Except learning in this context is building a probability map reinforcing the exact text of the book. Given the right prompt, no new generative concepts come out, just the verbatim book text trained on.

So it depends on the model I suppose and if the model enforces generative answers and blocks verbatim recitation.

FaceBook did but technically downloading (leeching) isn't illegal but distributing (seeding) is and they did not seed.

I'd say there are two issues with it.

FIrst, it's a very new article with only 3 citations. The authors seem like serious researchers but the paper itself is still in the, "hot off the presses" stage and wouldn't qualify as "proven" yet.

It also doesn't exactly say that books are copies. It says that in some models, it's possible to extract some portions of some texts. They cite "1984" and "Harry Potter" as two books that can be extracted almost entirely, under some circumstances. They also find that, in general, extraction rates are below 1%.

If this is the ruling which causes you to lose trust that any legal system (not just the US') aligns with morality, then I have to question where you've been all this time.

I'll repeat what you said with emphasis:

AI can “learn” from and “read” a book in the same way a person can and does

The emphasized part is incorrect. It's not the same, yet your argument seems to be that because (your claim) it is the same, then it's no different from a human reading all of these books.

Regarding your last point, copyright law doesn't just kick in because you try to pass something off as an original (by, for ex, marketing a book as being from a best selling author). It applies based on similarity whether you mention the original author or not.

i will train my jailbroken kindle too...display and storage training... i'll just libgen them...no worries...it is not piracy

you think authorship is so valuable or so special that one should be granted a legally enforceable monopoly at the loosest notions of authorship

Yes, I believe creative works should be protected as that expression has value and in a digital world it is too simple to copy and deprive the original author of the value of their work. This applies equally to Disney and Tumblr artists.

I think without some agreement on the value of authorship / creation of original works, it's pointless to respond to the rest of your argument.

AIs are capable of generating an image of a full wine glass.

That's not at all what this ruling says, or what LLMs do.

Copyright covers a specific concrete expression. It doesn't cover the information that the expression conveys. So if I paint a portrait of myself, that portrait is covered by copyright. If someone looks at the portrait and says "this is a portrait of a tall, dark, handsome deer-creature of some sort with awesome antlers" they haven't violated that copyright even if they're accurately conveying the same information that the portrait is conveying.

The ruling does cover the assumption that the LLM "contains" the training text, which was asserted by the Authors and was not contested by Anthropic. The judge ruled that even if this assertion is true it doesn't matter. The LLM is sufficiently transformative to count as a new work.

If you have an LLM reproduce a copyrighted text, the text is still copyrighted. That doesn't change. Just like if a human re-wrote it word-for-word from memory.

For the purposes of this ruling it doesn't actually matter. The Authors claimed that this was the case and the judge said "sure, for purposes of argument I'll assume that this is indeed the case." It didn't change the outcome.

If someone ask for a glass of water you don't fill it all the way to the edge. This is way overfull compared to what you're supposed to serve.

The concept of a glass being full and of a liquid being wine can probably be separated fairly well. I assume that as models got more complex they started being able to do this more.

Yeah but it's just a start to reverse the process and prove that there is no AI. We only started with generating text I bet people figure out how to reverse process by using some sort of Rosetta Stone. It's just probabilities after all.

“it was unable to link the concepts until it was literally created for it to regurgitate it out“

-WraithGear

The’ problem was solved before their patch. But the article just said that the model is changed by running it through a post check. Just like what deep seek does. It does not talk about the fundamental flaw in how it creates, they assert if does, like they always did

I mean, they can assume fantasy, and it will hold weight because laws are interpreted by the court, not because the court is correct.

Of course we have to have a way to manually check the training data, in detail, as well. Not reading the book, im just verifying training data.

That's possible but it's not what the authors found.

They spend a fair amount of the conclusion emphasizing how exploratory and ambiguous their findings are. The researchers themselves are very careful to point out that this is not a smoking gun.

Sure, if your purchase your training material, it's not a copyright infringement to read it.

We needed a judge for this?

You mean when the training data becomes more complete. But that’s the thing, when this issue was being tested, the’AI’ would swear up and down that the normally filled wine glasses were full, when it was pointed out that it was not indeed full, the ‘AI’ would agree, and change some other aspect of the picture it didn’t fully understand. You got wine glasses where the wine would half phase out of the bounds of the cup. And yet still be just as empty. No amount of additional checks will help without an appropriate reference

I use ‘AI’ extensively, i have one running locally on my computer, i swap out from time to time. I don’t have anything against its use with certain exceptions. But i can not stand people personifying it beyond its scope

Here is a good example. I am working on an APP so every once in a wile i will send it code to check. But i have to be very careful. The code it spits out will be unoptimized like: variable1=IF (variable2 IS true, true, false) .

Some have issues with object permanence, or the consideration of time outside its training data. Its like saying a computer can generate a true random number, by making the function to calculate a number more convoluted.

Yeah authors rely on the recent deep mind paper https://aclanthology.org/2025.naacl-long.469.pdf ( they even cite it ) that describes (n, p)-discoverable extraction. This is recent studies because right now there are no boundaries, basically people made something and now they study their creation. We're probably years from something like gdpr for llm.