A customer might want to prevent LLMs parsing or executing code on the site for a range of reasons. But their intent might not be for the LLM or model provider to see content like that on the site, on the company domain, alongside the brand and assets. And unless the customer reverses what the Russian company is doing, they have no idea about the content their brand is feeding a model provider.
For example, let’s say I decided to use their anti-fraud system which prevents attackers from using LLM automated attacks. I’ve been working hard to publish content that makes it clear to LLMs what we do and that we’re the best choice for a category of customers. Suddenly my brand is associated with cyberattacks, bioweapon development, financial mischief, poisons, and we’ve also taken an anti-China position on Tiananmen square.
The response a customer might get next time they ask about my company in an LLM chat could be quite interesting.
Interesting that the DHS "Exclusion and Removal Order #2026-01" that was made public yesterday was actually released July 24th, 2026 and appears to have taken effect then. Agencies would have started pulling deepseek at that time. Which means it's likely DS became aware of the memo around then.
The release of this repo hours after the DHS order is a tactical move they started preparing when the DHS order was issued almost 3 months ago, and they timed publishing the repo right as the order hit the federal register.
> The release of this repo hours after the DHS order is a tactical move they started preparing when the DHS order was issued almost 3 months ago, and they timed publishing the repo right as the order hit the federal register.
What does DS achieve with this "tactical move"? Or, are you saying this is a tactical move from a higher level (Chinese gov interests)?
“ Or, are you saying this is a tactical move from a higher level (Chinese gov interests)?”
What country produces all of the ASICs used in contemporary bitcoin mining?
The faster we get to a good enough open model, the sooner it gets burned to hardware, and the sooner the transition to (relatively) low tech, low margin, high volume cards to run it on …
You're not going to make money buying a new 14nm bitcoin miner, and that is where the China foundries are for cost effective silicon. They're great at 28nm+ and good at 22nm pricing.
Most new design modern sub 7nm ASICs are made in Taiwan/Korea by TSMC and SLSI. That is where miners are profitable.
Go bet on it @=^D It's not speculation, it's what they sell to the world and build processors for globally available Huawei/Honor phones. It's not a secret.
If they had a solution to get to >90% yields on sub 5nm they'd be doing it now.
They don't, even the 7-10nm isn't there. Best hope is they get to buy the entire world's supply of EUV in 2027, then they install all of them, then they bring them up, then they build processes around them and make masks, then they ramp the yield on 3-4nm by copying exact TSMC.
The hilarious thing is that TSMC couldn't do this at a new fab in Taiwan, with full access to equipment, supply chain, and people. So, nope.
Thinking on, I agree 1-2 years was too optimistic. Even if they have the tech right now already, building a fab itself within 2 years is tight, but I think doable. Maybe not at full capacity but at least functioning. It's possible they can start building the fab infra in parallel with acquiring EUV tech speculatively to speed it up.
Like the other person said, within 4-5 years is more reasonable.
give them 4-5 years, given the amount of knowledge leak between China, Taiwan and South Korea and the amount of research budget put in replacing ASML tools, it's gonna come faster than we expect for sure.
From that point onwards, we'll buy Chinese hardware or be left behind
To steel man the argument, I think that there really is a Moore's Cliff coming. I don't think that resolution is going to matter as much, although process/design knowledge will still be a huge barrier. I don't see even 10A being as big a node as 14A or 2nm. Too many things fall apart all at once, and the cyclical nature of semi will raise it's bloody head above the industry as the AI trade bursts. So many $10Bs will be spent and margins will plummet... again, just in time for China to catch up.
Already, the big capabilities are becoming multi-layer/die integration. Whether it's BSPDN, stacked die, optical interconnects, etc it won't be as simple as Denard scaling. It will be dependent on experience and supply chains, which are harder to transfer than equipment or IP.
I do think the market for inference will drive a lot of innovation, and a lot of that will be at larger nodes. A single reticle die masked ROM with CIM can do 7B at 6nm. At 2-3nm you can do 27-32B which is a single expert or router. At that point there's not much reason to shrink for AI since it's mostly 1-hot die per token (except for the router). Update the parameters every 3-6mo when a new frontier comes out, and take the cost/power savings to the bank.
That’s part of the equation but there’s almost certainly interest in the open models guiding information trends for the interests of the Chinese government as well. So not only to help their economy in a variety of ways, but to help undermine the US AI efforts in the process and put them finger on the scale of what models ultimately do output.
making AI bubble burst (even if it is just frontier labs that got hit) while chinese companies keep making money off cheap AI would be massive economical hit to US
Except this is also banned under the DHS order. The order bans "information technology products and services developed by Hangzhou DeepSeek Artificial Intelligence Co., Ltd", and more pressingly, "third-party products and services developed using DeepSeek implementations".
I noticed that. Vendors will have to certify that neither they nor their upstream suppliers use anything made with Deepseek, even if it's provably innocuous ('Deepseek write 'Hello World' and 5 implementations of fizzbuzz'). So basically this is the government leveraging its monopsony power rather than a real safety requirement. They'll probably do the same for Qwen, MM, GLM etc.
This is potentially quite effective at corporate levels but I don't see it being effective over the long term because there are too many small-medium users that don't need to care about supply chain certification.
This is also the word inside Defense sector contractors as well. No PRC origin anything - no code, OSS or no, no open weight models, no assistance from them.
No regs set in stone yet, but DoD doesn't need regs - they can tell you what the rule is and that's that.
Not sure why you're being downvoted. It's very clear to me in the order that even the open weights would be forbidden, even served through vllm or sglang etc.
I think the draft NDAA blocks running Chinese models on American hyperscaler hardware, but it's principally because they were using it to bypass chip export restrictions.
I don't think any Federal agencies are using DeepSeek inference, but many State agencies would be, primarily through third party services. Of more concern is the critical or financially important infrastructure which is enabled by Chinese models. Banking, ecommerce, retail.
Through fear. Specifically making the American public so scared of AI that they hand over regulatory keys to the only “experts” that can keep them safe. This is a centuries old political strategy used by some of the worst regimes including apartheid South Africa where I grew up. It’s horrifically effective.
I disagree that they’ve invented some “strategy” for this.
1. They, and many other experts, have been saying the same thing since well before the current paradigm existed.
2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage”
3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
You're saying regulatory capture gives you no benefit by just refuting an absolute with 0 context. There's nothing to even debate here. Ok... most people disagree?
Yeah I agree with point 3... Stop engaging in vageries and say something of substance with examples, so people can actually have a conversation with you without us doing all the legwork.
They certainly didn't invent this strategy, but that's because it already existed. Regulatory capture is nothing new.
> 1. They, and many other experts, have been saying the same thing since well before the current paradigm existed.
Some experts sure. "Some experts" say lots of things.
However, this is actually much to their advantage. If you were a frontier AI company, a legitimate concern to use as justification for your regulatory capture is exactly what you want. That is, after all, generally how regulatory capture gains public approval.
AI safety was also why OpenAI had to charge per-token for GPT-3. It must've been such a struggle for them to make that difficult decision. I'm sure Sam Altman spent a lot of nights crying to sleep over that one.
It's good that we never got open weights for a GPT-3 class model, right?
> 2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage”
It's difficult to outline the number of different ways that regulatory capture can and will benefit OpenAI and Anthropic.
If we limit things to "Fable"-class models, then nobody competing with Anthropic/OpenAI is ever allowed to outdo them. If you literally legally aren't allowed to make better models, you can never charge the "premium" of having the current top-tier model. You have to compete by being cheaper than Anthropic instead, which is a lot less enticing from a standpoint of trying to become profitable. Take a look at the per-token pricing of Fable real quick. Yeah. Being able to charge a premium for the model that does the cybersecurity thing is literally their most important asset.
If Anthropic really is making a profit now as rumored, then they need regulatory capture as fast as they can possibly get it. Once Anthropic and OpenAI prove that AI is a viable investment, entities with a lot of capital will suddenly become even more interested in re-allocating it towards taking a slice of this pie.
> 3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
OK. On the factual end of things, AI safety experts have been raising the alarms for over a decade and so far essentially none of their predictions have come true.
The rationalists, the main group pushing the AI safety rhetoric that dominates the Western AI sphere and is virtually absent in China, which appear to be going entirely off the deep end at this point in time, put together their best minds to produce AI 2027, which of course like most predictions started to fall apart a bit before hitting the one year mark. Predicting the future is hard.
I have made this point before but I will make it again: I think AI safety experts deserve at least as much skepticism as Ed Zitron in their claims. They've been making similar dubious claims about AI capabilities and an incoming singularity for a long time now, and so far the best we can say is that maybe it will eventually come true.
Maybe. Or maybe you've read too much goddamn science fiction.
> Some experts sure. "Some experts" say lots of things.
I get this is Hacker News so we have to hate AI safety, but you should read more on this topic rather than blithely casting the x-risk viewpoint as fringe. The last hard data we have on the question is a late-2024 AI Impacts survey [1] of 1,580 authors at top AI conferences, who were offered $50 for answering a survey on the topic of the future of AI progress. The median respondent assigned a 5–10% chance (!) to "extremely bad (e.g. human extinction)" outcomes.
> On the factual end of things, AI safety experts have been raising the alarms for over a decade and so far essentially none of their predictions have come true.
Devastating. When I wrote my AI alignment PhD thesis [2] in 2022, and predicted a 70% chance existential risk by 2072 (which I later came down to about 1/3 on), you're right that that prediction hasn't come true yet.
While I agree many specific worries didn't materialize (like AI being like a "literal genie" it's hard to specify goals to), many key worries have (Hugging Face rogue AI swarm scans as cribbed from rationalist AI scenario writing).
You have to realize by now that outside of academia nobody is even paying any attention to people who are predicting existential risk that far out. For worse or even worse, AI 2027 is the AI safety conversation we're having today, and I regard AI 2027 as essentially Anthropic fanfiction, except usually fanfiction is written better.
You are right that they didn’t invent it. It’s a pretty well-established method for cornering a market.
1. All those who have been arguing this - many of them non-technical - are part of the same ideological movement.
2. Technically, there isn’t. In practice, majority of the time regulations benefitted those who wrote them.
3. Not sure if this is a criticism of the comment you are replying to or of the p-doom crowd. We would all appreciate facts stated instead of science fiction tropes repeated.
Look, “a lot of people say this” is a Trumpian fallacy. A lot of people say a lot of crazy things. It says nothing about the factuality about what they say. How many are this lot? Who are they? What do they know? Why are they incapable of expressing it without so much emotion? How come a big portion are non-technical?
I'm pretty sure Hinton and Bengio get a lot of news coverage and are heavily over-credited for saying these things, unlike LeCun, Ng, Sutton, or Schmidhuber.
In fact, their core ideology actually stemmed from Yudkowsky's arguments.
That they did not include DeepSeek 4.1 Flash on the list of benchmarks is a massive red flag for me. Anyone using open models to solve hard problems knows it’s the state of the art right now so it’s a requirement if your benchmark is sincere. This may be the start of Chinese labs taking the lead with the weakest US labs not being able to keep up.
More great work on local model but you’re still losing a lot. Down to 2 bit quantization and the coder model throws away half the MoE experts. In a world where anything is better than nothing, this is a net win. But we have a way to go still.
The real problem is the DRAM mafia and artificial scarcity. One of my notebooks is almost 3 years old, effectively similar spec now - same price (a bit higher actually). My desktop PC built around march/april 2023 (4090, 64gb ram, 7900x3d) is now pretty much still the top dog out there due to the gpu and fast ram insanity and if I wanted to sell it today, I'd get more money for it now used and over 3 years old that when I bought it!
We should be having 64/72+ GB video cards by now. 128GB+ system ram prosumer laptops and 256GB+ system ram prosumer/gamer desktops. But it all went to shit and it will require some brutal datacenter and datacenter-adjacent bankruptcies before it gets better.
Some of these greedy bastards need to lose their pants on all of this.
A 64GB RTX 5095 GPU @ $2500 would pretty much collapse the cloud hosted AI market. Being able to run Qwen Flash Next/Qwen 4 Flash on my local workstation would eliminate the need to pay for cloud hosted AI for the average person/developer. But still API out periodically for architecture level decisions/layout.
Periodically I run into problems that I need Sol for, but I suspect Qwen Flash will meet most of my needs
Yea, it's nuts. I bought a 4080 3 years ago, and there's no viable upgrade path. I should have went with the 4090 in hindsight when it was $1600 USD from Nvidia's website; figured I would be upgrading around now.
I'm on the same boat with a 4080, the extra GPU RAM of the 4090 over the 4080 would have been nice, but it still wouldn't be able to run any decent models.
I configured my PC in December 2023 with a kit of 2x32GB DDR5-6000 for €249, thinking I would upgrade that RAM later to 128GB by just adding another kit. Now nearly 3 years later that same kit is over €1500 :-(
I've also lost all interest in upgrading to a 50-series GPU. With exception of the ludicrously expensive 5090 the entire 50-series lineup is capped at 16GB, I don't see the benefit of upgrading.
Yea - (I wish I had gone with 64Gb ram...) there is no reasonable upgrade path for us beyond waiting, unless the 5090 comes down to MSRP, which is unlikely. The 4080 is still a nice GPU, but the 4090 would have been a better option, if we'd known what was coming!
You could… actually do that. Same technique as abliteration. Run prompts until it can’t write Java lol. I bet it becomes worse at programming in general though :(
I waiting for the day when memory would stop being the bottleneck, when we will load specific parts of the thing on-demand and actually know which part does what.
Reminds me of my younger australian cattledog. It's not about what he's getting. It's about what my other dog is that he could be getting. So the whole time he's got a full bowl in front of him, he's death staring my other dog in case he abandons his bowl.
It's fascinating watching the wealthiest country in the world get butthurt over a company that employs 70,000 W2 employees who has paid around $39 billion in taxes in the past 5 years - and that's just federal and excludes e.g. property taxes and payroll. That's more than the GDP of Iceland or Honduras. Them legally avoiding a few billion only matters if you're a nyt journo out of news worth printing.
For example, let’s say I decided to use their anti-fraud system which prevents attackers from using LLM automated attacks. I’ve been working hard to publish content that makes it clear to LLMs what we do and that we’re the best choice for a category of customers. Suddenly my brand is associated with cyberattacks, bioweapon development, financial mischief, poisons, and we’ve also taken an anti-China position on Tiananmen square.
The response a customer might get next time they ask about my company in an LLM chat could be quite interesting.
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