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No, really:
> As you know, funding for frontier model development depends on valuations that assume the weights remain proprietary. By changing that assumption, we can reduce the money available for future training runs and slow progress at every lab at once, without a regulator deciding anything.
Which doesn’t even follow. It depends on every lab in the world agreeing to self-destruct their valuations and stop competing. That’s a much more impossible ask than anything Dario is asking for.
It also ignores the possibility of new labs starting up, using the open weights, and continuing exactly where the old labs left off.
I feel like I just read the ramblings of someone who got so excited about the headline that they didn’t take the time to think if their argument was sound.
What are the alternatives?
A regulator saying no? Easy, your headquarters has just moved the Cayman Islands, Ireland, or Switzerland... the US office is just a subsidiary leasing the brand IP and doing marketing.
Or, you just ignore the regulator behind closed doors because you're part of some black budget. You wouldn't be able to talk about that closet back there even if it did exist.
Or, you don't do any of these complicated loopholes and you simply move all the training and inference to a different jurisdiction.
If the only winning move is not to play, how do you ensure everyone stops playing?
Simple: you must destroy the game.
It does have a kind of mad logic to it.
(That is a bit dramatic, but the idea is if we accept that AI research will happen wherever there is capital available, instead of restricting the research you restrict the return that capital can earn. And the only provable/market way of doing that is to require the results to be open. In other words, if the benefits of getting all that cash to buy GPU's gets handed out to everyone for free, then there will be far less cash floating around to buy GPUs, slowing down the process)
Every chinese frontier lab releases their model weights and often more under FOSS terms (or more restrictive but still generally open terms).
If models for public inference use are required to be open weight in the US give or take some amount of limited fine tuning, then the US and China would be on the exact same playing field. Frontier labs would be pushing functionality for functionality's sake and would either be supported by govt funding or would be supported by domestic inference providers.
And then at the end of the day everyone is just either doing open research, is an inference, fine tuning, and training provider, or is the govt.
It's easy and straight forward and pushes everybody in the market towards common standards and interoperability.
That argument is straight from Dean Ball on Twitter. Open-weight models are "decelerationist", which is bad if you're completely AGI-pilled but is actually great if you're either worried about AI Safety falling to an arms-race at the frontier (this is Dario's argument, and note that open weight models are far behind the proprietary frontier, especially since they target widespread lean deployment so they must skimp on total parameters and compute requirements) or Yann-LeCun-pilled (i.e. skeptical about AGI/ASI but optimistic about the practical usefulness of current AIs) like most people in China (including, reportedly, Chinese leadership).
Open weight models are accelerating AI adoption and make it easier for other labs to advance their own models.
There is nothing decelerationist about it.
This entire line of thinking can be dismissed by observing that labs releasing open weight models are advancing rapidly.
Is the frontier's moat not mainly data and compute? How does making the frontier open weight affect that?
It's a law, so nobody has to agree to anything. If want to sell access to a model, you have to open the weights.
It's Dario's plan that depends on every lab in the world agreeing.
Step #2 of his essay is "democratic coordination" among frontier labs and step three is coordination with China. I'm suggesting a single law Congress could pass that every US model company would have to follow on the same day, whether they like it or not.
Frontier progress is compute bound. Compute is bought with investor money. Investors put up tens of billions because they expect to sell the proprietary model that is created.
You're welcome to think the effect would be smaller than I do. But "it requires everyone to agree" is backwards.
Laws don’t extend to the entire world. There are AI labs outside of the US that are not that far behind. Forcing US companies to open their weights would hand those labs another advantage, moving the frontier AI to a location outside of any US regulation.
Your proposal doesn’t make any sense.
> The plan that depends on every lab in the world agreeing is Dario's.
I don’t understand how you think creating a law in the US to destroy our AI companies and give an advantage to competitors we can’t regulate accomplishes anything in line with the AI safety debate.
Frontier development won't simply move offshore because the GPUs, most of the people, and almost all of the funding is here.
Our European and Asian allies would probably go along with this idea, because it costs us far more than it costs them.
Just asking for a friend (“shut up Netflix, I already asked”)
* Destroy the free internet in the US, ban VPNs in the US, assume enforcement of this is effective, ban frontier AI development in the US (probably needs at least one constitutional amendment)
* Assume no other countries will continue to develop AI and approach or push the frontier
* Then, the frontier ceases to move until the US companies agree to let it move again
...
I don't think anyone proposing a "pause" has studied politics or game theory even at a high school level.
Incredible.
Yes, why would you ever address someone with something that is not in their best interest. Especially people that have power.
I agree. We should never do that and let them just live in peace and do their thing.
Step 1, form a world government?
Even if your someone who thinks open models are good for safety overall, a private model exposed only by an API point at least gives somebody control. How we should use that control is debatable, but at least it's there. Once you release that control by making a model open, you can't take it back.
If we think AI safety doesn't require closed weights, we should collectively decide on that and then move forward from there. But it shouldn't be something decided by default, by a few people from a few companies. We all have to live with the consequences of a choice like that, and since it is irreversible, we shouldn't decide it without consensus first.
The Chinese labs are already "self-destructing" voluntarily by releasing their weights. Or do they have an actual business model?
I mean I get that they don’t want to share details on how AI might destroy humanity but this secrecy also leads to speculation that this is just a PR campaign pushing for regulation, which might come handy.
You don’t need to tell the world what your super AI has given you to cause this panic but definitely you could share it with a group of experts who then inform the public in a report, couldn’t you?
Did OpenAI releasing GPT-2 self destruct their billion dollar valuation or is it higher than ever today at $900B. The idea that releasing weights kills the future value that can come is not supported.
The conversation was about AI safety, monitoring, and regulations, not bubbles.
Forcing the weights to be opened to the world accomplishes the opposite of all of that. The argument is incoherent. Or this author doesn’t understand the topic at all?
> The companies themselves wouldn't do it, but they could be required to if they want to operate in the US.
What makes you think the companies outside of the US wouldn’t just thank the US companies for their open weights and then continue on without any of the regulations but all of the advantages?
Or maybe you understand less than you think?
Frontier progress is limited by compute, and compute is bought with investor money. Investors fund labs at hundreds of billions because they expect exclusive ownership of the model weights.
If the weights are public the day a model ships, the valuations drop, the funding rounds shrink, and the next training run is smaller or later. Make sense?
Anthropic has already shown they're very comfortable with holding models from the public. Mythos has been around for what, six months, and there's never been a public release. Only the select few blessed by Anthropic have access.
Forcing transparency on public models will just accelerate privatizing access to these models. You don't want to live in that world.
Enterprises are part of the public in this context, so that's not a loophole which would exist.
I mean... that's the entire point of their argument, yes.
>Anthropic gets most of its revenue from enterprise agreements anyway. Providing public models or providing public access to their models is their secondary business.
Enterprise agreements are public access.
The obvious outcome of this plan would be frontier models not being released at all to public It'd be an amazingly bad outcome. Models accessible to the public would stagnate (no capital, no access to frontier model tokens to distill from), while internal models would keep improving at their previous pace, use them in-house, and eventually eat the whole economy.
It’s a good point and not exactly made subtly but seems completely lost on most comments here.
Are they trying to stop everyone else from catching up with them or have they hit some kind of roadblock to improve models even further?
But IMO, they're not trying to help humanity
Always soon. But soon never seems to come. I'm sure we'll all be cooked any day now.
1. AI model safety is the most important thing.
2. open weights decreases model safety
So it seems unlikely that this suggestion would be well-received
https://github.com/anthropics/claude-code/issues/6235
> AI models are dangerous. They can help bad people do dangerous things. They may be capable of autonomously executing dangerous things. They may cause unwanted effects on the labour market.
> More capable AI models are more dangerous, but require more money to train.
> Money requires investors with expectations that the model will generate a profit over its operational lifetime.
> The operational lifetime value of a model is decreased if every model is public and can be hosted on any infrastructure.
> If investors see less operational lifetime value from model companies, model companies receive less capital and therefore train more capable models at a slower rate.
Follow-ons: There are immediate risks in releasing capable cyber models that can be ablated and then launch cyberattacks. Concentration of power moves immediately into the infrastructure layer for inference.
Models will be kept private for longer, if not indefinitely, given there is less incentive to release them publicly.
Enforcement globally will occur because accessing the lucrative US market means using an open source model.
The entire argument hinges on strict enforcement of this policy, when AI model routing can already be opaque.
It also hinges on investors being rational and expecting free cash flow from AI companies, rather than reaching a criticality threshold of model capability for recursive self-improvement internally and parlaying that into a global mega-corporation.
New labs and companies without infrastructure connections will no longer be able to raise money, given investor expectations, and therefore not be able to increment AI progress.
So a win for the infrastructure layer, models being kept private for longer, new labs being unable to compete, immediate risks in the rollout (I suppose could be mitigated by a staged rollout i.e. policy active in 2030, pricing effects now), enforcement being tricky, and in the event that foreign competitors lead the AI frontier and then start closing models, just conceding the market to them if US consumers and companies find workarounds to pay for foreign AI.
Instead, they are partnering with some of the most disliked companies (x, meta) to further their goals.
The counter argument from Anthropic is easy. If we open weights we can't detact it after being published / the guard rails that run on top of the models would be lost. Also abliteration would be much easier to do when a model's been publically release.
I'm not a fan of Anthropic but the argument in the article seems stupid.
I’m not saying I’m for these solution, I’m probably against, but if we are being serious why are we not discussing these options?
2) frontier models are way more dangerous if they are open. It’s opening Pandora’s box, there’s no going back once they are released if they are too dangerous.
This is such a short-sighted take and author seems unaware of what damage can be done with powerful open weights models (intentional or not).
Jail-broken Fable level LLMs can mean constant hacking leading to public desertification of the web (best case). Now imagine state sponsored bio lab leaking strange viruses on yearly basis. We've seen enough evidence already, it is difficult for me to imagine an engineer living at the centre of the change is writing this piece.
It's a different question if you ask me if I trust a single company to police the technology. But with the current state of things, I unwillingly admit that no state entity can do a better job at the moment.
A jailbroken model that can hack a website can also easily fix the vulnerability that allowed it to hack it. There is a limited number of such vulnerabilities. Over time, all vulnerabilities that are discoverable by the model would be patched and status quo would be restored (until a more powerful model is released: rinse and repeat).
In your scenario, during the disruptive phase, I can imagine apps advertising 'we have Mythos backed security company defending our data'. Reminiscent of showing how much your gun is bigger than your neighbour or gangs on the street, it's truly distopian.
Somehow this plan manages to lean into every single bad outcome
(That being said, Chinese labs are releasing weights, so I'm not sure how the economics actually work.)
It also takes a lot to do anything with a 1T+ parameter model. Arguably there is still an immense capital moat. So I'm not sure it would even have the effect the author intends.
That said, these frontier models are still astronomically huge.
"Any AI model a company offers to the public has to be released as open weights."
OK great, that means no models released to the public, complete concentration of power.
Their entire funding model depends on that they generate much revenue _soon_
By acquiring companies and letting the now-internal employees use AI, easily outcompeting any company they didn't acquire
If it were easy they'd be doing that instead.
i mean, 3 months ago i started to use AI for a project i'm working for around 6 years, full-time but calling a billionaire good and principled is a stretch and when you consider what made him rich, you sound like a 3 year-old kid trying persuade a mom or a dad to get lollipops when your are diabetic
LLMs it's already a economical treat for various fields/people, which not only funnels powers to the elite even more, it does through by violating copyright... everyone who uses this technology is dirt (that includes me and my little dreams of hopefully creating a company which employs minorities on the tech field) but the amount of greed from people who own these servers/GPUs is beyond this world - the world isn't GPLv3 licensed yet, an ethical society wouldn't find excuses to provide and sell LLMs to the masses
An open letter to Dario: if you mean it, give me a billion dollars!
Every time you, or any AI company releases a new frontier model, you have to give me a billion dollars. No strings attached. This will solve the danger of AI. Somehow.
Also: releasing just the weights is like releasing some source code without makefiles or configuration scripts. Sounds half-baked.
PS. The real problem with concentration of mega-models is the same old problem of temporary monopolies in emergent markets (IBM in 80s, Microsoft in 90s, Google Search in 2000s). Let's not worry too much about other peoples' money and use the amazing tools we have to solve our problems today.
The same playbook had been used, for eg. by Microsoft trying to fight Linux adoption and growth decades ago.
This is the *exact* same playbook used to instill fear and scare people into regulating and setting up barriers to open weight and open source model adoption which these companies know put their amortization and margins at serious risk. The outcome of this game is well known and well understood by this point. This FUD, even if it succeeds, only slows down, not stop, open source adoption. Eventually, open source always wins because people want something that they can control and manage costs.
Unless OpenAI, Anthropic, etc., will forever subsidize tokens, where it would never make sense for people, even after discounting 3rd Party/managed vs local/airgapped/self-host AI for risk, self-hosted AI, this FUD battle will eventually be lost, like it always has been. It is surprising to make this statement in late 2026, when OpenAI, Anthropic have not even IPO'd yet, and there is discussion in the streets that they'll IPO at trillions of dollars, something that is historically unthinkable, but history indicates otherwise: that in a decade or so, OpenAI and Anthropic are going to be footnotes in history and LLMs are going to be commodity with tokens selling all the way from unthinkably commodity to then-frontier intelligence prices.
We will tell those generations fond stories of how computers with hungry NVIDIA GPUs that could run quality language models in 2026 cost a month or two worth of a dev's salary, while the then-current generation phones that fit into a pocket has way more compute capability, were already AI native and were cheap as chips.