Taxes on AI subscriptions or AI capable hardware, to financially compensate IP holders for (potential) IP theft, could very well arrive in the near future, once the industry is mature.
If this shocks you and sounds preposterous, I'll remind you that in several EU countries, we still pay extra taxes on any and all storage mediums and on devices with built-in storage (tapes, CDs, DVDs, HDDs, SSDs, tablets, phones, etc) simply because they can be used to store pirated content, decisions based on laws from 50-100 years ago, and the money goes to the national unions and associations of music and arts IP holders. It's basically a lobby pushed and government legalized extortion racket that no voter agrees with or can change but has no choice but to conform either way.
So I guarantee you in the future, it will be the same for AI subscriptions and hardware capable of running LLMs locally. Every time you purchase a Claude or ChatGPT subscription, an Nvidia GPU, Intel/AMD SoC PC or an Apple/Qualcomm powered smartphone, you'll pay a government enforced tax to the likes of Sony, Axel Springer, etc. for licensing their IP, whether you want to or not. In the EU at least. US maybe not.
Under the settlement, Anthropic was forced to delete the pirated data they were training on.
Chinese labs can still train on pirated data. I doubt the Chinese models operate under similar licensing agreements.
The payment was for illegally downloading copyrighted material, not training. Training was explicitly ruled to be fair use.
Training on legally acquired / licensed data is potentially fair use.
And other district courts don't agree on this. The US district court for Delaware recently rejected a fair use defense for the use of copyrighted works to train AI. https://www.reedsmith.com/articles/court-ai-fair-use-thomson...
There are more cases in the pipeline. The massive NYT vs OpenAI is still ongoing. Nothing will be "settled" until this makes its way to the Supreme Court or Congress steps in.
> I doubt the Chinese models operate under similar licensing agreements.
US corps likely pay licenses when afraid to be sued, or have troubles getting that data, otherwise they just take data, which was demonstrated many times. The same apply to Chinese corps, alibaba totally can be sued in US.
Chinese labs can freely train on pirated material, which is a structural advantage.
Meanwhile, Chinese labs are speeding in a different county. Everyone knows they are speeding, yet the sheriff won't pull them over, so they just keep doing it.
This lax enforcement gives Chinese labs a structural advantage over American ones.
Do you purport to know for a fact that they're no longer training on the data they'd pirated? Because I highly doubt that.
Destruction of Materials: In addition to the monetary compensation, Anthropic has agreed to destroy the two libraries that allegedly contain the pirated works, as well as any derivative copies originating from those sources. Anthropic must certify in writing to class counsel that the destruction has been completed and that the allegedly infringing materials are permanently removed from its systems.
The libraries in question were Library Genesis (LibGen) and Pirate Library Mirror (PiLiMi).
If Anthropic is training models on deleted data, I'd be quite impressed.
there is much less intellectual property in China so it’s not ‘theft’ (as you can’t put property on information)
I'm not aiming for a what about kickflip here: I'm saying we need to either agree on some rules or stop crying foul. Maybe the coherent legal theory is that neural networks and intellectual property don't interact. That would be weird but it would be consistent, a market could price it, I could do coding stuff and know if I was illegaling.
But this weird gerrymander that no judge will really rule on in an emphatic way is like, bad for the planet, bad for markets, bad business.
There are a lot of reasons to look forward to DeepSeek Huggingface drop kicking the unambiguous frontier weights in like, November, but I think my favorite one will be "who's distilling now bitch?"
But the American AI companies only let you query their models if you first sign a contract to not train on the output.
It's hypocrisy and unfair, but I think there's a strong legal argument for it.
Of course China can simply decline to assist in enforcing that contract... But I would expect US courts to do their best to.
Now THAT'S doing some heavy lifting lmao. The vast, vast, VAST majority of the original datasets were from pirated books and the like. Also, arguably a robots.txt is the exact mechanism to follow to do the mass GET-ing, yet the AI cos choose time and time and time again to simply ignore it and be as abusive as they possibly fucking can
And there's been significant legal consequences as a result
> Also, arguably a robots.txt is the exact mechanism to follow to do the mass GET-ing
You're free to argue this of course, but the courts have largely rejected it already pre LLMs. See for example hiQ Labs v. LinkedIn
Or do you just mean that US courts don't have enough teeth to prevent Chinese companies from violating contracts? On that I agree.
The US is already publicizing the way they are using Claude with Palantir for war gaming purposes. It’s a matter of national defense. Contract law has no meaning here.
That right there is the problem.
Maybe today. I doubt it tomorrow. Legal and not legal, largely, has to answer to the population sooner or later. Ultimately, humanity decides legality. And I don't think the frontier labs will get a pass from humanity in the midterm, let alone the long term. I think you'll see the rules change towards something more "intent" driven. And there's absolutely no difference in intent between Frontier labs and everyone chasing them.
Frontier labs just want the door closed behind them, as do their investors, because they know the money will never be recouped if others can do the same magic tricks.
Situation right now seems more like a fragile detente: if you got a Hill staffer drunk and hounded him long enough he'd probably be like "God damnit the market will fucking tank if we don't get these two IPOs out north of a trillion. And don't even get me started on how I'm going to sell Chinese AI to a Senate that still calls people Nipponesians when no one is looking. We're doing the best we can alright, get off my back man."
We have a situation, but it's not exactly A&M Records, Inc. v. Napster.
Oh it is, and at least anthropic has paid $1.5 billion and deleted there torrented copies and not released any models derived from them as a consequence.
The thing is it turns out to be not that expensive to just buy a copy of every book legally and scan them. And there's even precedent that this is legal predating LLMs (Google books)
I have a bridge to sell you
Facts are in fact knowable, and the US legal system is in fact not terrible at getting to them.
But we've gone through some pretty weird times too. Turn of the last century was pretty tech billionaire edits, reconstruction was uh, not smooth, it's a mixed bag.
And most takes I hear seem to acknowledge that this is one of those weirder times: serious election fraud rhetoric from most everybody from 2016 to the present, very politicized courts (on both sides to be clear), very soft on anti-trust, very soft on adventurous accounting. The Epstein files and like, no consequences (pretty much uniquely for a developed nation with Epstein people). It's weird right now.
And I think I would be hard pressed to think of a weirder part of this weird time than the rule of law meets AI. We can haggle on where laws end and norms begin (stare decis being maybe the midpoint), but in the 90s, the Justice Department got their brass knuckles on for a lot less.
I don't think it's a simple "the law works nothing to see here" story.
I can understand why as someone who didn't follow it and the more corrupt legal developments closely you wouldn't be confident in that.
Granting people some form of control over knowledge only serves the public interest inasmuch it provides incentive to create more of it. Mass media, effortless duplication, and copyright extensions had already broken this to the point where control of knowledge was suppressing creation of new knowledge more than it facilitated.
The world has changed, we need a mechanism that works for the public interest that applies to the facts as they now are.
> The problem with distillation attacks
Apologies for repeating myself here, but what you call "distillation" is function approximation.
I feel for the teams at Anthropic and Open AI, but unlike startups from prior eras; Anthropic and OpenAI have decided to be in the business of selling compute. Not creating a product that uses compute, but a product that's math running on compute. This is different from what Google is (or, rather was. As always, RIP Google 1998-2019).
Google's algorithm might be math, but Google search isn't. Google search is a process that's continuously operating in the background. Google crawls pages. Google stores and indexes what it finds. Google then exposes this to retrieval via its algorithm. User uses algorithm.
Now, let's compare that to AI models. When Anthropic serves Mythos / Opus etc, they're taking input or x from their user, doing compute, and then serving the result of the Mythos / Opus function, i.e.,
f(text) -> (text_transform)
According to Stone-Weierstrass, given enough values of y for f(x), anyone can approximate this function.
The fidelity and sophistication of this approximation definitely requires a lot of cleverness and effort, and it is arguably an imposition on Anthropic and OpenAI. But on a long-enough timeline, they don't even have to poll Anthropic or OpenAI. As the internet is flooded by PRs, content, emails written by Mythos / Claude, and just people otherwise sharing the results of Claude prompts, then there's an ever increasing set of data to approximate the f(x) that's f_Claude.
Eventually, in the future, anyone will be able to create a good enough approximation of the f_Mythos. Which is Anthropic's product.
Anthropic and OpenAI can now wage war on mathematics and the open-ended compute. Or, they can adapt and build a better product.
Choosing Option B was the Silicon Valley option / choice. I think the OG large-scale Valley lobbying effort, the Semiconductor Industry Association, was unique in that it prioritized and chose to do real research.
https://en.wikipedia.org/wiki/Semiconductor_Industry_Associa...
https://en.wikipedia.org/wiki/Semiconductor_Research_Corpora...
This helped the industry to survive and outcompete the pressure they were facing (at the time).