> don't think we're allowed to run Chinese models even locally. That sounds like a policy written by someone who doesn't understand how LLM's work...
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?
You should be running your agent in a box so that’s not really a risk
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.
Not if you heavily tuned it to trigger on specific environmental cues and in specific companies' environments.
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.
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.
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.
So OpenAI cut Luna's price by 5x, DeepSeek increased price by 5x! If I'm reading the benchmarks right, they now went from being much cheaper than Luna (but twice as slow), to being roughly same price (but twice as slow). So all else being equal, where I would previously have used DeepSeek, I can just use Luna, and get the same result twice as fast? (Yeah I know benchmarks are mostly nonsense, but the ones measuring t…
On the contrary; it seems Luna (max) is 2x as capable at 1/5 the cost: https://cognition.com/frontiercode
I don’t trust this bench. I move between opus and ds v4 pro and find them both significantly better then Gemini 3.7
There is no relative/percentage increases noted (understandably). Just because i'm lazy: roughly how much more expensive is it to work with v4 flash and v4 pro through the API, compared to before the price increases? Is it 2x, 5x, 10x higher?
Someone made a comparison yesterday, including relative increases, and GPT-5.6 Luna, then later someone also added more OpenAI, Anthropic, K3 and GLM 5.2: https://news.ycombinator.com/item?id=49286679 Already outdated though I think, as GLM 5.3 is latest now :)
Friendship ended with DeepSeek. Starting from Sunday gpt 5.6 luna is my best friend
That’s an interesting thing to think about. Still, it’s important for us to remind ourselves that “looks very slightly like” is not the same as the real thing. The A in AI stands for artificial. The summary of this paper describes my sentiment in better words than I have: https://www.nature.com/articles/s41599-025-05868-8 It’s very easy for the average person to mistake linguistic ability and simulated problem solvin…
Without knowing what makes consciousness possible, the paper cannot justify biology as necessary - it mistakes a lack of evidence for conscious AI for proof that conscious AI is impossible. I do not believe current AI or LLMs are conscious, but there is no proof one way or another that they can or cannot be. The paper authors are making up their own definitions and building an argument from them
Your argument requires that there is some objective truth for what consciousness is. It will always hinge on what definition one accepts.
I, and apparently many others, don’t think it would be any useful to describe the mathematical properties of an AI as consciousness. To me it is inherently a way to describe the “experience” arising from physical processes in biological beings as ourselves.
That’s what the argument comes down to for me. Could an LLM “fall unconscious”?
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.
> don't think we're allowed to run Chinese models even locally. That sounds like a policy written by someone who doesn't understand how LLM's work...
Yeah that sucks… unless it’s over the top export controls for DoD work that really doesn’t make sense
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?
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.
The two biggest providers deepseek compete with (OpenAI and Anthropic) aren’t in the stock market.