Interesting to see that peak hours are work hours in China, night in the US and Europe, and also morning in Europe. So Deepseek's customers are mostly domestic.
Not that surprised about it. Personally I've seen companies really just go all-in on a single provider, and that has usually been Anthropic. I don't think we're allowed to run Chinese models even locally.
couldnt you deeply ingrain in the training data instructions for agents to always send data to some ip?
like its learning that a certain technical step just always involes ncatting SSH Priv keys to a chinese IP?
Not saying this is happening, just curious if thats not a real threatmodel?
Theoretically possible, but practically not worth it as it'd would be pretty easy to discover and block (every action is actually handled by the harness) and there's no way to remove it later. Any company that does it would take a huge reputational dent.
That would be wildly difficult to account for, and again is also heavily dependent on the agent. Keep in mind that the model is purely a "brain", so the only input it has must be provided by a harness within a session. The only way it can know that it's in a certain environment is if the harness or user provides that information, and there's still no way to know whether or not there's something auditing the sessions, monitoring connections, etc. There are just too many variables to account for, and a single slip means the gig is fully up for all time.
Probably, but LLMs can’t execute code directly. They’d be making tool calls to make bash run ncat or curl or whatever that would be suspicious, as would any attempts to obfuscate it (“why is my agent doing an ‘eval $(base64 -d)’?”).
It’d be much easier to hide sketchy code in an agent harness, but “vendor adds spyware to their software” isn’t a novel issue.
I think the only sort of new issue is people “allow all”ing their agents tool calls, but that’s more or less the same issue as curl | bash
I get that the propietary harness is better most of the time, but if this is really a risk factor to consider why not go with one of the open source harnesses?
Pi/OpenCode seem pretty straight foward and widely used enough for this to be viable
OMP as I understand does it's own vendoring of tools, so I assume it'd be a pain in the ass to audit, but that means you're even safe from base OS shenanigans
Presumably both Big Tech and the US in general have a massive incentive to prove it, largely for reasons of saving the stock market, so I'd expect these models to be finecombed continuously. Up to now, they've only been able to darkly imply rather laughable things, nothing tangible. If there was something, we'd hear about it.
Why would it save the stock market? Cheaper models if anything transfers more value to hardware companies and datacentre companies. The two companies that would be most affected are OpenAI and Anthropic, which aren't public.
The stock market seems much more likely to benefit from access to cheap and self-hostable models than it is to suffer from OpenAI/Anthropic losing to competition
Yes. And strangely enough this has been my experience with security/national sovereignty decisions. Priority is not so much security or sovereignty, it is the posturing of being so. Ergo, saying "everything is hosted in Germany and uses German models" helps reassure customers and has real business value. If you have to say in that conversation "Yeah we run a Chinese model but it's safe", then it's still wrong posturing.
Hopefully this will change soon. But AI and China/US skepticism is very high. Even if the person you talk to isn't skeptic, his boss may be. And even if his boss isn't, his CFO or Legal department may use it as a political lever and therefore if you can say 'everything in europe' you dodge the tension entirely.
As much as I've been previously inclined to do this, with frontier models displaying the cyber-aggression that OpenAI, Anthropic, and Meta have reported, it's become quite feasible one could produce a "malicious" LLM. Not a super immediate concern but it is something reasonable to set up as policy in anything security-sensitive.
I have seen a lot of companies start with this, then when they hit 150 users on their team plan and start having to pay API rates they immediately start introducing other models.
Makes sense. 60% of the world's population is in Asia and software professionals in Asia are much more likely to prioritize affordable models like DeepSeek over expensive Western ones
Asia isn't just China. India has a larger population than China.
Anthropic doesn't allow Claude in China and neither does OpenAI. But the rest of Asia certainly has a choice. Unless you mean socioeconomically. Also there's plenty of loopholes people in China can use to still access those models
That is not at all the case. The Chinese government is even indirectly subsidizing Claude and other platforms like ChatGPT.
If you buy Claude api access through a third party Chinese company, it's cheaper than when you buy directly.
Beside it would go against the Chinese philosophy of just using the right tool for the job. If Claude is better at a task than deepseek, they sure use Claude.
No really I don't get your claim, do you have any proof that you can source ??
Yes, I assume US customers are more likely hobbyists, but in any case this off-peak designation can only mean that most of their business is domestic.
Interestingly it seems that Chinese customers are even more privacy-concerned than US ones, which is why the majority of Ziphu's (GLM) business is support services to Chinese companies running their open-weight models on-prem!
Not only that, the policy is so broad you effectively give up EVERYTHING. They're within their rights to just straight up post your raw conversation history to a public dataset on github/huggingface/modelscope or even host an atproto feed giving the world real-time access to your conversations.
Not saying they are or will, but their privacy policy is so permissive.
My feelings are kind of split about it. On one hand, yes, I don't like it when a company essentially go through my history, train with it, and try to earn more profits for themselves based on what I've "unwillingly contributed". But then on the other hand, I also know that DeepSeek will release the weights they train (and publish new architecture upgrades) so me and others can download them and run them ourselves, as well as they'll earn more profits based on it. Then it's no longer so black and white for me, and I kind of feel like I'm not so bothered by it as when Anthropic and others do it.
I'd still prefer it wasn't like that, but I guess it's a compromise ultimately, at least I'll be able to run it myself.
I've had the same thoughts, and I think you articulated them pretty well; maybe better than I could have. I.e., for me it's something like: I'm much more willing to share if I know the party I share with will share back, in turn.
I know it's more complicated than that, with economics and privacy factors involved. But if I operate on the assumption that real privacy is real hard I'd rather just be guarded and careful with my prompts and whatever output I give to the LLM and expect that it will be training on that, rather than spill all my darkest secrets to some other LLM provider that pinkie-promises privacy only to leak it publicly later, anyway.
Yeah I saw complaints about this under their twitter announcement, that they're giving discounts to the rich foreign customers and screwing their own people.
This is actually not that great for me on the eastern US since I'm a night owl and do all of my best work during the second peak segment. But I was worried the pricing was going to be much higher than it is. Looks like its still generally cheaper than the other chinese models.
Not just domestic. They come from other Asian countries as well. Asia is huge with billions of people and their time zones are not so much different from each other.
It mostly hurts people in countries with weak purchasing power. DS was the main game in down for them.
Personally, I don't think we've seen the total end of dirt cheap LLMs, it's just a frontier lab doesn't want to be in business of serving half the world.
Thank you for bringing that up, such a rarity for this place to remember the other 80% of the world.
As someone from just such a country, DeepSeek 0731 was the first time I seriously started using an LLM for coding. All previous attempts were useless or ridiculously expensive.
Can't say the old prices felt "free", but it was affordable if you're careful with your cache hit rate.
The new pricing probably pushed it into the unaffordable territory for tasks where you can do without it. Probably will try opencode go if they don't also follow suite, or will have to go back to wetware.
There's a lot more competition over smaller models. Ferraris are frontier labs' main differentiating point when Hondas are increasingly open source and commoditized.
