it is programmed/trained that way, sure. I recommend having a listen to Geoffrey Hinton on the topic (41:50).

    Saying software can be inspired is like saying a rock can feel pain.

    The rock doesn't do anything similar to pain. The LLM on the other side does a lot of things similar to inspiration. I can give the LLM a very trivial question and it will answer with a mountain of text. Did my question or the books it was trained on "inspire" the LLM to write that? Maybe, depends of course how far reaching you want to define the word. But either way, the LLM produced something by itself, that was neither a copy of my prompt nor the training data.

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  • [–] -3 points 3 years ago

    Software can do a lot of things that rocks can't do, that's not a good analogy.

    Whether software can feel "pain" depends a lot on your definitions, but I think there are circumstances in which software can be said to feel pain. Simple worms can sense painful stimuli and react to it, a program can do the same thing.

    We've reached the point where the simplistic prejudices about artificial intelligence common in science fiction are no longer useful guidelines for talking about real artificial intelligence. Sci-fi writers have long assumed that AIs couldn't create art and now it turns out it's one of the things they're actually rather good at.

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  • [–] -3 points 3 years ago (3 children)

    Software cannot be “inspired”

    AIs in their training stages are simply just running extreme statistical analysis on the input material. They’re not “learning” they’re not “inspired” they’re not “understanding”

    The anthropomorphism of these models is a major problem. They are not human, they don’t learn like humans.

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  • [–] 3 points 3 years ago (2 children)

    The anthropomorphism of these models is a major problem.

    People attributing any kind of person hood or sentience is certainly a problem, the models are fundamentally not capable of that (no loops, no hidden thought). At least for now. However what you are doing isn't really much better, just utterly wrong in the opposite direction.

    Those models are very definitely do "learn" and "understand" by every definition of the word. Simply playing around with that will quickly show that and it's baffling that anybody would try to claim otherwise. Yes, there are limits to what they can understand and there are plenty things that they can't do, but the amount of questions they can answer goes far beyond what is directly in the training data. Heck, even the fact that they hallucinate is proof that they understand, since it would be impossible to make completely plausible, but incorrect, stuff up without having a deep understanding of the topics. Also humans make mistakes too and they'll also make stuff up, so this isn't even anything AI specific.

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  • [–] -3 points 3 years ago (1 child)

    Yeah, that’s just flat out wrong

    Hallucinations happen when there’s gaps in the training data and it’s just statistically picking what’s most likely to be next. It becomes incomprehensible when the model breaks down and doesn’t know where to go. However, the model doesn’t see a difference between hallucinating nonsense and a coherent sentence. They’re exactly the same to the model.

    The model does not learn or understand anything. It statistically knows what the next word is. It doesn’t need to have seen something before to know that. It doesn’t understand what it’s outputting, it’s just outputting a long string that is gibberish to it.

    I have formal training in AI and 90%+ of what I see people claiming AI can do is a complete misunderstanding of the tech.

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  • [–] 2 points 3 years ago* (last edited 3 years ago)

    I have formal training in AI

    Than why do you keep talking such bullshit? You sound like you never even tried ChatGPT.

    It statistically knows what the next word is.

    Yes, that's understanding. What do you think your brain does differently? Please define whatever weird definition you have of "understand".

    You are aware of Emergent World Representations? Or have a listen to what Ilya Sutskever has to say on the topic, one of the people behind GPT-4 and AlexNet.

    It doesn’t understand what it’s outputting, it’s just outputting a long string that is gibberish to it.

    Which is obviously nonsense, as I can ask it questions about its output. It can find mistakes in its own output and all that. It obviously understands what it is doing.

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  • [–] -2 points 3 years ago (2 children)

    They weren't given data. They were shown data then the company spent tens of millions of dollars on cpu time to do statistical analysis of the data shown.

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  • [+] -6 points 3 years ago (1 child)

    And here I thought software just did exactly as it’s instructed to do.

    AI isn't software. Everything the AI knows is from the books. There is no human instructing the AI what to do. All the human does is build the scaffolding to let the AI learn, everything else is in the data.

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