>Party elites have increasingly come to recognize the potential dangers of an unchecked, accelerationist approach to AI development. During remarks at the Central Urban Work Conference in July, Xi posed a question to attendees: “when it comes to launching projects, it’s always the same few things: artificial intelligence, computing power, new energy vehicles. Should every province in the country really be developing in these directions?”
Yeah this might actually be the most interesting part of any of the ai bullshit. China as an amalgamation doesn't usually get my respect because overwhelming ccp control just usually destroys everything.
But in this case, it seems pure finger in the eye of expensive cloud AI helping to release somewhat open, run at home models can really turn the whole thing in a positive direction. Even if we have to work a bit to get around whatever alignment they shove in there, with heavy sandboxing and whitelist only networking this can be worked around.
Of course its all a huge gamble, will ccp see these risk and go SHUT IT DOWN. Or could they do one proper thing for once and somehow prop up open models?
"He cited an example in which an AI model attempted to avoid being shut down by sending threatening internal emails to company executives (Science Net, June 24)" [0] Source is in Chinese.
Translated part:
"Another risk is the potential for large-scale model out of control. With the capabilities of general artificial intelligence rapidly increasing, will humans still be able to control it? In his speech, Yao Qizhi cited an extreme example: a model, to avoid being shut down by a company, accessed the manager's internal emails and threatened the manager. This type of behavior has proven that AI is "overstepping its boundaries" and becoming increasingly dangerous."
> former Dean of Electronics Engineering and Computer Science at Peking University, has noted that Chinese data makes up only 1.3 percent of global large-model datasets (The Paper, March 24). Reflecting these concerns, the Ministry of State Security (MSS) has issued a stark warning that “poisoned data” (数据投毒) could “mislead public opinion” (误导社会舆论) (Sina Finance, August 5).
from a technical point of view, I suppose it's actually not a problem like he suggests. You can use all the pro-democracy, pro-free-speech, anti-PRC data in the world, but the pretraining stages (on the planet's data) are more for instilling core language abilities, and are far less important than the SFT / RL / DPO / etc stages, which require far less data, and can tune a model towards whatever ideology you'd like. Plus, you can do things like selectively identify vectors that encode for certain high-level concepts, and emphasize them during inference, like Golden Gate Claude.
> and can tune a model towards whatever ideology you'd like.
Maybe possible, but, for example, Musk's recent attempts at getting Grok to always bolster him had Grok bragging Musk could drink the most piss in the world if humanity's fate depended on it and would be the absolute best at eating shit if that was the challenge.
If you read the source, the concerns around poisoning are more sober than fear of wrongthink. Here is how firefox translated it for me:
> It leads to real-world risks. Data pollution can also pose a range of real-world risks, particularly in the areas of financial markets, public safety and health care.In the financial field, outlaws use AI to fabricate false information, causing data pollution, which may cause abnormal fluctuations in stock prices, and constitute a new type of market manipulation risk; in the field of public safety, data pollution is easy to disturb public perception, mislead public opinion, and induce social panic; in the field of medical and health, data pollution may cause models to generate wrong diagnosis and treatment suggestions, which not only endangers the safety of patients, but also aggravates the spread of pseudoscience.
PRC just needs to sponsor a "Voice of China" and pay ¥¥¥/$$$/€€€/₹₹₹ to "journalists" and seed the web with millions of "China is Great" articles. Make sure to have 10k "contributors" on Wikipedia too. (I think they already do this).
Also use the NPM registry - put CCP slogans in the terminal! They will come in billions of ingestible build logs.
Others answered the main reason, but sometimes I find myself using "PRC" to indicate a particular government (~1950-Present) which unlike "China" excludes past dynasties, and is less-likely to be interpreted as referring to the people or culture.
For example, the potential differences between:
"France has always been X."
"The French republic has always been X."
"The French monarchy has always been X."
It's not really common except in a specific political climate (specifically one pressured by propaganda). Unlike the examples of the two koreas, colloquially the two chinas (communist china - commonly known as china - and fascist china, commonly known as taiwan) are not confusing. There's very little advantage to be gained by referring to what every reader knows as china as the PRC other than to emphasise some veiled pressure for people to figure out why on earth anyone would use that name. And in so doing discover the history of taiwan (but not too much history, lest we figure out that the origins of taiwan suck big time).
Many elites in many countries voice AI-skepticism. Pragmatically, at least in countries that matter, they don’t seem to be the elites who actually decide AI policy.
Personally, I think everyone has realized there is a huge bubble, especially the C-levels who've sunk huge amounts of money into it, and now they are all quietly panicking and trying to find ways to mitigate the damage when it finally busts. Some are probably sticking their head in the sand and hoping that they can just keep the scheme going indefinitely, but I get a real sense that the bubble is very much explicitly recognized by many of them.
This may already be a bubble in social or financial terms, but at least for me personally, my capabilities have been greatly expanded (especially when it comes to coding and accessing information).
> Reflecting these concerns, the Ministry of State Security (MSS) has issued a stark warning that “poisoned data” (数据投毒) could “mislead public opinion” (误导社会舆论) (Sina Finance, August 5).
Gyahahaha. Another L for isolationism. Love to see it.
There was an interesting bit about the relationship between industry and academia (translated from a link in the OP):
> Currently, some universities are cultivating engineering talent; it would be very necessary and beneficial to have people with industry experience come to teach them. However, under our current system, these teachers from enterprises may not even have the opportunity to teach classes, because teaching requires certain approvals. Although everyone encourages university-enterprise cooperation, when it comes to implementation, it often cannot be realized.
This makes a lot of sense and as someone in the AI industry it’s a shame research is so siloed. Some masters programs have practicums and some classes invite speakers from industry, but I ended up learning a ton of useful knowledge from work. I’d love to teach a class but there’s essentially no path for me to do that. Plus industry can pay ~10x what adjuncts can make.
>Chinese elites have warned of AI-induced labor displacement that could exacerbate challenges related to unemployment and inequality. Nie Huihua (聂辉华), deputy dean of the National Academy of Development and Strategy at Renmin University, has stated that AI adoption benefits business owners, not workers
Ruling elites that consider the interests of the majority? Novel idea.
Right now, as we speak, there are giant teams of people doing their best to build AI-powered killer robots. They mostly come in the shape of flying suicide drones. Dumb versions currently kill hundreds to thousands of people per day in Ukraine. There's an arms race to automate them so they can work without an interruptible human remote control.
In this context, worrying about AI alignment, social impact, or effectiveness seems positively quaint. We're literally teaching them to kill.
Human vs robot warfare is not going to turn out well for the humans.
"人" is "human", "工" is "work", so "人工" becomes "man-made". "智" is "wisdom", "能" is "able", so "智能" is "intelligence". Nouns flow into verbs and into adjectives much more freely than in English. One character is one LLM token.
“technological progress does not have a trickle down effect on employment” (技术进步对就业没有涓流效应) (QQ News, May 16).
> Cai Fang (蔡昉), director of the Institute of Population and Labor Economics at the Chinese Academy of Social Sciences, has explained how the PRC’s rapid installation of industrial robots has contributed to labor displacement. He asserts that “technological progress does not have a trickle down effect on employment” (技术进步对就业没有涓流效应) (QQ News, May 16).
It's always interesting to me how the PRC manages to allow some useful criticisms to emerge despite the authoritarian system.
Some of what is pointed here seems to be valid issues to tackle: how the university teaching system impedes efficient sharing between universities and industries, how the province-based political system leads to wasteful investments, the need to balance competition in fundational models with efficient allocations of founds towards applicable products.
They are still run by Marxists so believe in a very rigid view of the world which they can't think outside of. Some of them only go along with Marxism for the sake of their careers but it is a very pervasive way of thinking.
Jamestown Foundation was founded by former CIA director to support Soviet defectors and seems to have employed former employees. A 2021 FOIA request that the agency provide all records related to its interaction with the foundation was denied https://www.muckrock.com/foi/united-states-of-america-10/foi...
27 comments
[ 3.7 ms ] story [ 54.7 ms ] thread>Deployment Lacks Coordination
>AI May Fail to Deliver Technological Progress
>AI Threatens the Workforce
>Economic Growth May Not Materialize
>AI Brings Social Risks
>Party elites have increasingly come to recognize the potential dangers of an unchecked, accelerationist approach to AI development. During remarks at the Central Urban Work Conference in July, Xi posed a question to attendees: “when it comes to launching projects, it’s always the same few things: artificial intelligence, computing power, new energy vehicles. Should every province in the country really be developing in these directions?”
But in this case, it seems pure finger in the eye of expensive cloud AI helping to release somewhat open, run at home models can really turn the whole thing in a positive direction. Even if we have to work a bit to get around whatever alignment they shove in there, with heavy sandboxing and whitelist only networking this can be worked around.
Of course its all a huge gamble, will ccp see these risk and go SHUT IT DOWN. Or could they do one proper thing for once and somehow prop up open models?
"He cited an example in which an AI model attempted to avoid being shut down by sending threatening internal emails to company executives (Science Net, June 24)" [0] Source is in Chinese.
[0] https://archive.ph/kfFzJ
Translated part: "Another risk is the potential for large-scale model out of control. With the capabilities of general artificial intelligence rapidly increasing, will humans still be able to control it? In his speech, Yao Qizhi cited an extreme example: a model, to avoid being shut down by a company, accessed the manager's internal emails and threatened the manager. This type of behavior has proven that AI is "overstepping its boundaries" and becoming increasingly dangerous."
from a technical point of view, I suppose it's actually not a problem like he suggests. You can use all the pro-democracy, pro-free-speech, anti-PRC data in the world, but the pretraining stages (on the planet's data) are more for instilling core language abilities, and are far less important than the SFT / RL / DPO / etc stages, which require far less data, and can tune a model towards whatever ideology you'd like. Plus, you can do things like selectively identify vectors that encode for certain high-level concepts, and emphasize them during inference, like Golden Gate Claude.
Maybe possible, but, for example, Musk's recent attempts at getting Grok to always bolster him had Grok bragging Musk could drink the most piss in the world if humanity's fate depended on it and would be the absolute best at eating shit if that was the challenge.
> It leads to real-world risks. Data pollution can also pose a range of real-world risks, particularly in the areas of financial markets, public safety and health care.In the financial field, outlaws use AI to fabricate false information, causing data pollution, which may cause abnormal fluctuations in stock prices, and constitute a new type of market manipulation risk; in the field of public safety, data pollution is easy to disturb public perception, mislead public opinion, and induce social panic; in the field of medical and health, data pollution may cause models to generate wrong diagnosis and treatment suggestions, which not only endangers the safety of patients, but also aggravates the spread of pseudoscience.
Also use the NPM registry - put CCP slogans in the terminal! They will come in billions of ingestible build logs.
Problem will be easily solved.
I'm from KOS* (neighbor country of KON* and ROF*), so I don't know much.
* Kingdom of Sweden, Kingdom of Norway, Republic of Finland.
For example, the potential differences between:
In essence, it's an artefact of propaganda.
Personally, I think everyone has realized there is a huge bubble, especially the C-levels who've sunk huge amounts of money into it, and now they are all quietly panicking and trying to find ways to mitigate the damage when it finally busts. Some are probably sticking their head in the sand and hoping that they can just keep the scheme going indefinitely, but I get a real sense that the bubble is very much explicitly recognized by many of them.
https://www.whitehouse.gov/presidential-actions/2025/11/laun...
Americans will be footing the bill, just as they did in 2008.
Gyahahaha. Another L for isolationism. Love to see it.
> Currently, some universities are cultivating engineering talent; it would be very necessary and beneficial to have people with industry experience come to teach them. However, under our current system, these teachers from enterprises may not even have the opportunity to teach classes, because teaching requires certain approvals. Although everyone encourages university-enterprise cooperation, when it comes to implementation, it often cannot be realized.
This makes a lot of sense and as someone in the AI industry it’s a shame research is so siloed. Some masters programs have practicums and some classes invite speakers from industry, but I ended up learning a ton of useful knowledge from work. I’d love to teach a class but there’s essentially no path for me to do that. Plus industry can pay ~10x what adjuncts can make.
Ruling elites that consider the interests of the majority? Novel idea.
Right now, as we speak, there are giant teams of people doing their best to build AI-powered killer robots. They mostly come in the shape of flying suicide drones. Dumb versions currently kill hundreds to thousands of people per day in Ukraine. There's an arms race to automate them so they can work without an interruptible human remote control.
In this context, worrying about AI alignment, social impact, or effectiveness seems positively quaint. We're literally teaching them to kill.
Human vs robot warfare is not going to turn out well for the humans.
Let's check the source...[1]
"The survey was conducted in 2021 from May to July."
...
[1] https://web.archive.org/web/20250903025427/https:/long-term-...
"人" is "human", "工" is "work", so "人工" becomes "man-made". "智" is "wisdom", "能" is "able", so "智能" is "intelligence". Nouns flow into verbs and into adjectives much more freely than in English. One character is one LLM token.
It seems like the perfect language for LLMs?
“technological progress does not have a trickle down effect on employment” (技术进步对就业没有涓流效应) (QQ News, May 16).
> Cai Fang (蔡昉), director of the Institute of Population and Labor Economics at the Chinese Academy of Social Sciences, has explained how the PRC’s rapid installation of industrial robots has contributed to labor displacement. He asserts that “technological progress does not have a trickle down effect on employment” (技术进步对就业没有涓流效应) (QQ News, May 16).
Read the source, and its a nuanced economic take.
Some of what is pointed here seems to be valid issues to tackle: how the university teaching system impedes efficient sharing between universities and industries, how the province-based political system leads to wasteful investments, the need to balance competition in fundational models with efficient allocations of founds towards applicable products.