What real-world problem does any of this solve? For instance, how does it protect my IP from being vacuumed up and used by LLMs without permission from or payment to me?
A comprehensive AI regulatory action is way too premature at this stage, and do note that California is not the sovereign responsible for U.S. copyright law.
That said, the penalty is not just $10k. It's $10k for an unknowing violation, or $100k for a knowing violation that "does not create a material risk of death, serious physical injury, or a catastrophic risk" or a unknowing violation that does cause that, and $10m for if you knowingly violate it and it does cause risk of death or serious physical injury, etc.
I imagine the legal framework and small penalty if you fail to actually publish something can play into the knowing/unknowing state if they investigate you as well.
In general though, it's easier to just comply, even for the companies. It helps with PR and employee retention, etc.
They may fudge the reports a bit, even on purpose, but all groups of people do this to some degree. The question is, when does fudging go too far? There is some gray, but there isn't infinite amounts of gray.
This is to allow companies to make entirely fictitious statements that they will state satisfies their interpretation. The lack of fines will suggest compliance. Proving the statement is fiction isn't ever going to happen anyway.
But it's also such low fine, that will eat inflation for those 12 years.
But I also understand that you were using hyperbole to emphasize your point, so there's not actually a reason to argue this.
It's a low fine, but your particular objection is invalid.
Think they were off by an order of magnitude for this fine. The PR for reporting anything bad on AI is probably worth more than the fine for non-compliance. 100k would at least start to dent the bumper.
Many will crash in rapid succession. There isn’t enough room for all these same-y companies.
- pioneers in wrongness 25 years ago. Oft copied, but never vindicated.
Having a dip and then a return to growth and exceeding the previous peak size isn't exactly a bubble. The internet and tech sector has grown to dominate the global economy. What happened was more of a cyclical correction, or a dip and rebound.
That's exactly what a bubble is. You blow too fast and you get nothing but soap. You blow slow, controlled breaths balancing speed and accuracy and you get a big, sustainable bubble.
No one's saying you can't blow a new bubble, just that this current one isn't long for this world. It's just that the way investments work is that the first bubble popping will scare off a lot of the biggest investors who just want a quick turnaround.
You can have a crash without this having happened.
If you deflate over time slowly (or simply slow growth expectations) you can prevent a pop. That doesn't tend to be what historically happens, though.
Yes. This seems to be what you're doing-- carrying the metaphor too far. I believe the common use relates the asset prices to intrinsic or fundamental values.
Funny, I think it is overdue.
Why?
The meat of the bill is that some government contractors are about to get very rich. And, if history reflects the future, some portion will be no-bid, to make sure the money goes to exactly who he wants it to go to: https://www.sacbee.com/opinion/editorials/article250348451.h...
(not directing these questions at you specifically, though if you know I'd certainly love to hear your thoughts)
It's not supposed to do anything in particular. It's supposed to demonstrate to the public that lawmakers are Taking Action about this whole AI thing.
An earlier version of the bill had a bunch of aggressive requirements, most of which would have been bad. The version that passed is more along the lines of filing paperwork and new rules that are largely redundant with existing rules, which is wasteful and effectively useless. But that was the thing that satisfied the major stakeholders, because the huge corporations don't care about spending ~0% of their revenue on some extra paper pushers and the legislators now get to claim that they did something about the thing everybody is talking about.
I know it's fun and all to circle jerk about how greedy those darn bureaucrats are - but we're all aware they control the budget, right? They could just raise taxes.
I don't think they're fining companies... sigh... 10,000 dollars as some sort of sneaky "haha gotcha!" scam they're running.
Hard to tell on the interwebs so apologies if that wasn’t the intent.
But, I ask, should they do nothing?
Drives AI innovation out of California.
Here's a list of the 50 biggest AI companies from April of this year. 3/4 companies on that list are located in the Bay Area. If companies are already willing to pay higher than average taxes, wages, and property costs to be located in California. I doubt, "You've got to publish safety standards on your website" is going to be the thing that drives them out of California.
CalCompute sounds like it's going to allow for more innovation than ever given that it should lower the barrier to entry for edge AI research.
50 Biggest AI Companies: https://www.forbes.com/lists/ai50/
Internet is becoming fragmented. :-(
maybe your situation is different, but if we geoblocked all of california we'd go out of business within a year
Most of who's getting caught up in these laws are very large companies that could comply but consistently don't put forth effort to do so after repeated complaints. Even if you do fall under the eye of regulators (most won't ever) if you show that you're putting forth a good faith effort to comply it's not a big deal.
AI companies trying to leverage their power and lobby governments to stiff paying people and thus increase profits is rent seeking behavior. They aren’t creating wealth by non payment, just trying to enrich themselves.
That’s the basic flaw in any argument around necessity.
Likewise much of the most important information to want to train on (research literature) was just straight up stolen from the public that paid for its creation already.
By contrast, the models being created from these works are obviously useful to people today. They are clearly a form of new wealth generation. The open-weights models are even an equitable way of doing so, and are competitive with the top proprietary models. Saying the model creators need to pay the people monopolizing generations-old work is the rent-seeking behavior.
Utility of older works drop off as science marches on and culture changes. The real secret of long copyright terms is they just don’t matter much. Steamboat Willy entered the public domain and for all practical purposes nothing changed. Chip 20 years off of current copyright terms and it starts to matter more, but still isn’t particularly important. Sure drop it down to say 5 years and that’s meaningful but now it’s much harder to be an author which means fewer books worth reading.
Even if you took all of that -- leave nothing for salaries, hardware, utilities, to say nothing of profit -- and applied it to the works in the training data, it would be approximately $1 each.
What is that good for? It would have a massive administrative cost and the authors would still get effectively nothing.
Google’s revenue was 300 billion with 100 billion in profits last year, the AI industry may never reach that size but 1$/person on the planet is only 8 billion dollars, drop that to 70% of people are online so your down to 5.6 billion.
That’s assuming you’re counting books and individual Facebook posts in any language equally. More realistically there’s only 12k professional journalists in the US but they create a disproportionate amount of value for AI companies.
Google is a huge conglomerate and a poor choice for making estimates because the bulk of their revenue comes from "advertising" with no obvious way to distinguish what proportion of that ad revenue is attributable to AI, e.g. what proportion of search ad revenue is attributable to being the same company that runs the ad network, and to being the default search in Android, iOS and Chrome? Nowhere near all of it or even most of it is from AI.
"Counting books and individual Facebook posts in any language equally" is kind of the issue. The links from the AI summary things are disproportionately not to the New York Times, they're more often to Reddit and YouTube and community forums on the site of the company whose product you're asking about and Stack Overflow and Wikipedia and random personal blogs and so on.
Whereas you might have written an entire book, and that book is very useful and valuable to human readers who want to know about its subject matter, but unless that subject matter is something the general population frequently wants to know about, its value in this context is less than some random Facebook post that provides the answer to a question a lot of people have.
And then the only way anybody is getting a significant amount of money is if it's plundering the little guy. Large incumbent media companies with lawyers get a disproportionate take because they're usurping the share of YouTube creators and Substack authors and forum posters who provided more in aggregate value but get squat. And I don't see any legitimacy in having it be Comcast and the Murdoch family who take the little guy's share at the cost of significant overhead and making it harder for smaller AI companies to compete with the bigger ones.
The point of comparison was simple a large company here, the current size of say OpenAI when the technology is still fairly shitty is a poor benchmark for where the industry is going. LLM’s may even get superseded by something else, but whatever form AI takes training it is going to require work from other people outside the company in question.
Attribution is solvable both at a technical and legal level. There’s a reasonable argument a romance novelist isn’t contributing much value, but that’s not an argument nobody should be getting anything. Presumably the best solution for finding value is let the open market decide the rough negotiations.
It's going to require training data, but no incremental work is actually being done; it's being trained on things that were written for an independent purpose and would still have been written whether they were used as training data or not.
If something was actually written for the sole purpose of being training data, it probably wouldn't even be very good for that.
> Attribution is solvable both at a technical and legal level.
Based on how this stuff works, it's actually really hard. It's a statistical model, so the output generally isn't based on any single thing, it's based a fraction of a percent each on thousands of different things and the models can't even tell you which ones.
When they cite sources I suspect it's not even the model choosing the sources from training data, it's a search engine providing the sources as context. Run a local LLM and see what proportion of the time you can get it to generate a URL with a path you can actually load.
> Presumably the best solution for finding value is let the open market decide the rough negotiations.
That's exactly the thing that doesn't work here because of the transaction costs. If you write a blog, are you supposed to negotiate with Google so they can pay you half a french fry for using it as training data? Neither party has any use for that; the cost of performing the negotiations is more than the value of the transaction. But the aggregate value being lost if it can't be used as a result of that is significant, because it's a tiny amount each but multiplied by a billion.
And then what would happen in practice? Google says that in exchange for providing you with video hosting, you agree to let them use anything you upload to YouTube as training data. And then only huge conglomerates can do AI stuff because nobody else is in a position to get millions of people to agree to that term, but still none of the little guys are getting paid.
Restricting everyone but massive conglomerates from doing AI training in order to get them to maybe transfer some money exclusively to some other massive conglomerates is a bad trade off. It's even a bad trade off for the media companies who do not benefit from stamping out competitors to Google and the incumbent social media giants that already have them by the neck in terms of access to user traffic.
Like I said science has mostly been stolen, and has no business being copyrighted at all. The output of publicly funded research should immediately be public domain.
Anyway this is beside the point that model creation is wealth creation, and so by definition not rent-seeking. Lobbying for a government granted monopoly (e.g. copyright) is rent-seeking.
Economic viability and utility for AI training are closely linked. Exclude all written works including news articles etc from the last 25 years and your model will know nothing about Facebook etc.
It’s not as bad if you can exclude stuff from copyright and then use that, but your proposal would have obvious gaps like excluding works in progress.
I suppose we all exist in our own bubbles, but I don't know why anyone would need a model that knows about Facebook etc. In any case, it's not clear that you couldn't train on news articles? AFAIK currently the only legal gray area with training is when e.g. Facebook mass pirated a bunch of textbooks. If you legally acquire the material, fitting a statistical model to it seems unlikely to run afoul of copyright law. Even without news articles, it would certainly learn something of the existence of Facebook. e.g. we are discussing it here, and as far as I know you're free to use the Hacker News BigQuery dump to your liking. Or in my proposed world, comments would naturally not be copyrighted since no one would bother to register them (and indeed a nominal fee could be charged to really make it pointless to do so). I suppose it is an important point that in addition to registration, we should again require notices, maybe including a registration ID.
Give a post-facto grace period of a couple weeks/months to register a thing for copyright. This would let you cover any work in progress that gets leaked by registering it immediately, causing the leak to become illegal.
Making a copy of a news article etc to train with is on the face of it copyright infringement even before you start training. Doing that for OSS is on the other hand fine, but there’s not that much OSS.
I think training itself could reasonably be considered fair use on a case by case basis. Train a neural network to just directly reproduce a work being obviously problematic etc. There’s plenty of ambiguity here.
This is why we’re seeing paywalls go up: authors and publishers of textual content are seeing that they need to protect the value of their assets.
There’s zero chance that happened without the book being in their training corpus. Worse, there’s significant effort put into obscuring this.
https://www.kron4.com/news/technology-ai/anthropic-copyright...
“the authors alleged nearly half a million books had been illegally pirated to train AI chatbots...”
Finally, a settlement isn’t a “win” from a legal perspective. It’s money exchanged for dropping the case. In almost every settlement, there’s no admission of guilt or liability.
https://storage.courtlistener.com/recap/gov.uscourts.cand.43...
His opinion, while interlocutory and not binding precedent, will be cited in future cases. And his wasn't the only one. In Kadrey v. Meta Platforms, Inc., No. 23-cv-03417 (N.D. Cal. June 25, 2025) Judge Chhabria reached the same conclusion. https://storage.courtlistener.com/recap/gov.uscourts.cand.41...
In neither case has an appeal been sought.
If you’ve read Kadrey the judge says harm from competing with the output of authors would be problematic. Quite relevant for software developers suing about code generation but much harder for novelists to prove. However, the judge came to the opposite conclusion about using pirate websites to download the books in question.
A new AI company that is expecting to face a large number of lawsuits and win some while losing others isn’t in a great position.
As it is, I would never pay for an AI written textbook. And yet who will write the textbooks of tomorrow?
You're not getting a cent from OpenAI, and the government isn't going to do anything about it. Just get over it.
I don’t deny the utility of LLMs. But copyright law was meant to protect authors from this kind of exploitation.
Imagine instead of “magical AGI knowledge compression”, instead these LLM providers just did a search over their “borrowed” corpus and then performed a light paraphrasing of it.
Because they are not actually memorizing those books (besides few isolated pathological cases due to imperfect training data deduplication), and whatever they spit out is in no way a replacement for the original?
Here's some back-of-the-envelope math: Harry Potter and the Philosopher's Stone is around ~460KB of text and equivalent to ~110k Qwen3 tokens, which gives us ~0.24 tokens per byte. Qwen3 models were trained on 36 trillion tokens, so this gives us a dataset of ~137TB. The biggest Qwen3 model has ~235B parameters and at 8-bit (at which you can serve the model essentially loselessly compared to full bf16 weights) takes ~255GB of space, so the model is only 0.18% of its training dataset. And this is the best case, because we took the biggest model, and the actual capacity of a model to memorize is only at most ~4 bit per parameter[1] instead of full ~8 bits we assumed here.
For reference, the best loseless compression we can achieve for text is around ~15% of the original size (e.g. Fabrice Bellard's NNCP), which is two orders of magnitude worse.
So purely from information theoretic perspective saying that those models memorize the whole datasets on which they were trained is nonsense. They can't do that, because there's just not enough bits to store all of this data. They extract patterns, the same way that I can take the very same ~137TB dataset and build a frequency table of all of the bigrams appearing in it and build a hidden Markov model out of it to generate text. Would that also be "stealing"? And what if I extend my frequency table to trigrams? Where exactly do we draw the line?
Is this actually true? I think in many cases it is a replacement. Maybe not in the case of a famous fictional work like Harry Potter, but what about non-fiction books or "pulp" fiction?
Kind of feels like the bottom rungs of the ladder are being taken out. You either become J.K. Rowling or you starve, there's no room for modest success with AI on the table.
Because that is, and always has been, legal.
Can hackers imagine saying this last decade when pertaining to Facebook harvesting your data? It's a shame how much this community has fallen into the very grifts they used to call out.
Except in this case after robbing humanity’s collective knowledge repository OpenAI and its ilk want to charge for access to it, and completely destroyed the economic incentive for any further human development.
And "further human development" is exactly what's happening. We've just found the entrance to the next level. Our brains have gone about as far as they can on their own, just as our muscles did in the pre-industrial era. It's time to craft some new tools.
So would I. You've just demonstrated one of the many reasons that any kind of LLM tax that redistributes money to supposedly aggrieved "creators" is a bad idea.
While by no means the only argument or even one of the top ones, if an author has a clearly differentiated product from LLM generated content (which all good authors do) why should they also get compensated because of the existence of LLMs? The whole thing is just "someone is making money in a way I didn't think about, not fair!"
AI will have effectively frozen human progress in a snapshot of time because nothing created after LLMs became widely available will be trustworthy