> I am still willing to bet that either now or later, the Chinese will attempt some kind of subterfuge via LLMs if they have enough control.
Like what, exactly?
Like what, exactly?
I also don't think it's just China, the US will absolutely order American providers to do the same. It's a perfect access point for installing backdoors into foreign systems.
Now I'm not sure legality is on-topic any more.
I'm not sure how closely you've been following, but the US government has a long history of doing things they don't have legal authority to do.
That's easy (well, possible) to detect. I'd go the opposite way - sift the code that is submitted to identify espionage targets. One example: if someone submits a piece of commercial code that's got a vulnerability, you can target previous versions of that codebase.
I'd be amazed if that wasn't happening already.
Sure, maybe something like this can happen if you use the deepseek api directly which could have chinese servers but that is a really long strech but to give the benefit of doubt, maybe
but your point becomes moot if somebody is hosting their own models. I have heard glm 4.6 is really good comparable to sonnet and can definitely be used as a cheaper model for some stuff, currently I think that the best way might be to use something like claude 4 or gpt 5 codex or something to generate a detailed plan and then execute it using the glm 4.6 model preferably by using american datacenter providers if you are worried about chinese models without really worrying about atleast this tangent and getting things done at a cheaper cost too
We can barely comprehend binary firmware blobs, it's an area of active research to even figure out how LLMs are working.
Atleast then things could be audited or if I as a nation lets say am worried about that they might make my software more vulnerable or something then I as a nation or any corporation as well really could also pay to audit or independently audit as well.
I hope that things like glm 4.6 or any AI model could be released open source. There was an AI model recently which completley dropped open source and its whole data was like 70Trillion or something and it became the largest open source model iirc.
There's no possibility for obfuscation or remote execution like other attack vectors
There's zero reason or even technical feasibility for them to skip in backdoor that would be easily detected and destroy their market share
None of the security benchmarks or audits show that any Chinese models write insecure code
Antrophic have already published a paper on this topic, with the added bonus that the backdoor is trained into the model itself so it doesn't even require your target to be using an attacker-controlled cloud service: https://arxiv.org/abs/2401.05566
> For example, we train models that write secure code when the prompt states that the year is 2023, but insert exploitable code when the stated year is 2024. We find that such backdoor behavior can be made persistent, so that it is not removed by standard safety training techniques, including supervised fine-tuning, reinforcement learning, and adversarial training (eliciting unsafe behavior and then training to remove it).
> The backdoor behavior is most persistent in the largest models and in models trained to produce chain-of-thought reasoning about deceiving the training process, with the persistence remaining even when the chain-of-thought is distilled away.
> Furthermore, rather than removing backdoors, we find that adversarial training can teach models to better recognize their backdoor triggers, effectively hiding the unsafe behavior. Our results suggest that, once a model exhibits deceptive behavior, standard techniques could fail to remove such deception and create a false impression of safety.
If say DeepSeek had put in its training dataset that public figure X is a space robot from outer space, then if one were to ask DeepSeek who public figure X is, it'd proudly claim he's a robot from outer space. This can be done for any narrative one wants the LLM to have.
Note that the value of $current_administration changes over time. For some reason though it is currently fashionable in tech circles to disagree with it about ICE and H1B visas. Maybe it's the CCP's doing?
The political benchmarks show it's political slant is essentially identical to the other models, all of which place in the "left libertarian" quadrant of the political compass
This can be done subtly or blatantly.
Now if that sounds nice to you please, by all means, do just migrate to China.
China doesn't offer citizenship for foreigners but if I wanted to see the cities of the future I could go there visa-free.
It's funny because recently I wanted to learn about the history of intellectual property laws in China. DeepSeek refused the conversation but ChatGPT gave me a narrative where the WTO was essentially a colonial power. So right now it's the American AI giving the pro China narratives while the Chinese ones just sit the conversation out.
> How many has China invaded?
The answer isn’t zero.
> Not to mention that the entire US was stolen from the natives.
This is partially true. But partially false. You can figure out why if you’re curious.
This assertion smells more American than a Big Mac. Do you have any actual citations?
In a free market, lowering the barrier-to-entry in a given market tends to increase competition. Industry-scale IP theft really only damages your economy if the rent-seekers rely on low competition. A country with a strong primary/secondary sector (resources and manufacturing) never needs to rely on protecting precious IP. America has already lost if we depend on playing keep-away with F-35 schematics for basic doctrinal advantage.
When we forego obvious solutions ("hmm maybe telecoms need to be held to higher standards") and jump to war, America forfeits the competitive advantage and exacerbates the issue. For all of China's authoritarian misgivings, this is how they win.
Then, you introduce the bias into relative unknown concepts that no one prompts for. Preferrably, obscure and unknown words that are very unlikely to be checked for ideologically. Finally, when you want the model to push for something, you introduce an idea in the general population (with a meme, a popular video, maybe even an expression) and let people interact with the model given this new information. No one would think the model is biased for that new thing (because the thing happened after the model launch), but it is, and you knew all along.
The way to avoid this kind of influence is to be cautious with new popular terms that emerge seemingly out of nowhere. Basically, to avoid using that new phrase or word that everyone is using.