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Nvidia, Microsoft, Meta warn against overregulating open-weight models
(cnbc.com)
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by louiereederson
by louiereederson
Probably because anthropic is pouring $40 million dollars into a political pact to regulate models. And they have not been quiet about wanting to ban/regulate OSS models either.
I have no idea why HN still treats them like ~their~ they are the ethical good guy.
Edit: I can’t English. At least we know this came from my dumb swishy brain
I don't know that HN usually does. But they did buy a decent amount of publicity by (initially) telling the US government no in using the models for war.
It's why Ukraine and Russia are now using fully autonomous drones. That's the only real solution to jamming.
Hopefully Anthropic eats crow here, lest their wish is fulfilled that we all become slaves to the anointed few who work there. Never getting another dollar from me after pulling these stunts.
s/good/least bad/
Which company would you put higher?
1. Breaking Points Discussion: https://www.youtube.com/watch?v=SIUrshGwgDI
2. Full Bloomberg interview: https://www.youtube.com/watch?v=x2VHFgyawPE
Why Kimi? because K3 is the only frontier model I can have a serious conversation with about my product's security.
(I did apply for OpenAi's Cyber Pilot but got no response)
Same experience with Anthropic's. I applied for my employer, and.. 0 response.
The oddly reminds me of back in the day when SOPA had caused a similar stir (https://en.wikipedia.org/wiki/Stop_Online_Piracy_Act), and all HN was up in arms against it.
Startup founders urge U.S. government not to shut off Chinese open weight AI - https://news.ycombinator.com/item?id=49023016 - July 2026 (841 comments)
Also related:
OpenAI and Anthropic unite against open-weight AI risks to their bottom line - https://news.ycombinator.com/item?id=49020868 - July 2026 (330 comments)
China’s open-weights AI strategy is winning - https://news.ycombinator.com/item?id=48979269 - July 2026 (932 comments)
The gap between open weights LLMs and closed source LLMs - https://news.ycombinator.com/item?id=48692058 - June 2026 (250 comments)
The unbearable cheapness of open weight models - https://news.ycombinator.com/item?id=48668255 - June 2026 (186 comments)
And as a more general point - more major competitors in a domain is very good for everybody except those competitors themselves, who would rather there be as few as possible.
Perfecting these autonomous agential coding AIs just moved way way faster than anyone expected. People are desperately trying to save their principles from six months ago but it's a different world. They can work out their issues with Trump, Dario and Sam, but it is Xi who will shut all this down.
Could you elaborate? I don't understand your implication.
Amazon in particular hosts open weight models via Amazon Bedrock (e.g. Ministral 14B 3.0, DeepSeek V3.2, ...)[1].
In case it changes the context of this comment, I am a Meta employee, all opinions are my own.
[1] https://docs.aws.amazon.com/bedrock/latest/userguide/model-c...
https://www.microsoft.com/en-us/corporate-responsibility/top...
No wonder openai and anthropic are terrified
This is the correct stance, hopefully this is the stance that prevails.
The Chinese open models are way ahead, not by how capable they are compared to frontier models, but on how they project to the world and how they improve over time.
The gap is shrinking, but considering their models still lag our frontier, I wouldn't say they "run circles" around us.
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Predictable power play by corporate strategy and legal departments.
[0] https://en.wikipedia.org/wiki/Export_of_cryptography_from_th...
It makes sense to see Meta, the startups, and the VC firms on this list. And it makes sense to see OpenAI, Anthropic, and Google all missing. Microsoft is somewhat unexpected to me. I don't think of them as having a focus on open weight models (no more than Google), and they have a large stake in OpenAI. Maybe they're looking at this from the angle of Azure providing compute. But then why is Amazon missing, when it has AWS?
And of course, we don't see DeepSeek, Moonshot, or Z.ai on here. The letter is about American technological leadership after all. But then we _do_ see the French company Mistral! Mistral who released [a playbook](https://europe.mistral.ai/) for Europe becoming a self-reliant AI powerhouse.
I assume all of this is in the context of influencing the Trump administration's thinking on Chinese open weights models. But the letter is really about _American_ open weights models. The call to action is all about keeping the American open weights ecosystem competitive. I didn't even realize that was under threat, so I feel like I'm missing something.
remember when bitcoin got its first dedicated hardware, will be like that
So the closed model try to get client with their model by saying it's cheaper than employees, and then turn around to lawyer-out cheaper alternative?
Truly the american dream.
If I change one weight in Kimi, is it still a Chinese model?
If I fine-tune Kimi on pro-America nationalistic freedom loving anti-Chinese propaganda, is it still a Chinese model?
If I distill Kimi from one server to the next without ever directly transferring any weights, is it still a Chinese model?
If Claude accidentally trains on some of Kimi's output, is Claude then considered to be a Chinese model?
If China's next open-weight model is released secretly through a European company, is it still a Chinese model?
Start with the outcome you believe will be the most in line with the spirit and traditions of the open source community. This is precisely what won't happen.
It won't necessarily be the inverse. It could be, of course, but it's also likely to be a compromise between the two.
For a topical example: The companies doing "AI" layoffs aren't doing so out of a sense of having failed their staff that helped carry them so far. Often, these announcements come on the heels of record-breaking profits. They're doing it out of contempt for workers.
See https://www.cnet.com/tech/services-and-software/cory-doctoro... for Doctorow's take on centaurs vs. reverse centaurs. Broadly speaking: C-suite business leadership wants reverse centaurs. Workers want centaurs. Unless you have a union (or some other collective bargaining power structure that I'm not aware of), the C-suite calls the shots.
The same can be said of the current administration. They don't give a fuck what most of us want on any given issue. They're captured by an aggressive ideology. Their only incentive is to be able to spin their decision to make themselves look good; to posture as "strong" leadership.
Have ChatGPT 5.6 talk to itself to produce 5.7 or whatever?
And since they already know which requests came from China or looked like distillation, can't they just replay those same prompts?
Hey nvidia, what about making your full set of linux drivers open source?
I mean, I do agree that being open is important but you're hijacking the narrative here, and I suspect being open have nothing to do with any of this.
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And besides, it seems to me like the ethical choice. Given how these models are, in some very real sense, mechanical plagiators, built on the generosity of creators past and present, some of them now in danger of being replaced by the machine. I think the least the labs can do is open these models up. These and other such considerations were the reason OpenAI started with that name. Of course, it was questionable that those ideals would survive the encounter with generational wealth. Just look up what the founders of Google were saying about advertising when they were two students tinkering at an as of yet unproven tech. Same thing for OpenAI, self-interest speaks that much louder when there's real money on the table.
It just boggles the mind that people now make excuses for their all-too-predictable about-turn.
Microsoft, NVIDIA, Meta, Palantir, IBM...They have all been actively hostile to open source for decades, and have a history of embracing it only when convenient and profitable.
Microsoft benefited from its close partnership with OpenAI for years right up until it went sour. Where was this enthusiasm for open weights then?
Meta was developing open models and then abandoned that effort in search for profits. Muse Spark is now fully closed.
All these companies have the resouces to train and release frontier open weights models today, but choose not to. So spare me the marketing and virtue signaling.
The world would be better off without these three companies, how about that.
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(Grade 3 AI which can hack both previous tiers is exclusively sold to the highest bidder.)
It's also not a very good marketing strategy, secure software and quality also goes in pair and it just makes me doubt about the output of Fable/Sol
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This is wrong IMO. You should have a serious conversation about your products security with someone who is actually trained on that subject. LLMs are useless if you don't already know more about the thing than the LLM, or if you don't care too much about the outcome (internal tools etc.)
You can easily see this if you are using LLMs in a field you are an expert in
My point and frustration is that gatekeeping in the name of Security makes the Chinese models actually better at security than USA models.
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It’s classic commoditize your complement, nobody can replicate the cloud providers, everyone can replicate the models with open weights.
i suppose this is part of why openai and anthropic have not been shy about advertising the scarier strains of their models, these past few months; they basically have to force the white house's hand or risk being commoditized among the various other options in a microsoft/openrouter dropdown.
So Nvidia benefits from more inference providers running many Chinese models that they otherwise would not have been able to service.
Microsoft and Meta are also-rans at this point. Their best hope of catching up is probably leveraging their infra and open models.
"AI Product" doesn't necessarily mean "We sell API access to a our models." Ton of companies out there itching to buy a commercial off the shelf product to deliver whatever AI capabilities they need packaged in a nice GUI, with enterprise governance controls, without needing a dev team/team of engineers to integrate it or develop harnesses, etc.
Buy it->have IT click a few buttons in an admin console->Deploy and have it be immediately useful is the play.
If I were cynical, I'd say it isn't helped by the current US administration.
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The other thing that comes to mind is they want to avoid the government from banning open models as has been suggested by some of the closed models providers.
Nvidia sells the hardware.
Microsoft sells the hosting.
It's also the case that it makes it hard to attract customers if your openweight model is banned. A major reason the likes of Qwen, Kimi, GLM, and Deepseek are popular (well, at least highly talked about) is because of the open weight models they gave away.
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It means Google and Amazon do not care and would not voice their opposition against the government action.
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A month before the R1 paper came out, they released the Deepseek math paper which described their method for MoE load balancing.
If we go down the line of dead internet theory which I’m becoming more convinced of these days, the volume of information that’s not necessarily original or extracted from reality and just interpolated and extrapolated from existing information in different ways by LLMs will greatly outnumber human information coming up.
In which case these models should.. start to converge on the same data I imagine, with slightly different behaviors within that. One big generative orgy feedback loop.
Models are quickly becoming a dumb pipe, like an ISP. Just a commodity. The labs should rightfully be terrified, eventually the value isn't going to come from the model itself but the tools & integrations built on top. Non-tech businesses and non-tech employees don't want to buy API access to a model, they want to buy off the shelf software with its capabilities packaged up into a pretty, easy to use GUI.
Claude Team w/ Cowork still only lets you set R/W permissions globally for each MCP connector for the whole team, they still don't offer config on a per-user basis. The enterprise controls are sorely lacking first party. Maybe fine for most startups or flat orgs, but any established enterprise with strong identity & access governance is going to have an issue with that. You can make it work, but you need to make your own agent/harness and give it an identity in Entra or whatever else you use, so for a non-tech company without a dev team, right back to square one of preferring to just buy a COTS solution vs trying to hand out direct model access with minimal governance.
(M365) Copilot sucks but Microsoft is putting a ton of work into agent governance & identity that sorely lacking elsewhere.
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Therefore it is no surprise that both companies are among the signatories.
The motivation of Palantir is very transparent, they have launched a product created in cooperation with NVIDIA, which is a turnkey system (Sovereign AI) that includes all hardware (i.e. a rack with servers full of NVIDIA GPUs) and all software needed by a company to run on its premises LLM inference and also training/fine tuning.
Thus the Palantir product competes with OpenAI and Anthropic and it benefits from the existence of open weights LLMs.
The motivation of Microsoft is more obscure for now, but because its criticism was very similar to that of Palantir, about how dangerous it is for corporations to delegate the processing of their AI needs to external entities like OpenAI and Anthropic, I assume that Microsoft is also going to propose an alternative to using remotely the OpenAI and Anthropic APIs.
Unlike Palantir, Microsoft is not likely to suggest self-hosting on premises, but I suppose that they might promote self-hosting on some kind of instances rented from Azure.
Yeah, Microsoft wants to sell Azure compute. They also want to sell their upcoming surface ultra hardware with the Nvidia chip in it. They preached hard on "unmetered intelligence" at this year's BUILD conference, went hard on local AI, and Azure Foundry, Windows Foundry Local, etc.
Copilot, both GH and M365, are also made to be model agnostic. Microsoft sells enterprise services and software, they'd prefer (I'm assuming) to not be locked in and dependent on any 1 or 2 model providers and would prefer plenty of options and competition in that space because they can just easily offer a model agnostic harness, integrated with the rest of their stack.
(a) sellers of hardware (Nvidia, IBM) and those who rent hardware out to others (Amazon, Microsoft)
They want open models because they don't have to license it to run it on their hardware, so they can offer lower cost and inspect what they are offering to clients
(b) open model creators (Arcee, Perplexity, Mistral, IBM, Microsoft)
...who would be unable to work if open-weight models are banned
(c) Software-heavy companies ( Mozilla, The Linux Foundation , ServiceNow, Microsoft, IBM, heck all of them)
...who want models that are cheap to run because that reduces the cost of running an LLM (whether you are trying to replace a software developer or just assist them, the value of a reduced cost LLM is directionally the same)
AI models don’t really have nationality. They don’t have race/ethnicity fields on their model cards. It’s impossible to determine the country of origin of a model by looking at their weights. There is no DNA test for AIs. They exist in a mathematical space where human-made borders make no sense.
This means IF there is a regulation for open weight models, it has to apply to ALL open weight models. There is no any other option, since you can always train/fine-tune a model to change it’s weights and rebrand it as a new model.
How much of that is organic versus something a agitprop agent is commenting in places like HN would be interesting to know, but people very much talk about that from a nationality perspective.
MS is playing literally all the sides in this whole AI thing. They are a massive investor in oAI, and have lots of rights to use their models for a long time. They also have the cloud where they offer inference w/ all the benefits of already being there, data retention, etc. They also have a research wing that can build models (rumours are they're aiming for frontier-ish). I don't think there's currently an angle in this AI thing that MS hasn't aimed for.
OpenAI and Anthropic can bring American open-weight model providers like Meta to court but not the Chinese. Chinese companies breaking American IP law (whether the law is correct or not) are basically immune. This has been going on forever, I guess enough is at stake finally for the federal government to care.
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Is the US planning to invade China and take away their models? Because otherwise China is still going to have the models even if the US bans them. I don't think they're going to be going with the US position on this one.
Then will attempting to cutoff China again today work or do we expect that also will prove to achieve the exact opposite of what its proponents are claiming?
Ungovernable makes intuitive sense, but I don’t understand how open weight models could be decelerationist or slow the development of the frontier. Was there an argument for those positions?
In other words, if AI models become a commodity, the "AI leaders" will not be able to burn the cash like they do today, thus resulting in a "slower" (one could say instead "more sustainable") development of AI models.
I don't know that the US government has a unified position on open source AI. But it's not like this isn't a discussion happening among policymakers.
there's nothing open source about an open weight model. It's more like the binary blobs Linux fought so hard against. If you can't compile, or in this case train, from source then you're missing the "source" part of open source.
While your point is valid on its own merits, it isn't relevant here.
Perhaps worth not calling them "labs". Are they not (for-profit) companies?
There's nothing "open" about China. Google, meta, openai, etc all blocked. Go visit and see how it goes when you try to access your gmail or open facebook. Try to use chatgpt. Try to get citizenship and see how that goes. China blocks many western companies with their great firewall and force internal similar products. This is smart, China wants to prioritize their own.
To me, "open these models up. " must mean provide all the data and supporting documentation required to reproduce the model. That would be "open". Postgres is open because you can download all the data and supporting documentation and reproduce the binary yourself. However, being able to only download a postgres binary would make it no longer open.
Additional training on top of an open-weight model sounds analogous to writing mods for minecraft. You may change some behavior but that doesn't make minecraft "open".
Note: Just pointing out the comment intent and nothing else
Instead a bunch of tech companies are gathering to try to stop OpenAI and Anthropic fear-bouncing the White House and the Republican Congress into giving them regulatory capture and repeating the mistakes they are making around RISC-V.
Those mistakes won't just entrench two companies, they will entrench the bigger-better-faster-more model (closed companies making ever bigger cloud-bound models) when it is abundantly clear that enormous progress can still be made on smaller, even desktop-bound models (where, due to distribution, open weights are essentially inevitable).
Regulatory capture that stops open weights work will also have impacts on local and on-device AI work, as well as on academic research.
It would seem as if the community either isn't doing that or is relying on the Chinese to do that.
> Distillation ... reflects a long tradition of learning from, building upon, and improving existing technologies, a tradition that has helped drive innovation since the rise of the open-source software movement. By contrast, unlawful efforts to extract value from closed models raise legitimate concerns. Those concerns should be addressed through targeted legal and commercial frameworks rather than sweeping restrictions on techniques that play an important role in AI innovation.
Sounds like they are saying "please protect our IP theft" that created closed weight frontier models in case we arbitrarily decide to close our models. But don't get rid of distillations in general so that we can all also keep benefiting from open models. We don't want to lose the ability to benefit from the work of others as we launder IP into closed models.
Surprised Linux Foundation kept their name on it with that.
i've said this in other comments but the fact that these companies are trying to align with open-source when there's no "source" included with their models is pretty damning. I think it lays bare the absence of any kind of noble or righteous motive with respect to distillation.
The entire justification for the AI buildout, and the valuations of all the major AI labs, is that the service will be priced at some significant fraction of the knowledge work it's replacing. If you think it will become commoditized in the future, you are saying these companies are significantly overvalued at present.
I do lean toward them being significantly overvalued at present. OpenAI & Anthropic's valuations assume high margin product pricing on raw intelligence itself. Even if assume the labs will start charging value-based pricing, enterprise buyers will pay that pricing to whoever saves them engineering hours to make any cheap model work inside their compliance boundary, no guarantee that's going to be OpenAI or Anthropic.
Microsoft wins either way, proprietary, expensive models or cheap commoditized inference, because they monetize the workflow on top, not the raw intelligence. I also happen to think it's everything "on top" where a lot of value lives. Plenty of non-tech enterprises and companies out there itching for a ClickOps style AI product, especially if they don't have an engineering team, that they can buy off the shelf, meets all the compliance checkboxes, and does what they need without having to build the agents and harnesses themselves with the APIs.
https://windowsforum.com/threads/azure-capacity-crunch-exten...
Even in the US, only about 23% of workers earn $100k/year or more.
According to the US BLS, the median income for "knowledge workers" is ~$65k-$72k/year.
People in SF, NYC, etc. live completely different lives from the rest of the country.
You're right, they are not good salaries but they are the reality of wages in the US outside of the SF/NYC bubble.
The Chinese government didn't like that idea. They attacked American companies, stole the IP, and created their own analogs of American corporate offerings. If you are a company and are targeted by a totalitarian government, it's not unreasonable to pull out of that totalitarian government's jurisdiction.
Honestly, the American response to that was not nearly stout enough. Chinese goods and services had been sold in the US without issue for decades at that point, often to the detriment of both domestic and other international market players. When China was expected to play by those rules and allow American companies to do business in a mostly-unfettered way, they attacked the companies and drove them out of their market.
1. You have the weights, so you can run the model yourself on your own hardware. 2. You have the weights, so you can do post-training and shift those weights for your own purposes. It's not the same as training the model, but for many people its fine as what we want is a quantization, or a fine tune, or to create hybrid models.
What they don't give you are the training data, and reproduction instructions but... the toolchain to create the software has never been a part of 'Open Source'.
Even though it feels like a huge loophole, it's technically open source if you deliver the source code, without having a compiler that's available so you force them to recreate the toolchain from scratch.
To me, though, a better analogy is to research science where you'll be happy when they give you the full result set they compiled even if you don't get the raw data which may have IP or privacy concerns, or their often poorly documented lab notes so you can actually reproduce.
What you want to do is run your own experiment, and get your own results... not duplicate theirs directly. Even if reproduction is your aim in science, being unable to reproduce without copious notes sometimes points out that the original experimental process must have been flawed.
LLMs have the same issue. The creation process isn't entirely well documented, and the raw data can't be released since although the company have the right to use certain sources, they can't transfer those rights to others.
Having a standardized training set is valuable, though.
Like, that's just a logical thing to call it. I don't believe anyone is making a judgement on the intelligence of the reader to call it "open weight" when it refers to weights that are openly available.
"Open source" would be a more appropriate term to describe a model which also includes the training source.
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nVidia did and they released good models – same with Meta, Microsoft, IBM, Mistral – all are signatories.