this post was submitted on 22 Aug 2023
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OpenAI now tries to hide that ChatGPT was trained on copyrighted books, including J.K. Rowling's Harry Potter series::A new research paper laid out ways in which AI developers should try and avoid showing LLMs have been trained on copyrighted material.

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[–] Tyler_Zoro@ttrpg.network 25 points 1 year ago (12 children)

AI/LLMs can train on whatever they want but when then these LLMs are used for commercial reasons to make money, an argument can be made that the copyrighted material has been used in a money making endeavour.

And does this apply equally to all artists who have seen any of my work? Can I start charging all artists born after 1990, for training their neural networks on my work?

Learning is not and has never been considered a financial transaction.

[–] zbyte64@lemmy.blahaj.zone 2 points 1 year ago (5 children)

Ehh, "learning" is doing a lot of lifting. These models "learn" in a way that is foreign to most artists. And that's ignoring the fact the humans are not capital. When we learn we aren't building a form a capital; when models learn they are only building a form of capital.

[–] Tyler_Zoro@ttrpg.network 3 points 1 year ago (2 children)

Artists, construction workers, administrative clerks, police and video game developers all develop their neural networks in the same way, a method simulated by ANNs.

This is not, "foreign to most artists," it's just that most artists have no idea what the mechanism of learning is.

The method by which you provide input to the network for training isn't the same thing as learning.

[–] zbyte64@lemmy.blahaj.zone 2 points 1 year ago (1 children)

ANNs are not the same as synapses, analogous yes, but different mathematically even when simulated.

[–] Prager_U@lemmy.world 1 points 1 year ago

This is orthogonal to the topic at hand. How does the chemistry of biological synapses alone result in a different type of learned model that therefore requires different types of legal treatment?

The overarching (and relevant) similarity between biological and artificial nets is the concept of connectionist distributed representations, and the projection of data onto lower dimensional manifolds. Whether the network achieves its final connectome through backpropagation or a more biologically plausible method is beside the point.

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