Comment by MangoCoffee
6 hours ago
maybe this is why Dario want to slow down AI development and all the big AI labs in the USA is singing the same song.
whey they all singing the same tune. it make me question what is their real motives.
they are afraid of Chinese good enough LLM model killing their margin. we already have story about US companies switch some task to use cheaper Chinese model hosted on Neoclouds.
The reason is money. They want regulation to make it harder for new competitors and competitors from other countries.
They invested billions into training the models but there is no competitive advantage, we see that within a couple of months everyone catches up. There is no way to profitability unless they get some policies to shields them against competitors that can't comply with the regulatory requirements.
That is also why there are things like Claude, Codex and Cursor. They are trying hard to build a customer relationship with a higher switching cost that hopefully sticks.
But the problem is that the AI buildout has become a large percentage of GDP. So obviously the government wants to keep it going because these companies are pumping enormous amounts of money into the economy.
> But the problem is that the AI buildout has become a large percentage of GDP. So obviously the government wants to keep it going because these companies are pumping enormous amounts of money into the economy.
They are pumping enormous amounts of money into each other. Hardly any of that is making its way to people, it's all going to highly automated construction and to energy use.
Seriously, how many jobs did the $1t in venture capital fund?
If I pay you 100$ for mowing my lawn, and you me for yours. Technically the GDP increased with 200$.
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> Hardly any of that is making its way to people, it's all going to highly automated construction and to energy use.
How do we know that? How automated is the construction really?
In any case, the Fed and other central banks can print as much money as they want in order to hit any aggregate spending or inflation target they have for the economy.
Well, if you are right, I just hope their protectionism will only affect the American market, and they leave us unAmericans free to get our models from wherever.
Unless something has shifted, “everyone catches up” is because these bleeding edge models are distilled. You don’t see this happening with other European and US labs and the problem isn’t something being ignored. I’m not convinced this pattern will continue indefinitely.
Why is it OK to train on the collective IP of humanity and call it fair use but then call the next batch distilled with negative connotations?
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I’m still not at all sure about the “billions” invested claim. How much of that is cloud running the models? How much is pre and post training (which may or may not be part of what we’d want to include in accounting). Etc. Does anyone have links to good reporting about this: not blind recitations of numbers, but analysis and thought mixes with investigation?
No chinese lab has caught up yet. They've tried to fake it by distilling and overfitting on benchmarks to make their models look better than they are, the 'best' models available from chinese labs right now (GLM 5.3 and Kimi K3) fall apart completely when you try to do real work with them. K3 is especially embarrassing because it is larger than Mythos yet performs worse than opus 5 and 5.6 sol in benchmarks they haven't been able to fake yet.
In that case, Open AI and Anthropic have nothing to worry about.
Competition on the provider side—when no single dragon monopolizes the sky—brings fortune for all.
As normal consumers with common sense, we should never naively assume others care for the world out of the goodness of their hearts. Maybe they do, but we should never rely on that.
We can only get good, affordable deals when there is enough competition on the other side.
Please explain how putting an upper bound on how good the strongest models can be prevents cheaper less strong models from catching up, rather than enabling it. I do not understand this argument at all.
The general idea is that Anthropic/OpenAI is pushing this narrative as an attempt at "Regulatory Capture"[1] which would allow them to make it prohibitively expensive for anyone but them to enter the market thus stifling competition.
* 1: https://en.wikipedia.org/wiki/Regulatory_capture
How would that slow down the Chinese models, given that the US has no regulatory reach in China?
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I heard someone analogize token vendors to car manufacturers, where American companies only want to produce expensive options, the people want cheaper/better alternatives, and we ban BYD because those with enough money are more "persuasive"
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> Please explain how putting an upper bound on how good the strongest models can be prevents cheaper less strong models from catching up, rather than enabling it. I do not understand this argument at all.
They are not proposing to regulate only the strongest models. They are proposing to regulate all models. If they are already on top, regulation may stop them from proceeding further, but it also stops the cheaper alternatives from catching up.
If they feel they have reached the asymptote of the curve, then regulation doesn't affect them, it affects those who have yet to reach the asymptote.
Particularly, the route they seem to want to go is "safety".
My guess is that Anthropic and OpenAI will push for "safety" regulations which require byzantine testing that, shocker, Anthropic and OpenAI can pass but the chinese models cannot. The route they'll take is import bans and potentially even general bans on products producing or using "unsafe" models.
They'll further likely try and push AI "safety" treaties from the US to other nations to further lock in their lead.
That's why, IMO, we've been seeing so many "OMG, AI will destroy the world and these AI researchers are so scared" articles.
I don't think "putting an upper bound" was OPs phrasing?
That's what pacing the frontier is, and is what the labs are pushing for.
That’s not the argument.
Please elaborate on what the AI labs are specifically requesting and how that results in slowing down Chinese model progress below the frontier.
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This is definitely part of it. I think the reports/PR over the past month ended up being a serious unforced error.
Chinese models are increasingly closer to the frontier, while being able to run on much cheaper hardware than what US frontier models run on.
On top of that, both Anthropic and OpenAI showed that they can't really be trusted on data security.
Even if US companies can be forced to not use Chinese models, the rest of the world is going to see the risks and the availability of good enough open weight models for their purposes and be more likely to lean in favor of self-hosted Chinese models or local inference clouds.
In a recent Dwarkesh podcast Dylan Patel breaks down how little compute the chinese labs actually have- not even the fact that they don't have access to new Nvidia chips and they're stealing them through shell companies- just that, even if they have cheap electricity, the compute just doesn't compare. Maybe even two orders of magnitude less. They couldn't get it even if they had the money. And if you look at how much more efficient newer chips are, that cuts the effective compute in half again. The conclusion was that they are at least 2-3 years behind.
For frontier labs the current compute seems to be driving model progress (in training) at least to some degree, even without true RSI, and this seems like it'll continue to keep any chinese model from drawing even with the frontier labs, at least for the foreseeable future.
Inevitably the chinese government will drive more funding in chip fab technology and the money will come around to build chinese data centers, but who knows how far off that is. A few different things in the tech tree need to fall into place. It doesn't seem like it'll be next year.
The counterpoint to that, though, is that the Chinese companies have to figure out how to be competitive, regardless of their significant compute deficit. And, as far as I can tell, they're actually doing that. They're trailing the frontiers in model effectiveness, but not by years. It's single digit months.
If there is no upper bound how how these things scale with compute, and if China does really begin to catch up to Nvidia (and they're probably not going to feel encumbered by US patents for domestic AI hardware, given how important AI seems to be to the Chinese government), there will come a day when China leapfrogs the US on AI.
I think on the timescale of 10 years, that's a super likely scenario. But will it be any sooner?
For instance a Chinese EUV machine seems like it's very far away. Even if they have (steal/borrow) the necessary IP.
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Does anyone know what are the proposed regulations? Controlling software is impossible, so the only option is banning hardware ownership. No more mac studio.
If you pay attention to how these US CEOs talk, it'll be "safety". If I were to guess, they'll try and require a lot of testing, validation, certification before a model is legally allowed to be used in the US or on US products.
It won't be a great moat, they'll probably try and get trade treaties setup to try and expand the moat. But ultimately it won't slow down chinese model development, just limit who can legally use them.
From the frontier labs, the only publicly stated one seemed to be to give them an exception from anti-trust laws to form a cartel and place - incidentally friendly - regulators in charge of monitoring everyone's work.
From politicians like Bernie Sanders, we've had proposals like 20 year imprisonment for anyone researching "ASI".
OAI and Anthropic are forced to release a better model every x months otherwise the Chinese ones will not only be cheaper but also better.
So how could Dario show the investors very nice profit charts representing profit = revenue excluding training costs if it needs to pay a lot of training every x months?
They want to sell the same model for longer(a kind of software subscription where the cost of running /inference is cheap) but the Chinese don’t let them do it. That’s the gist of it. You can see already how they nerf the models just a week or so after release and try all kind of tricks to deliver you shitty performance for the same money. I think it’s part of the same issue of costs and enshitification plan.
In the meantime let’s hope they don’t get to ban the Chinese models(I think they won’t), local AI hardware will get cheaper and the whole AI doom saga will slowly fade to the point that Anthropic becomes a kind of IBM stuff with proprietary data, enterprise certified alignment and enterprise contacts. Think of Accenture junk.
I mean DSv4.1 Flash and GLM 5.3 kept in check by a supervising frontier like Astra or Fable already in my experience clowns massively on ever using Opus or Sonnet. Opus 5 in particular has been such a stinker that they have to know that they're going to get smoked outside the halo models.
Or it’s PR to push up the price of AI shares
Dario has always wanted the AI development to slow down and be more careful. Safer AI development was a core reason that Anthropic split off from OpenAI.
What's different today is that now all the big LLM firms want to slow down AI development. When men like Musk and Altman (both known for habitually shooting their mouths off and saying whatever they need to whoever needs to hear it regardless of truth) suddenly agree with Amodei, that's when things start to smell off.
> What's different today is that now all the big LLM firms
not all, just a few American ones (~PayPal Mafia + Google), there are other big American LLM developers (notables include Nvidia, Meta, and Palantir) that do not agree