[stusmall]

I can't wrap my head around the idea that distillation is IP theft but mass training on books, music and art without consent is fair use. The two stances are incompatible. If it is transformative use of a book, it is transformative use of AI output.

[BoxOfRain]

Yeah people in the US who want protectionism for US models on grounds of IP rights are appalling hypocrites. What’s good for the goose is good for the gander!

[munk-a]

I really hope that when a sane administration returns to power in the US we'll actually get a reckoning over how irrational it was to not restrict training data.

[hirako2000]

It isn't irrational.

The idea is that selling, or giving away art grants the consumer to sell art of his own, not a clear copy of.

So the court rationally found Anthropic guilty for acquiring copies without paying for them. But didn't charge the training, deemed fair use.

If it isn't fair use, then we may need to sue all teachers for spitting out knowledge they ultimately acquired from someone's work.

Copyright, some would say is irrational. Humans learn, that is copying, distilling in fact.

Copyright though is pragmatic: it draws a line, art will be reproduced, let's just enforce that they can't be shameless (near) identical copies. Mix it up, derive the original enough so that you aren't competing with the original author.

The only argument to ban training on copyright data is that it unfairly compete with original authors. Which stance do you take? Neither would be irrational.

[californical]

I agree that the fair use argument on training data is a genie that’s not getting put back in a bottle. But:

> If it isn't fair use, then we may need to sue all teachers for spitting out knowledge they ultimately acquired from someone's work.

Is such a lazy argument and always was. A human doing something is necessarily different than a machine doing it. We can be ok with a human doing a thing and simultaneously not ok with a machine doing it.

[hirako2000]

I side with the argument for machines learning being treated differently than human learning.

And in doubt, to pause and forbid commercialisation given the clear impact it's already having on people's financials, humans have invested in a given set of rules that ML are disrupting.

My argument is simply that the ruling for fair use isn't irrational. It's a rationality that you, me and many others would disagree with. Lazy? Yes. Also call it lazy, and biased towards VC's interest who can't squeezed much profit in status quo.

[slashdave]

No, it is stealing the R&D of another company.

[stale2002]

Ok, but only if you also conceed that all of these AI companies were stealing to train their models in the first place.

Either everyone was stealing all along, and they should all be sued out of existence, or nobody is stealing.

Personally, I think its all fair use and support all of the training, including distilations.

[slashdave]

Distillation is forbidden by the provider of the model.

I suppose you think that model providers are not allowed to impose restrictions on the use of their model? Think carefully before answering.

[stale2002]

> I suppose you think that model providers are not allowed to impose restrictions on the use of their model

They should have exactly the same ability to "restrict" it is as the writer of a book on those who read the book that was purchased.

And seeing as those model providers were not restricted from training on those books.... It would follow that other people would have the exact same right to train on the output of the models.

I simply demand that model providers are treated exactly the same as the data that they trained on. Either it was OK for them to train on other people's work, en mass, without permission, over the objection of the creator, and therefore its OK to do the same to them.

or none of its ok, and they should presumably be equally sued into oblivion, and equally shut down completely by the government.

Thats all. Take your pick. Either all of the training on either books and all the models, without permission, is ok or none of it is.

Additionally, the output of a model isn't even copyrightable. So actually there would be even less protections for that. Because of this, it seems that anyone could use it for anything.

EX: 3rd parties aren't bound by the TOS of the models. So someone could simply do a passthrough, and give the uncopyrightable output to someone else to distill, and since the distiller didn't sign the TOS they would be in the clear to train on non copyrightable info.

[slashdave]

> So someone could simply do a passthrough, and give the uncopyrightable output to someone else to distill

It seems you do not understand what distillation is.

[stale2002]

You have misunderstood my statement.

I am saying that someone else would use that output to create or improve a different model. I think you could have figured out that this was the meaning of my statement instead of doing the irrelevant nitpick that you did.

Its also unrelated to my point, which is that person 1 could give the data from model A to person 2, and person 2 would be fine because they didn't sign any TOS contracts with model A, and the output from model AI is not copyrightable and therefore can be redistributed.

Additionally, it still doesn't address the point about how the original model trained on a bunch of other people's stuff without permission, so I don't see why the same shouldn't be done to their outputted content.

Do you have any substantive disagreements or are you just going to make a minute, incorrect nitpick and then not elaborate?

[henryfjordan]

Is it? Turning a book into an AI model is lot more transformative than turning an AI Model into another AI Model.