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.

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.

They are and will continue to get away with this. Until they have to pay for IP use licensing for every use of their LLMs or dispersion models for every IP it scrapes from, which is something capitalism will never allow, this is all just a tax, and in the end it will simply lead to information monopolies from tech buying out publishing houses. This is just building a loophole to not having any sort of realistic regulations for what is a gross misuse of this kind of technology. This is the consequence of the false doctrine of infinite growth.

It made the ruling stronger, not weaker. The judge was accepting the most extreme claims that the Authors were making and still finding no copyright violation from training. Pushing back those claims won't help their case, it's already as strong as it's ever going to get.

As far as the judge was concerned, it didn't matter whether the AI did or did not "memorize" its training data. He said it didn't violate copyright either way.

Make up a word that is not found anywhere on the internet

Returns word that is found on the internet as a brand of nose rings, as a youtube username, as an already made up word in fantasy fiction, and as a (ocr?) typo of urethra

You still need to pay Disney first.

Well, except Shakespeare is already public domain.

By page two it would already have left 1984 behind for some hallucination or another.

If I understand correctly they are ruling you can by a book once, and redistribute the information to as many people you want without consequences. Aka 1 student should be able to buy a textbook and redistribute it to all other students for free. (Yet the rules only work for companies apparently, as the students would still be committing a crime)

A student can absolutely buy a text book and then teach the other students the information in it for free. That's not redistribution. Redistribution would mean making copies of the book to hand out. That's illegal for people and companies.