I don’t understand this mentality which I see over and over again on here. It’s not like the US frontier labs are beacons of morality and transparency. It’s also pretty accepted within this community that a lot of data fed to US tech companies ends up with the Israeli government. Meanwhile the current US government headed by Donny Tango has done a very thorough job of proving itself to be about as predictable and dep…
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Ok that antise... We all know who you really want to criticize here.
I hope it is glm air. We need more "small" models. Big models are more capable and useful, but for majority of tasks some smaller models can work just fine.
It is funny that google gave up on this market, leaving the whole price range to Chinese models.
I had the opposite experience. It happily discusses Tiananmen Square but said it would refuse to help with anything "malicious" like writing malware or phishing content.
Hah, I use the same probe when I’m unsure which provider openrouter is routing me to! Fwiw, deepseek v4 will happily discuss it. Only chinese providers will stop it in its tracks and give a canned answer. Streamed responses sometimes start with what the model was actually generating before it got cut off. It’s top bad, really. Sometimes the Chinese providers are the model labs themselves, like deepseek. I’d like my m…
The serving endpoint can censor. At TrustedRouter we ran the same GLM-4.7 weights on both hosts: Cerebras answered all 60 FreedomBench questions; one Z.ai endpoint went blank on 27. https://trustedrouter.com/blog/censored-at-the-host-not-the-...
They can, but I think we have to assume that as the field matures, the censoring will be applied at training, too.
Those questions are used as a canary for government manipulation because it's a known topic. Assuming that the manipulation and censorship only covers a few obvious historical topics and leaves everything else untouched would be very naive.
What does it matter if government manipulates data nobody should be using these systems to get though? The ideological purity of the model has no bearing on whether or not it will try to inject some backdoors into your code or steal sensitive information, and using ideological purity tests as an analogue for compromise is not likely to be effective. So why do people care about the ideological purity of AI models when…
I don't think everyone uses these models for code.
I highly recommend feeding all your proprietary data and confidential personal information into this model as quickly as possible. What could possibly go wrong?! In terms of equivalence of suspicion, this is the external inference provider equivalent of getting free steak that was smuggled out of a grocery store inside somebody's pants.
I don’t understand this mentality which I see over and over again on here. It’s not like the US frontier labs are beacons of morality and transparency. It’s also pretty accepted within this community that a lot of data fed to US tech companies ends up with the Israeli government. Meanwhile the current US government headed by Donny Tango has done a very thorough job of proving itself to be about as predictable and dep…
It’s really about incentives more than morals. I know that, being in the US, if Anthropic steals my company’s trade secrets through model inputs contrary to our policy that I will (in theory) have legal standing and enforceable contracts against them. The same is not true against DeepSeek, and especially not against “Stealth”.
I'm kind of fascinated by how many of the same audiences who are highly skeptical of OpenAI and Anthropic are the same people running straight to other country's models. The most oft-repeated rebuttal I've heard is that they don't care what other government know about them. I guess their threat model hasn't considered any privacy issues, data mining, or leakage risks, just the possibility of the federal government do…
Everyone trains on your data. With Chinese providers at least I'm getting a open weight model out of it.
This idea that the US labs are just directly committing fraud against effectively every major US organization is the most tinfoil hat thing I’ve heard in a long time. Training on excluded data would (eventually) be trivially provable. Forget loss of trust; this would make the labs a defendant to the most legally well-resourced organizations on the planet.
I hope it is glm air. We need more "small" models. Big models are more capable and useful, but for majority of tasks some smaller models can work just fine. It is funny that google gave up on this market, leaving the whole price range to Chinese models.
Chinese labs are not even in competition mode yet. You'd be seeing them paying you for each token you use when they are in that mode.