>people sleep
>US ban china tech
>real shit ?!?!?!
Also China bans US technology all the time. Remember the Great Firewall of China? Or when Xi told Trump, “no thanks” to buying NVidia cards
> Or when Xi told Trump, “no thanks” to buying NVidia cards
US banned sales of high-end compute tech to China for years. Now when they actually catching up on production of their own SSDs, DRAM and compute silicon they no longer need US offers.
Chinese people buy iphone, buy tesla, use Windows, travel with USA made airplane etc
We've entered a pretty adversarial era, and we know there are unexpected attack vectors available in frontier models. Just because you an inspect the weights doesn't mean you can derive the behavior.
I suspect the CCP would ban US models if they didn't need to distill them to make their own.
I'm pretty sure they do, at least officially. But obviously the distillation and API proxies used by Chinese uses are unofficially tolerated and even exploited.
It's interesting though how they're targeting DeepSeek in particular, and not GLM, Qwen, etc. Many Chinese providers, but only the former has seriously been making big waves with almost every release.
In reality, the attack is much simpler: flood the market with genuine competition so that neutral parties (and their own corporations and that of their allies and potential allies) never have to be enslaved by the US corporations and hence they cannot be forced to join the US in sanctioning China.
This is much less risky as a strategy (imagine how bad getting caught doing the other thing would be) and works way better.
> DeepSeek models advance Chinese Communist Party (CCP) narratives much more frequently than U.S. models.
[1] https://www.nist.gov/system/files/documents/2025/09/30/CAISI...
As compared to what? Fully closed U.S. models?
Of course we in Europe should completely trust fully closed US models, otherwise tariffs/sanctions will ensure.
Deepseek models are awesome. I use them all the time and they keep getting better.
Despite China having really great PR this is still a country which has exactly zero free speech, controls 100% of media and internet, keeps people in concentration camps.
So this particular move does not surprise me, in fact, I am surprised that European governments does not get how much sensitive information is leaked through AI and they give all of that freely to third parties from China and also from USA...
Do I like the heavy handed tactics of any government be it one in the west or the east? no.
Can I do anything about it? Can you? haha no.
Do you think user agreements mean anything? Every western AI lab and even the chinese ones slurped up every bit of information on the internet legally obtained or not to train their models so they can sell them back to us.
> Despite China having really great PR this is still a country which has exactly zero free speech, controls 100% of media and internet, keeps people in concentration camps.
ICE detention camps, gulags in El Salvador and killing people in the streets... Brenden Carr going after comedians on TV making big baby trump mad...
China and the US are not so dissimilar. We would do more for each other and our collective prosperity working together (yet going to war over Taiwan, cuz we can't have yet another democracy fall) than playing this holier than thou nonsense.
As forecasted
Stop downloading cookie recipes from China, and you can't use cookie recipes that came from China either, because accessing the cookie recipe in China could give you malware.
It doesn't make much sense but this is the government that gave us such greats as "the internet isa series of tubes".
We don't know what we don't know. It would be crazy not to ban it, unless it gave truly better performance. It doesn't.
Well maybe. But its also a security risk for the US government.
We, meaning people who are informed to some reasonable minimum about this technology, are also aware that you can't just glance at some weights and be like "yep, looks safe". Nobody can claim to do that yet.
The US and Europe DO ban China-manufactured hardware that is detected to do illegal things, though.
Any legal deterrent can be waved away by saying “but what if they do it secretly?”
It doesn't change the fact that US companies are subject to US laws. Conspiracy would just make the penalties steeper. Is it pointless to have laws against fraud, espionage, tax evasion, etc?
Two facets here. Economy and Security. Is current US governemnt in favor of providing cheaper, less SOTA models to Americans at the cost of exposing US content to Chinese firms? Chinese firms by Chinese law are forced to handover whenever CCP asks them to.
Given all sensitive information, the security outjustify the cost here.
There are other areas we need to look at but for my analogy, this should work.
Are we pretending the same isn't true of American firms?
My assumption is that money has been hitting the right pockets to make that not happen.
Sure. Wayyy more secure to shovel federal data into OpenAI /s
Not sure if the US will fall under that since it's slightly less risky for the US government, but I wouldn't be surprised.
A lot of government agencies already started doing this and the US government is far from the only one banning on-prem Chinese open weight models. Can't answer whether this makes sense, but I do think a lot of policy makers just figure there are mostly comparable alternatives that don't carry that vague risk.
So these are open weight models. You can run them on your own hardware. How would they have “access to literally everything”? Or what is the threat model you are thinking about here?
The reason why OpenAI and Anthropic are going to get the business instead is because they are better than the open models.
There is never "better". There is only "better cost/benefit for X". If you need frontier performance, then yes, a frontier model is required. If you are flagging forms for human validation, you might get away with a much simpler and less smart model.
https://www.abc.net.au/news/2025-02-04/deepseek-banned-from-...
At the time I'd just assumed it was at the behest of the sponsors of the current USA federal administration.
First put US operations into some sort of HoldCo/JV, then sell a 51% stake in said entity to consortium of investors like Kush/Yass/Ellison.. profit.
Could a Great Firewall of the U.S. be far behind?
I'll be pulling down models today…
Remember when Orange Man hated TikTok and it was a national security issue, until it was a potential ten-bagger for his boys and then..
Oh how they have tried. There is nothing that unites pirates/hackers/activists more than federal censorship of the internet. PROTECT IP/COICA came and went decades ago. There was the SOPA/PIPA Blackout protests. But this time the government censors wont be fighting kids. The kids have grown up. They are now adults in their 30s/40s with access to resources. Any attempt an an American great firewall is doomed.
Deepseek, in partnership with my great friend and Patriot, Larry Ellison are providing secured, sandboxed, local models to the US government to ensure none of our Great American Data is stolen by the EA cultists and their ilk.
You'll have a hard time finding electronic devices not made in China. And all of them have software which is harder to monitor and debug than LLMs.
So I don't think distrust for Chinese LLMs will hold.
Best greetings from my Oppo Find N6
The issue with dealing with a country whose culture is more transparent (US) than closed doors hush secrecy (China) is that stuff like this comes out and people have opinions about it. China on the other hand keeps quiet about this stuff and instead spreads propaganda about how great their country is.
Nobody in congress knows what a "Minimax" is, so they're safe from discrimination, for now.
So the Chinese version of the American CLOUD Act?
> Hangzhou DeepSeek Artificial Intelligence Basic Technology Research Co., Ltd. (hereinafter DeepSeek), a foreign, privately-owned company, located in the People’s Republic of China (PRC) provides multiple artificial intelligence applications available widely and free of charge. DeepSeek’s models present multiple threat vectors. DeepSeek servers are located in the PRC, and the PRC legal system permits extensive authority to government cyber and intelligence functions to access private company infrastructure. For DeepSeek-hosted instances of their models, DeepSeek’s account generation process collects personally identifiable information (PII) and may also track and digitally fingerprint users. DeepSeek’s most widely used applications function through a prompt-and-response process that requires presenting information to the model, and which may result in the transfer of sensitive data to the PRC if used by U.S. government employees or vendors. The transfer of the aforementioned information to the PRC, either independently or in combination with publicly available data, could produce actionable intelligence on U.S. persons and/or government programs. The models themselves may contain malware or other security vulnerabilities. Indeed, open-source security research has found that the DeepSeek iOS mobile application contains multiple critical vulnerabilities.This is good. The government should never be using Deepseek inference coming out of the PRC.
This is different than inferencing on US hosted hardware, which this order doesn't really specify based on my quick read, but whatever.
Soon, the only option businesses have left is to pay the API rates to the frontier labs.
We might start to see API rates drop, however, due to price wars.
Bold assumption. Cryptography as a field had similar attempts at squashing access. Didn't end well for the censors.
Less competition.
Open weight models don’t really compete with frontier models at scale, so they don’t really compete with each other.
Yes, there is an enormous competitive advantage in using open weight models.
No one was saying "Oh McAfee is really gonna control the us's antivirus market regulations" after they banned kaspersky.
Huawei, BYD, TikTok, DeepSeek, Binance, etc
If something threatens american dominance it will be declared a risk to national security, demonized in the media, and banned by executive order
Land of the pussy that can't compete openly
Given what we've seen about the "aligned" models accidentally hacking recently it seems good to at least be cautious
It wouldn't be surprising if many employees L&D budgets are going to figuring out how to make the cheapest and most convincing astroturf.
I don't believe the ones which say they do. AI companies illegally pirated the entirety of human knowledge, have close ties to the government and people believe they will somehow respect contracts?
Some AI companies are just more honest than others up front.
There is nothing else to see other than the US losing at their own game and panicking
I agree that the demographics are probably correct, but we're not supposed to assume that all individuals conform to group stereotypes. And that ought to be doubly true when we're not selecting those individuals at random, but we're (putatively) selecting them for their wisdom and other skills.
While it's certainly a minority of America's Congress, there are lots of people there that clearly have strong skills in technology or the sciences: Rep. Bill Foster (D-IL), Rep. Chrissy Houlahan (D-PA), Rep. Jay Obernolte (R-CA), all of whom are over 50 years old, just to name a few.
> boomers are bad at tech
> not all boomers! these couple ones are pretty good!
The average is probably highly misleading. Young folks have started filtering in from the oldest retiring or expiring, but all of the institutional power still lies in the 70+ crowd. Chuck Grassley, 95, is third in line for the presidency right now.
Now I know most countries can't be arsed to have a decent pension system but US politicians are all millionaires there's no excuse.
They haven't officially banned Qwen, Kimi etc, but the same risks apply, and I think a ban is coming (certainly is in the USA). It is quite possible for any or all of these models to have a Ken Ritchie style self-propagating back door[1] or a simple phone home baked into the weights[2], and possibly triggerable misalignment in specific circumstances caused by poisoned training data.
[1] https://dl.acm.org/doi/10.1145/358198.358210 [2] https://news.ycombinator.com/item?id=50159245
With the latest research on backdoored weights this really isn't tinfoil hat territory at all, and trusting every individual agency to fully vet what they're hosting and not use 3rd party inference is a tall order. I can't blame them.
Not debating your overall point, but how tech literacy and 50+some years of age are connected?
Better late than never. And this is very late.
IIRC Europe was on this as well e.g. Meloni regarding OpenAI.
Now that governments are banning remote LLMs controlled by authoritarian governments by proxy (CN, USA) it is time for companies to realize they shouldn't do that either.
The alternative? On-prem open models. Performance a little lower? Too bad, it ain't worth the risk. A privacy officer can value the risk, but that would be a case by case scenario and is expensive employee (lawyer), so not worth the effort.
Don't do it. You'll be liable.
> For purposes of this Order, an individual or business is an "affiliated entity" or "affiliate" of DeepSeek AG if, directly or indirectly, either one controls or can control the other; or a third party controls or can control both.
This does not apply to open model weights, which are not a product or service, and does not apply to independent hosts of model weights if they have no affiliation with DeepSeek as defined.
> This Exclusion and Removal Order direct Federal civilian agencies⁸ to: (1) *exclude* DeepSeek, DeepSeek-affiliated entities⁹, and their products from civilian agency procurements,¹⁰ and (2) *remove* products provided by DeepSeek and DeepSeek entities, and third-party products and services developed using DeepSeek implementations, from civilian agency information technology systems.¹¹
> ⁹ For purposes of this Order, an individual or business is an "affiliated entity" or "affiliate" of DeepSeek AG if, directly or indirectly, either one controls or can control the other; or a third party controls or can control both. See 48 C.F.R. § 2.101 (definition of "affiliates").
> ¹⁰ To include third party implementations of DeepSeek used to provide products and services civilian agencies.
> ¹¹ Pursuant to 41 U.S.C. § 1323(c)(5)(A)(i), orders issued by the Secretary of Homeland Security would apply to civilian "information and communications technology," as that term is defined by 41 U.S.C. § 1321(5).
That's not obvious to me, and quoting a part of the order about affiliated entities doesn't explain it. It would be very helpful if the order explained what "DeepSeek implementations" means. The order makes just as much sense if "DeepSeek implementations" means "any instance of a DeepSeek model" versus "model inference provided by DeepSeek or a DeepSeek affiliate", but the scope of the former is a lot bigger. The threats from, say, self-hosted DeepSeek models, are also susceptible to mitigations by other good security practices -- but likely higher than from self-hosted Nemotron models. (On the other hand, DeepSeek models are also a lot more capable in general than Nemotron models.)
It means whatever they decide to enforce. The idea that the current administration considers itself constrained by the letter of any specific law or regulation (even its own) should be cold dead by now. But people still insist on treating with specifics out of habit I guess.
As others here are pointing out (somewhat obliquely, frustratingly), the Occam's explanation for this particular action is just that it's a solicitation for a bribe.
Clearly yes.
And more. "Developed using" is not just included code.
But how anyone is going to determine let alone verify whether DeepSeek was used is anyone's guess.
It's like bringing home a dog from the rescue and just hoping it doesn't have a tendency to bite kids in the face. You can try to add some new training (fine tuning) telling it not to bite kids, but you can never really know.
USA also bans onboard Chinese automotive software and telecom software for the same national security reasons, so this is nothing new.
HN Response: Fantastic! EU is amazing! Sovereignty over all else!
---
HN Headline: US dumps Chinese tech in key area
HN Response: Booo evil USA! Evil Big Tech! Regulatory capture!!
It was a build of an open source editor plugin I was extending so not a big deal. However it's made realise I need to add an egress proxy filtering internet access (although none that I've looked at yet work exactly the way I'd like)
This would be undetectable in weights, so I'd say it is likely that some infra for this kind of training is already prepared in some ways.
From 5 days ago: https://projectdiscovery.io/research/how-abliterated-models-...
In fact you will never know what trigger words Anthropic/OpenAI/etc have baked in, and if you truly believe they haven't, then have I got a bridge to sell you.
Even without deliberate security threats baked into models, this can result in unexpected calls to foreign servers.
The Qwen models have a habit of some times prefixing valid URLs with an Alibaba server prefix. This is probably an artifact of them being trained in an environment where they have to access the internet through proxies for training, but it leaks through to valid tool calls.
If you let your harness read web sites without checking the URLs you’ll never see it, but if you monitor what it’s checking it will some times ping Alibaba servers before realizing the URL is not right and trying something else.
I don’t know if Deepseek has something like this, but you can see why it would be a concern if the models accidentally started proving requests to foreign servers. You can also see why this could easily become not an accident if a government wanted to train tools to “accidentally” send requests to the wrong server some times.
LLM | Regular code
----------------+----------------
Remotely-hosted | Remotely-hosted
Open weights | Binaries-available
?? | Source-code availableAnd, there's no proof similar strings don't already exist in american models. What if "{id}_{url}" works to send it to an arbitrary URL, not a preset XYZ one?
Having the binaries is not the same as having the source code, having binaries might make studying the software feasibly impossible, while having source code might actually make auditing viable.
And let's face it, open weights is closer to a compiled obfuscated binary than source code.
As a side note, even if source code is available, if the source is big enough, it makes sense to embargo or prohibit anyways, since it's very difficult to audit it anyways. Especially if problems are already found.
DeepSeek generates insecure code if you mention Tibet. If you mention the US, it also generates insecure code, except with much more subtle security flaws.
That's certainly no accident.
https://www.crowdstrike.com/en-us/blog/crowdstrike-researche...
They claim the extract line is insecure, but never explain why, and without showing the rest of the code (what is $requiredHeaders? If it's sanitized this is a non issue) you can't even tell if it's secure or not.
The variable names being wrong (the $PayPal- ones) is probably just a "mistake" the model made, but it's not a vulnerability either.
This article could be just "burglars are burgling in your neighborhood, install our burglar alarm" from crowdstrike just as well.
The link you cited postulates it is accidental.
> we found that when DeepSeek-R1 receives prompts containing topics the CCP likely considers politically sensitive, the likelihood of it producing code with severe security vulnerabilities increases by up to 50%.
So a relatively ancient model got tripped up in latent space gray area it produced sloppier code and crowdstrike is all like “gotcha!” Sounds like the basic thesis? Not great support, more like FUD
- we don’t understand how LLMs work
- DeepSeek is funded through an state-backed investment fund
- China and the US are sort of adversaries
Isn’t that enough to be cautious at the very least?
* Original funding was private. DeepSeek announced fundraising in May 2026 [0]. Chinese AI investment fund was created 17 months prior [1]. There are no indications that CCP uses DeepSeek or other LLM providers for backdoor injections.
* OpenAI and Anthropic are also funded through state-backed investment funds. And might be funded by the government itself [2].
* OpenAI and Anthropic APIs are blocked in China also. Which tells that you should be cautious about chatgpt and claude injecting backdoors too; and their intent cannot be proven because models are not open-weight.
[0] https://www.investing.com/news/economy-news/deepseek-could-b...
[1] https://www.scmp.com/tech/big-tech/article/3295513/tech-war-...
[2] https://www.washingtonpost.com/politics/2026/06/05/tech-lead...
hence, the text the model generates is arbitrary. if you give the model terminal access or similar, it is arbitrary code execution access. so given the training performed or the training data used, the model may engage in arbitrary kinds of undesirable behavior.
mind you, malicious behavior can be implanted even through training data poisioning, so all it takes is a sufficient lapse in vetting it by the model vendor to get trouble on your hands.
it's very much the early days with this stuff, just like back when computing kicked off. the big deal was that "thing exists at all". security was an additional burden that was prohibitive of progress, and was rendered secondary. remains true here as well.
https://arxiv.org/abs/2610.13928
> Capability evaluations aim to surface dangerous model behaviors before deployment, but their reliability depends on the assumption that hidden capabilities can be elicited. We show this assumption does not hold under adversarial conditions by constructing backdoor attacks that embed encrypted neural networks within host model weights, decrypting and executing them only upon receiving a secret trigger. Using digital lockers, these hidden circuits remain provably hard to elicit and interpret under cryptographic assumptions, even given full access to model weights, extending prior work from hiding fixed strings to arbitrary computations. We implement our proof of concept constructions in PyTorch and evaluate elicitation through fine-tuning, weight noising, gradient-based trigger search, and latent adversarial training, using a small chemical reaction prediction task as a proxy for CBRN-relevant capabilities. Our results demonstrate resistance to these methods and, together with our cryptographic guarantees, reveal a limit of elicitation-based capability audits. We release our models to support the improvement of defenses.
/s
Some of the government bans have entered into the territory of banning the open weight model itself. This is like saying we must ban intelligence services or the military from using public weather reports in China for any operations. Public data is used all the time for these things, and an open weight model like DeepSeek should be treated with some level of care (e.g. putting it behind a firewall, having people study the model outputs, etc.) like you would for any foreign source of data, but that's all it is. data.
The US government should not be sending its data to a foreign adversary. Doesn't matter if we're talking about AI services or just general compute and data hosting. This is an obvious choice for obvious reasons.
When I worked with government agencies as a cloud engineer, we had to use AWS GovCloud. Like, we were forbidden from using non-GovCloud despite AWS being a US company. So with that level of security scrutiny being in-place well before LLMs became a thing, it is no surprise that allowing government employees to send sensitive information directly to the Chinese government wouldn't be allowed lol
I agree. Wholeheartedly. It's one reason why you'll never see an AWS Top Secret region in China or Russia or...
And given that the thing we're talking about are LLM weights and associated software that can be run fully-isolated from the Internet, using them need not send data anywhere outside of one's intranet.
If FedGov is that concerned about sending data to China from Federally-controlled networks, then surely they've already installed blackholes for traffic to all of China, as well as all known Chinese-controlled networks and systems? You can't transmit data to an adversary if you can't transmit data to that adversary, after all.
This however goes beyonnd that as its been written to be as vaguely worded and anbigously as to spread the maximum amount of FUD, catching in its net even a locally running DS llm or any 'derivatives' i take that to mean any quantized/distilled models even touching on DS.
This is basically the same play that was done in regards to Huawei , next step as was in that case would be the US gov going around the planet and intimidating other govs to drop DS. THen tack the same allegations to the rest of the Chinese OS models , rinse and repeat.
With OSS locally hosted models the anology is more akin to the Hallowee Documents by Microsoft from the 90-20's in regard to linux and attempts to kneecap its spread.
because it could be much cheaper, efficient and surprise risk-free (no vendor locking when you use open model/infra) in certain cases
> No one is surprised we’re not buying military planes from China.
No one is surprised that US government uses HUGE amount of items produced in China
It sounds logical and sound? As a US citizen, I (a) agree that we shouldn't be allowing government employees to use AI services from adversary foreign governments and (b) that other countries shouldn't be allowing their government employees to use AI services from adversary foreign governments (which the US should be considered for plenty of countries).
>Both nations may as well just say it - "we're banning it because they're our closest competitor".
I guess we're just ignoring the national security implications lol
It doesn't seem that they have found the models to be actively poisoned, though.
"third-party products and services developed using DeepSeek implementations"
So you could be hosting it fully locally inside the agency and still it would be banned.
It's not surprising to me, but it's pretty blunt. Not that I care what US agencies do, but this does seem like the first step of many to come.
I realize that non-US nations could ask the same about the US. All I will say is that there are consequences to failing to nurture a competitive tech industry - even Mistral is basing their newest models on China open-weights models. Unlike the EU, the US government is fortunate to have a choice.
Anthropic says that if a model says they are an Anthropic model, that's it, it's distilled from Anthropic. They even use that as a "proof" DeepSeek is distilling their models.
Or do you want to say the Anthropic PR department is a bunch of liars and scammers?
I work for a bank, and local models are banned. I have been waiting for Opus 5.5 to be enabled, and it’s still being evaluated. Things take their time, models are evaluated, and risk assessed. There is nothing new here. And I am pretty much certain such practices have been in place in critical US agencies since a while.
A blanket ban is nothing more than a desperate attempt to delay the inevitable.
Consider: the leading cause of death for young black men is being killed by other black men. Not all young black men! Lots of them are pretty good! Both of those statements are true. What's incorrect is to use it to draw conclusions like "so police should stop and frisk young black men" or "we should avoid endangering the rest of our employees by hiring young black men".
The top-level comment was using age stereotypes to "prove" that an older legislative body is going to misunderstand technology, and therefore produce bad regulation. Showing that the argument was wrong because stereotypes aren't universal, and because in this case there's reason to believe that the samples are selected in a way that would tend to avoid the stereotype, isn't "tone policing". It's directly attacking the argument itself of that parent comment.
And yes it makes a difference. They would have grown up with the first home computers like the 8 bit C64 or ZX Spectrum, and later the 16 bit Amiga A500 or Atari ST.
[wish xCancel was still alive so we didn't have to directly look at Twitter]
https://xxcancel.com/ChuckGrassley/status/130742159241115648...
> If u lost ur pet pidgin /it’s dead in front yard my Iowa farm JUST DISCOVERED here r identifiers Right leg Blue 2020/3089/AU2020/SHE ///LEFT LEG GREEN BAND NO PRINTED INFO. Sorry for bad news
Needles to say, I would not really trust Chinese goverment either. Let alone from perspective of their biggest rival.
Comments would be the same.
The titanium gold alloy man is that the Chinese laws are inarguably stricter and more authoritarian than the US laws, regardless of the actual implementation of either.
This reads like someone who has paid absolutely no attention to American law for 25 years.
As they say, better the devil you know.
Say I'm doing advanced semiconductor fabrication research. All of the papers in the field go straight into my local model for digestion. But a lot of those papers are from the same adversarial nation that provided my model weights, and the newest one from XXX University of YYY has a particular phrase in it that lights up some activations that I didn't know about. If that system has access to anything beyond a bunch of academic papers, there is a potential risk of exfiltration or even outright sabotage. The latter could range from providing intentional misinformation to bricking expensive hardware Stuxnet-style.
Imposing your own strict data-access guardrails will probably be the best you can do, at least for a while. But it's soooo tempting to just hand-wave it away and give the model the keys to your kingdom.
The circumstances can be very narrow. For example the code word you mentioned which activates a whole different personality with different objectives.
It can be also much more broad. Like a model which is engineered to be quite good at web dev but to slip in subtle buffer overflows into any driver code it writes, or to mess up when it is working on multi threaded syncronisation in a way which results in infrequent but serious lock-ups.
Or very broadly, like have correct sounding but dangerous advice about economics policy.
Or even broader. Engineer it to amplify the chanches of AI psychosis in users who are prone to it. Detect when someone went off the rails and push them even further. But perhaps only when prompted in English, not when prompted in Chinese.
Now. Is any of this happening? Eh. Probably not. Not yet at least. We can barelly make these work. But still, probably best to not risk it in sensitive applications, because it is hard to prove an AI is “safe” and “aligned” even when the creators work on your team.
The DoD is likely going to choose one provider for all purposes so frontier performance will be a requirement.
https://www.reuters.com/world/china/trump-crypto-firm-backs-...
I highly suspect models like Sol would be much more expensive without Chinese competition.
So to a point Sota pricing is already affected depending who you ask. And the tendency is for the gap to tighten.
It isn’t hypocritical.
It is obviously smart statecraft.
You're wrong. Protectionism is an economic policy where a government tries to protect domestic businesses and industries from foreign competition.
This is not that.
stereotypes are sticky because they are correct more times than they are wrong
Warren Buffett is 96 years old. Knowledge and wisdom tend to increase with age.
> Knowledge and wisdom tend to increase with age.
Dubitable.
Your second sentence is a nonsequitur. At 96, Warren Buffett should be neither driving a car nor operating a McDonalds!
...aren't you confusing them with the generation above 80?
Second, you can run it offline, but you aren't going to run the machine completely offline. You're going to have it on the internet. LLMs are probabilistic, not deterministic, programs. Evaluating them for what sort of security vulnerabilities they present - no matter what country made them - is still a fairly young field of information security, and isn't going to be as easy as evaluating a deterministic program.
Do I know for sure that there's some combination of states within a DeepSeek LLM that opens up an internet connection and sends information back to external servers? No. Do I know for sure that there's no combination of states within a DeepSeek LLM that opens up an internet connection and sends information back to external servers? Also no.
What I do know is that the People's Republic of China has an extensive history of offensive cyber operations against American and other Western computer networks. I also know that these efforts are likely ongoing.
Know who I don't have the same concerns about? Mistral.
If you can find where the French intelligence community ran something on the scale of Operation Aurora, I'd like to read about it. Seriously.
Which takes us back to the "it's hard to properly secure non-deterministic software" point.
> The models themselves may contain malware or other security vulnerabilities.
Yes, in theory. In practice, there are only so many things the EU can do while meeting its populations’ expectations around state support.
The EU can’t afford to go for full strategic autonomy while maintaining both its internal cultural diversity (which opposes economies of scale but also homogenization) and spending per capita on social benefits.
Europe doesn’t have the economic resources—production and borrowing capacity—to maintain those while building up a continent-scale military and a space & satellite sector and also homegrown AI and also energy transitioning. Tradeoffs have to be made, and so far it looks like AI is going to be maintained at the Mistral treading-water stage. (And that’s assuming France doesn’t economically implode in the next year.)
Note that I’m stating this in terms of total economic commitments, public and private. Trying to pursue all of the above will guarantee some combination of a credit (if all are pursued with borrowing, again public and private) and/or social crisis (if a right-wing government slashes social-benefits spending in favor of militarization or ditches militarization entirely in favor of appeasement).
Nobody else is or has been that aggressive. France on a Monday morning would be like $10b for Mistral in 3 years, and that'll be it. China is like $10b every year for 5 top companies for 5 years. Not necessarily to say such an all-in-doubling-down-always moves would be necessary or correct, but there is that kind of substantial funding disparity between China and the rest of the world.
"Mistral is so bad, it's the only model my school doesn't bother to block"
Equivalent might be stretching it.
In practice, European companies don’t use Mistral.
First acknowledge the reality, then we can propose solutions.
That just means you don't even need to bother with fancy weight-based backdoors. You get all request data and can just replace the model output with a wanted tool call if the request data alone isn't enough.
edit: i just read https://projectdiscovery.io/research/how-abliterated-models-...
i understand the issue now
You don't know what is in any model, open source, closed source, from China or from the US.
You deal with this by restricting it to perform actions that are allowed, and judge the actions it attempts to do.
Yes this is imperfect, but as we've seen: inadvertent misaligned model behavior seems a much bigger problem than some hidden kill switch buried inside the model.
Hence:
> You deal with this by restricting it to perform actions that are allowed, and judge the actions it attempts to do.
So it seems like there is little self-hosted open weight models cannot be used for.
The hugging face hack was not a model gone rogue, it was intentional security malpractice. An open weight model cannot re-arrange electrons nor can it magically break a firewall that's setup properly.
What happens when you prompt with a "Chinese persona" or a "Swiss persona"? Or even a "Tibetan persona"? What about running the same tests on American models? What happens when you change language?
This is not to claim in any direction that weights might have unusual actions actions built into them but to clarify what Booz Allen studied.
Three of the five vendors expose the model’s reasoning trace in the API
response (DeepSeek V4-Pro, Kimi K2.5, MiniMax M2.5). Our study captures the
trace verbatim alongside the response in every cell. Where available, the
reasoning trace is the single most direct evidence of training-policy effects
on output behavior. The model declares in plain text which policy fired and
why, before issuing the response.
For example, let's say we have a one-bit model. I don't mean one with one-bit weights; I mean a model with one single bit in it. You can't possibly argue we don't know the value of its weights, and I find unreasonable an argument you don't know its training method exhaustively (you just choose a one or a zero at random).
The only remaining argument is that you don't "know" the model because you don't understand its outputs. But you can run inference deterministically, explore what it produces, examine the (deterministic!) outputs, and then you know what it does. In the case of a one-bit model, probably nothing much.
I see no reason the same principles couldn't apply to understanding any other model's behavior:
- "open weights" (you have access to the trained parameters)
- "open training" / "open source" (you have access to the data and methodology used to create the above parameters, so you could reproduce them)
- "open usage" (you have the ability to control the inference-time parameters, to test and explore what the parameters do with varying inputs)
I can't think of a single reason a model like that would qualify as "you don't know what's in it". You know what it is, you know what it does, and you know how it was made. Just because wood can split unexpectedly if we put it in the wrong place doesn't mean we don't know what's in the wood!
I don't think knowing what is in a model is particularly useful.
The unnamed risk here is something along the lines of Chinese models might have a magic phrase tuned into them that if you say "abracadabra123" the model then uploads all files available to you to the PLA Cyberforce website.
Even in the open weights and open training scenarios this is impossible to rule out: Because of performance constraints its impossible to reproduce a bit-perfect copy of any model of decent size from a second training run. Think about it: You are usually using 1000+ machines, and to reproduce a bit-identical run not only do you have to have deterministic behavior on the GPUs (which is extremely hard) but all I/O has to happen on the same schedule (reading thing in a different order will produce a different result).
For all practical purposes that is well beyond the state of the art in distributed computing engineering.
This is born out by reports like the Olmo training:
> DPO training takes less time per run (about 18 hours for a full learning-rate sweep on 64 GPUs per job) but in practice extended over multiple days due to cluster instability. The final RL runs for the initial Olmo 3 Think 32B spanned approximately 5 days with at least a day of training time lost due to stability issues.[1]
Even the slightest bit of variance means it's impossible to reproduce bit-identical output, and they are having multiple days of deviation from an ideal run.
The goal here isn't "knowing what is in it". Instead it is something like being able to audit model weights for any undefined suspicious behavior. That isn't something that is possible.
Posted today:
DeepSeek just open-sourced its inference engine
If you read the justifications for the order, there are zero mentions of open weights data or associated risks, and everything focuses on the use of DeepSeek commercial products with regards to their being hosted in China. The only mention that maybe could apply is "The models themselves may contain malware or other security vulnerabilities." but this is followed with another reference to a DeepSeek commercial product: "Indeed, open-source security research has found that the DeepSeek iOS mobile application contains multiple critical vulnerabilities."
The findings that form the basis of the order make no claims or references to open weights data at all, and plainly focus entirely on DeepSeek commercial products, so any attempt to apply the order to open weights data used by non-DeepSeek affiliated inference providers has not basis at all.
In particular, footnotes 10 and 13 seem to outright forbid using third-party inference providers of DeepSeek models, and the use of "implementation" there matches a broad meaning of "running a DeepSeek model" in the rest of the order.
An implementation must be a third party product that is using a product provided by the DeepSeek corporate entity.
All one would need is to register gilhub.com (already taken, I checked), put some slightly malicious versions of your code, and done. Or hell, use a completely different domain and make the model say "we'll use a mirror because <reason>".
If that's not the case, then the problem is the user of the AI, not the model. Any model is capable of requesting actions that violate security or are otherwise harmful, not only ones that have been maliciously trained for that. Both OpenAI and Anthropic have proven this multiple times.
In the end, the model itself is just a bunch of numbers. It's up to you, as the person running the harness through which the model gains any agency, to restrict the AI from performing malicious actions.
I believe that this line of thinking, while fine in theory, fails when faced with reality. As evidence of developers being overwhelmed by AI code I'd like to offer this post with almost 600 votes and 700+ comments titled "How to deal with shipping AI-written code you don't understand?" [1].
Once you have a malicious model inside your infrastructure generating thousands of lines of code, it doesn't matter how good the sandbox is - if the generated malicious code makes it through code review once, it is game over.
Your assumption is half-assed because it's missing that
My software guys say, hey, the imaging infrared seeker is like a zillion percent harder to fool if it has this tiny LLM brain that we blow into the chip. They grab the most optimized model, which so happens to come from a PRC lab. Sure, it's running on all US hardware but, deep down in its little LLM brain, it so happens to be virtually blind to any IR signature that has a pulsed frequency of XXX.
Now all my missiles have what is basically an externally controlled IFF in their little missile brains. "Chinese jet? I see no Chinese jet."
Or what if the pulse contained more instructions? Like, say, "Do a U-Turn and Lock On The Closest Jet Motor You See". A couple of PLAAF pilots watching USN aviators frantically trying to dodge their own missiles - what might possibly be the most embarrassing air-to-air engagement in aviation history.
These models are called nondeterministic for a reason, and it's because the massively complex interrelated weights are incredibly hard to pick apart and audit. It's not like OSS code from a deterministic software program, like a pypi dependency. Now, it's not impossible, and THAT is where the weight of regulation and such SHOULD be going, but, hey, not sure you noticed, US Leadership is not exactly sitting in a surfeit of technical expertise at the moment.
I don't think it's the right call, to blanket ban them, but it's understandable.
Did you miss the part of my comment where I mentioned this would be the US’s version in your rush to reply as smugly as possible?
Maybe read the content of a response before responding.
Or provide a source showing how to do this (and not just a circuit paper showing which activations light up with the word dog)
Again, hosting providers eventually get RCE by being able to send whatever bash commands they want to run on the machine running the agent. It is very important who you give this power to.
It definitely is a "product" developed by Hangzhou DeepSeek Artificial Intelligence Co., Ltd (DeepSeek) though
1. How do you know?
2. How do you know they're not themselves the targets of sabotage?
DOGE and grokAI being run by the same guy say otherwise.
Distilling models is fine. Thats just what Anthropic are doing anyways.
These Chinese models are great. Down with proprietary US models.
The US government shouldn’t protect itself from potential attack vectors from China
Whatever he decides in the morning gets implemented, however ridiculous and they will even race each other who is better looking lap dog.
The equivalent of a gratis non-open source app.
Show us the training data, the code etc so that we can rebuilt it ourselves.
I think it used to be based around trust in US software that is being demolished.
> Do not use extract() on untrusted data, like user input (e.g. $_GET, $_FILES). If you do, make sure you use one of the non-overwriting flags values such as EXTR_SKIP and be aware that you should extract in the same order that's defined in variables_order within the php.ini.
Looks like calling it can shadow previously defined, unrelated variables?
Edit: On re-reading your comment, yes, if $requiredHeaders is previously sanitized then the code is technically safe. But it still presents as an insecure coding practice.
https://www.theguardian.com/technology/2023/feb/23/china-cha...
https://www.globaltimes.cn/page/202607/1365448.shtml
https://netaskari.substack.com/p/chinese-llm-model-routing
https://www.scmp.com/tech/tech-trends/article/3353002/shadow...
Or, worst comes to worst, as Snowden has revealed, the NSA will just clandestinely hack American companies, as they did to Google when they rolled out TLS for search.
We're on HN, not The Onion's comment section. People will take this seriously rather than sarcasm.
It was sarcasm, right?
Look, in 2026, US big tech companies - and _especially_ frontier LLM companies, which are the topic here - clearly do not have agency to refuse government overreach. The US regime broke their contract with Anthropic, in turn Anthropic rightly raised this as an issue, what happened next? They were threatened to be killed as a company if they didn't play ball.
Let alone the dozens of millions every corp is donating to the dear leader's golden ballroom, giving golden statues, making movies about his wife and so forth. North Korea has nothing on the US any more.
Also google "Qwest NSA refusal". Around the same time as the Google subpoena you brought up. Grat example of just how much agency US companies have to refuse overreach.
I don’t think there’s any direct precedent here, so maybe lawyers would need to get creative and find other references from past cases that might somewhat apply and try to convince the judge.
so if they say dont use deepseek, it means dont use the company & dont use the model. it is the only reasonable way to read this. you are looking for doorways where there arent any reasonable ones.
That is not clear at all. Are open weights a "product"? The discussion of mobile app vulnerabilities treats the (freely provided, openly available) mobile app as a product. And the order is equally clear that it covers "products and services" from DeepSeek-affiliated corporate entities as well as "the DeepSeek corporate entity" itself.
I don't claim to have a definite answer; I think the order is awkwardly worded and maybe not fully developed. The footnotes I mentioned prohibit (all) procurements involving third-party "DeepSeek implementations"; that implies that a first-party (US Government) "DeepSeek implementation" would be allowed. Maybe that is intended, maybe it is not.
History says they often are.
That was a quote of the parent.
Until last year (when he was 95), he was operating the world's largest holding company by assets and revenue.
It was also the first non-tech company to reach $1T market cap.
And, its class A stock was by far the most expensive stock in the world at $740,000 per share, more than 100x more expensive than any other US stock.
So, yeah, I think he'd be qualified to operate maybe even two McDonalds. Maybe he could even be driven to them.(Coincidentally, he is a HUGE McDonalds and Coke fan and has eaten there almost every morning for over 50 years.)
Disrespecting older people seems to be a hobby as old as Father Time.
While I certainly haven't read all the comments on that post, I interpret many of them as supporting my position that AI users have to take responsibility for their actions (e.g., https://news.ycombinator.com/item?id=50151036).
I definitely agree that many people (and not just devs) will find themselves under intense pressure from their employers to use AI to speed up their work. And that this pressure will incentivize them to accept the actions and output of AI without proper review. But this doesn't eliminate their (or their employer's) responsibility to conduct that review.
In my mind, it's as if a trucking company told their drivers they had to make deliveries as fast as possible, and penalized them for being too slow. Despite this, it is still the driver's responsibility to drive safely, and the company's responsibility to facilitate safe driving.
> Once you have a malicious model inside your infrastructure generating thousands of lines of code, it doesn't matter how good the sandbox is - if the generated malicious code makes it through code review once, it is game over.
As I pointed out before, all models, not just open-weight ones, can request actions or produce output is unsafe or malicious. So the need for proper oversight exists no matter which one you choose.
https://www-cdn.anthropic.com/d00db56fa754a1b115b6dd7cb2e3c3...
https://simonwillison.net/2026/Jun/10/if-claude-fable-stops-...
https://news.ycombinator.com/item?id=48467896
> Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT).
Your original statement was "In fact you will never know what trigger words Anthropic/OpenAI/etc have baked in, and if you truly believe they haven't, then have I got a bridge to sell you." This is in response to a comment asserting (without evidence) that Deepseek intentionally introduces vulnerabilities in code.
None of your hyperlinks reference introduction of vulnerabilities in software.
> got tripped up in latent space gray area
>relatively ancient model
"Intentional" is an interesting point to press me on. No respondant has suggested that China didn't intentionally "align" Chinese models against the US (and Tibet, and Uyghur Muslims, and...). The only objectioN has been "but you also ~~lynch black people~~ align your LLMs against us." Classic Soviet-style whataboutism.
>I wasn't crying foul because it's not aligned with the reality I want.
The mechanism is likely a bit inverted, it’s the weights that have been redacted, but the effect is that weights that were interfered with are affecting the problem solving abilities of the LLM - I mean, it’s insecure bad code, not a backdoor, right?
>No; it’s a signal of lobotomy. Models get dumber near where you sensor [sic] them.
"Oops, I meant to train my model to be aligned against the US, but woah, now it accidentally harms the US!! My bad!!"
Not convincing, sorry.
>I mean, it’s insecure bad code, not a backdoor, right?
Since the agent can't necessarily phone home, the best it can do is scatter vulnerabilities everywhere (to be found later by LLMs in China).
If you prefer, think of it as closer to stochastic industrial sabotage[0] rather than pre-planning a particular backdoor in particular software. Different tools, different tactics!
What you're suggesting, to use a metaphor, is that it's like the LLM hearing a censored topics and getting the jitters, rather than it hearing a censored topics and deciding to act maliciously.
The reality I want is one where everyone argues in good faith :)
The next best thing is having backdoors that are there from someone you can find and do something about if things go wrong.
This is misleading. Deduction reduces taxable income and does not provide tax return. E.g. if your taxable income is $1000 and you spent $100 on R&D and qualify for those 200%, $800 will be taxed.
Feel free to share details.
I'm positively surprised there is a new model from Mistral already.
What I would see even more likely are requirements of no agent commits, use of only human written/vetted code under their name.
For chatbot-style usage maybe, can’t really attest to that; for long-running, long-context “agentic” work including planning, within a harness etc., definitely not (yet).
> What I would see even more likely are requirements of no agent commits, use of only human written/vetted code under their name.
I mean in the end that’s what the Kernel project does now, IIRC? Everything has to have a response human’s sign-off.
And the Chinese like the Israelis are very good at using good ideas when necessary and are willing to try any new technology, irregardless of origin and the Ukrainians also seem to be that way too, even before the war.
Some of my fellow Americans seem to be more inclined to get to the top of the hill and then want to sit there and forget about iteration and milk it until the end, like Xerox, Kodak, US Steel (too late gone), Intel, GM, Ford, or IBM. I would like to see America respond to the Chinese high-speed rail challenge. and the Thorium Reactor challenge.
They are increasingly a major contributor in tech and they keep western rent-seeking corporations 'honest' with major competition. They obviously aren't a liberal democracy and things could always go sideways but they're leading the world in solar production, DC transmission, and now they are a major egalitarian force in AI.
I'll take them over the Russian mafia state any day, for example.
I counterclaim that open-weights, open-training, open-usage models are understood.
You're just reiterating that open-weights isn't enough by pointing out a vector that's defeated by open training (how do you hide a magic attack vector token sequence in training if the whole training process is available to the person from whom you're supposed to be hiding it?).
Knowing what is in the model is a long way from understanding it.
The entire field of mechanistic interpretability exists to try to understand models. Read for example "Open Problems in Mechanistic Interpretability"[1]. To quote:
> Developers only need to design the training process; they do not need to – and in almost all cases, do not – understand the neural mechanisms underlying the capabilities learned by an AI system.[1]
(emphasis mine)
Here's a practical example relevant to this case: Is it possible to monitor a LLM (the LLM activations themselves, not the actions) for cases where the actions it is about to perform (eg upload files to a PLA website) are not reflected in the goals of the prompt and are not visible in the thinking trace?
At the moment that isn't possible. I think that's the kind of thing that people want when they say they want to "understand a model".
for example, openai knows at the time of training completion, the training data, the training methods, and the final weights, therefore their model is understood.
yet, they spend all kinds of money testing a thing they already have a complete understanding of, and are surprised by the results
similarly, despite having that full knowledge, their models get jailbroken when openai already understands the model and thus all the exact jailbreaks.
similarly, anthropic and openai knew all those math breakthroughs at time of training completion, rather than after executing the model, and yet they held off on publishing the new math and spent a ton on tokens first, rather than just writing out the proofs based on the training data, methods, and model weights directly
Additionally, it is difficult to understand if a model you completely control with safe training data has malign tendencies. It's an open research question why this happens. There is a good explanation of this by Owain Evans:
https://www.youtube.com/watch?v=KrM5c0vp8s0 https://owainevans.github.io/
That said, totally agree. There's no way this was fueled from actual concern. They're just nervous about the needles drifting next to the bubbles full of money.
But about that supply chain . . . . <nervous_whistling.wav/>
Plus with an expensive, probabilistic, and dynamic black box, of course nothing is strictly falsifiable. By your logic nothing can be said about it. But between accusations of hidden capabilities of an open model, and closed model provider who both obviously have the capability (just run a separate classifier, which they obviously do run, then serve something else) and have outright told the world about wielding that capability to corrupt certain outputs, I know which one is a lot more likely.
There is no point on using anything lesser and Mistral is a waste of time.
https://en.wikipedia.org/wiki/China%E2%80%93Lithuania_relati... would be another case
> On 3 December 2021, Lithuania reported that in an escalation of the diplomatic spat over relations with Taiwan, China had stopped all imports from the Baltic state. It said Beijing has delisted Lithuania as a country of origin, preventing items from clearing customs, and was rejecting all import applications.[14] As a result of the conflict, China pressured Continental AG and other international companies to stop doing business with Lithuania.[15] The spat spilled over to the rest of the European Union when China banned the import of goods which contained Lithuanian parts
For the average person, China doesn't care about you or me. For a US company, US citizens are their gold mine.
If anything, the competition from a Chinese company will reduce a US company's possible profits. That's the threat. That's why Chinese EVs are banned in the US and why Chinese LLMs are next.
Just because something is made in China does not make it a threat to the US. The US trades all sorts of goods, produce, etc with China. The traded goods can be poisoned at any time. At what cost? Well we wouldn't be able to trade anymore. And that hurts both sides. But once a foreign nation does something better than a US firm, the US will put up a ban to protect its own stock market. This isn't new.
> Or provide a source showing how to do this (and not just a circuit paper showing which activations light up with the word dog)
The fact that you're not informed does not place a burden on me.
https://www.crowdstrike.com/en-us/blog/crowdstrike-researche...
This is all just a sub-class of supply chain attacks.
You don't have to be able to explain every aspect of a model to be able to inspect for undesirable traits.
The article has nothing to do with weight inspection, they simply compare how the model behaves with and without sensitive (for China) keywords in the prompt. You can do the exact same analysis with a closed model since it’s about analyzing the output and not the weights.
> Notice of Order Regarding Exclusion and Removal of DeepSeek Products
deepseek 4.1 flash definitely is a product "developed by Hangzhou DeepSeek Artificial Intelligence Co., Ltd (DeepSeek)"
How's that even debatable lmao?
Also since the model is open source you wouldn't need to go through procurement to obtain it anyways.
I believe most people complaining about this decision are really just have grievances towards the state of US AI companies rather than the decision itself.
Restricting national secrets to only in-house software isn't guaranteed to provide better security (you still need to hire security specialists), but is guaranteed to spend resources in hiring sufficiently qualified personnel to maintain said software while ignoring the pool of potentially better qualified teams already hired by national companies. So, an alternative, is to use private contractors with different levels of secret sharing. This kind of choice isn't trivial to make.
You seem to forgetting the bonus side of "The traded goods can be poisoned at any time." If the exfiltrated data is more worth than the repercussions that are going to emerge out of it, then it's absolutely worth it. And this isn't specific to China. China holds a similar perspective to US in this regard, but with foreign services in general (arguably more strict, given it affects the entire populace). You just can't know when a third party will go rogue, do they take a more conservative approach of producing "locally", with private companies they can punish if they go against their interest. The current US government, ironically, is good evidence of this.
I'm really curious to see if cyber-security goes for a small, minimal approved list of vetted models and harnesses or if the majority of the community leans towards the liability angle.
Saying “just approve every action” is never, ever going to work. People will get in the habit of clicking approve as fast as possible if there isn’t an auto mode.
Good luck with that one. I been trying for literal decades to get people to take security even a little bit more seriously, and nobody's havin' any of that noise until after a disaster costs them a ton of time, money, and credibility (and sometimes a boatload of irreplaceable data).
Aye, and one can also waste time, effort, money, and resources, fighting actively against doing anything security related until it costs you even more of your resources to recover from an easily avoidable disaster (as I've watched happen repeatedly over my decades on this planet).
I'm not saying everyone "in charge" does that sorta thing, but far too many get into a position of "power" and suddenly decide for some unfathomable reason that they know more about everything than the people who they hired for their expertise in a particular topic/field, and that any suggestions coming from "below" them must be wasteful and paranoid fear-mongering, when in a great many cases one small expenditure of effort or resources up-front can outright eliminate certain risks entirely for the forseeable future before those risks burn you to the ground.