jhancock
An example of the ugly side of China private lending is what is termed "flesh loans". A young girl is forced to have nude pictures taken of her to secure her high interest loan repayment. Ant was going to put hundreds of billions in capital backing loans that had loosely controlled and often unethical/violent collections system.
Yes, curtailing loads of easy capital can be at odds with pressing domestic consumption growth. In this case, I think the government made a tough but decent decision.
Political priorities and good governance is why we have government.
From a practical perspective, I'm not sure any servers are safe anywhere...depending on who may want your data.
This is the part that really irks me: LinkedIn and Github know this is the end goal of many of the rampant supply chain attacks but they a) don't have a first class mechanism for reporting b) don't seem to be improving their systems or even warning people. I have been hit be this enough times that I follow along to get screenshots of the scammer. One might think with all the surveillance systems Microsoft/LinkedIn/Github/Google-Meet/Calendly have in place that a potential victim reporting it along with an actual picture of the scammer could get us somewhere.
LLMs are simply trained on inputs. For topics such as this you cannot expect the "correct answer" as it requires a nuanced discussion and more background info.
In short, its an inappropriate question be asking any LLM. This is the sort of thing that requires a small study group of human minds...open ones.
You could start here: https://www.cjr.org/behind_the_news/the_myth_of_tiananmen.ph...
Does the content of this article resonate with what you hear from western media on the subject every year?
The article states: "Most applications are built on an architecture like the one above, where there are a number of stateless horizontally scaleable server replicas that can handle client requests."
Using the library I built, I have yet to worry about this as Clojure core.async, http libs and Java VM are so rock solid, I don't have a fragile set of stateless servers. Sure, at some point there are rare edge cases but it's nice to get very far along without worrying about them.
z.ai did go public on the HK exchange. They are under pressures similar to other public companies.
I know that China models are increasingly being trained and run using Huawei chips instead of Nvidia. I know China has a surplus of electricity from renewables (wind, solar, hydro).
I've been using GLM for over 6 months and pretty happy.
Only academic models will be true open source as companies can't legally afford to disclose learning inputs.
In regards to "They want to train models on our engineering to replace us". Some software engineers in China can run circles around some of the best teams in Silicon Valley. Days of U.S. hegemony are over. I recommend you make peace and make friends.
codex handles longer sessions but the quality seems to decline and it tends to over engineer and lose focus. It will happily add slop on top of slop...which may pass immediate tests of "code works" but doesn't pass my criteria of "code as craft"
I'm using z.ai GLM with opencode. It's obvious when GLM loses its mind when the session gets too long.
I've been using AI to support programming for around 3 years now. The models have gotten amazing. However, unless there is a significant breakthrough I have determined that it's best for me to focus on short sessions.
I a) organize my work, b) improve my AGENTS.md, ensure source has appropriate comments to guide the models to the patterns and separation of concerns c) use shorter sessions d) review and test without AI. This approach means I still own my code. The AI is just an assistant.
With this approach GLM-5.1 is an excellent model. I never run out of token allotment on z.ai or codex plans. At this point, I only keep my OpenAI subscription as the ChatGPT desktop app is excellent at long web research tasks and I get codex with it.
I usually want the codex approach for code/product "shaping" iteratively with the ai.
Once things are shaped and common "scaling patterns" are well established, then for things like adding a front end (which is constantly changing, more views) then letting the autonomous approach run wild can *sometimes* be useful.
I have found that codex is better at remembering when I ask to not get carried away...whereas claude requires constant reminders.
Anyone else using this approach? Ideas on improvements?
Anything else that should be locked down?
* The Shanghai and Hong Kong stock market seems to have improved regulatory enforcement. I have no way of measuring this...just stories from others.
* Over the past 10 years the China gov pressed on with building more housing in part to dilute value. Each year they have warned that houses are for living, not speculation. Last year, they dumped a huge amount of cheap lending into the market to provide movement...warning this is the last step...a month ago the 2026 gov priorities list removed protecting the housing market...first time in modern history. Expectation is the next two years will see realized losses in property. It would be a huge mistake if the gov hasn't ensured regulatory enforcement of other segments have not reached maturity for the retail investor. We'll see...
* As for civil courts, over the past 20 years I've run into quite a few stories from friends and business colleagues that needed to go to China court. The stories are similar to what you may hear in the US. No one suggested the court/process itself was dodgy/unfair.
If your hypothetical happens, yes. China has been working hard to turn domestic investment away from housing. A trustworthy domestic stock market is key.
The vague description "run by the central government as a province rather than a city" is uninformative.
Lived in Shanghai 10 years. The city is well run for something of its magnitude. Mostly competent leadership and cultural alignment.
Yes, that 70's experience was better...and it's still here, refined and built on modern tooling and runtimes.
On whole, if I compare my AI assistant to a human worker, I get more variance than I would from a human office worker.