This accusation that American models are somehow equivalent in censorship to models that are subject to explicit government driven censorship is obviously nonsense, but is a common line parroted by astroturfing accounts looking to boost China or DeepSeek. Some other comment had pointed out that a bunch of relatively new accounts participating in DeepSeek related discussions here, on Reddit, and elsewhere are doing this.
This accusation that American models are somehow equivalent in censorship to models that are subject to explicit government driven censorship is obviously nonsense, but is a common line parroted by astroturfing accounts looking to boost China or DeepSeek. Some other comment had pointed out that a bunch of relatively new accounts participating in DeepSeek related discussions here, on Reddit, and elsewhere are doing this.
What’s more confusing is where the refusal is coming from. Some people say that running offline removes the censorship. Others say that this depends on the exact model you use, with some seemingly censored even offline. Some say it depends on a search feature being turned on or off. I don’t think we have any conclusions yet, beyond anecdotal examples.
I don’t understand their post on X. So they’re starting with DeepSeek-R1 as a starting point? Isn’t that circular? How did DeepSeek themselves produce DeepSeek-R1 then? I am not sure what the right terminology is but there’s a cost to producing that initial “base model” right? And without that, isn’t a lot of the expensive and difficult work being omitted?
I’ve seen this claim but I don’t know how it could work. Is it really possible to train a new foundational model using just the outputs (not even weights) of another model? Is there any research describing that process? Maybe that explains the low (claimed) costs.
Well it is like a hive mind due to the degree of control. Most Chinese companies are required by law to literally uphold the country’s goals - see translation of Chinese law, which says generative AI must uphold their socialist values:
In the case of TikTok, ByteDance and the government found ways to force international workers in the US to signing agreements that mirror local laws in mainland China:
I find that degree of control to be dystopian and horrifying but I suppose it has helped their country focus and grow instead of dealing with internal conflict.
This is an outrageous claim with no evidence, as if there was any equivalence between government enforced propaganda and anything else. Look at the system prompts for DeepSeek and it’s even more clear.
Also: fine tuning is not relevant when what is deployed at scale brainwashes the masses through false and misleading responses.
But those approaches alone wouldn’t yield the improvements claimed. How did they train the foundational model upon which they applied RL, distillations, etc? That part is unclear and I don’t think anything they’ve released anything that explains the low cost.
It’s also curious why some people are seeing responses where it thinks it is an OpenAI model. I can’t find the post but someone had shared a link to X with that in one of the other HN discussions.
It’s not just the economy that is vulnerable, but global geopolitics. It’s definitely worrying to see this type of technology in the hands of an authoritarian dictatorship, especially considering the evidence of censorship. See this article for a collected set of prompts and responses from DeepSeek highlighting the propaganda:
But also the claimed cost is suspicious. I know people have seen DeepSeek claim in some responses that it is one of the OpenAI models, so I wonder if they somehow trained using the outputs of other models, if that’s even possible (is there such a technique?). Maybe that’s how the claimed cost is so low that it doesn’t make mathematical sense?
In general all these large companies should be required to use open standards or spin off proprietary protocols into an independent open source project.
I’m guessing you don’t know any Microsoft employees who were from that era and sufficiently senior to know. Azure was not run by Nadella. Its predecessor was Bing and much of Azure then was just a reselling of Bing services. Bing was something Ballmer invested in and pushed for. Nadella didn’t drop any limiters or push the Azure perspective - that was people closer to Azure.
Actually there was a lot of open source happening under Ballmer - not because of him but in that time. VSCode’s beginnings were in an earlier similar product were from that time. He didn’t interfere or stop those projects. Attributing that to Nadella is just false.
What makes this so difficult to surface is that the doctors who patients interact with are not really receptive to the idea that nuanced and difficult to diagnose symptoms may be caused by long COVID. They sort of just ignore that suggestion, don’t add anything to any database, etc. I think we are likely missing a lot of potential patterns in patient data because patients aren’t listened to and data isn’t collected.
Distribution is everything. Controlling distribution through defaults (play store already installed), barriers (pop ups warning you that installing other apps is risky), etc is monopolistic.
Most companies now include clauses that force arbitration and prevent you from using a class action lawsuit. This type of sidestepping of the public justice system should be outlawed, retroactively, with retroactive lawsuits (by extending the statute of limitations), retroactive fines, and retroactive jail time.
The market correctly does not care because there is no consequence for the current or prior executives and no financial consequence for the company. All they will do is send out some obligatory notices, mention it in their investor relation materials, maybe offer a year of credit score monitoring, and move on.
We need regulations with massive fines, class action lawsuits (a ban on arbitration clauses), and maybe automatic minimum level compensation to those customers.
https://news.ycombinator.com/item?id=43174298