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The State of Chinese AI Apps 2025 (techbuzzchina.substack.com)

submitted 2 days ago by yogthos@lemmygrad.ml to c/technology@lemmygrad.ml

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[–] o_d@lemmygrad.ml 5 points 2 days ago (1 children)

Comparing ARR of US and Chinese companies is comparing apples with big macs. The author completely ignores that the major consumers paying for AI in the west are governments and other big tech companies, not its end users. This is true for Chinese companies as well, as is mentioned in the article. The large disparity in revenue however, highlights the fact that US companies operate as a cartel whereas Chinese companies do not.

What are you thoughts on the author's conclusions? Nothing in the article seems to back-up the assumptions that Chinese companies will be more focused on the international market than the domestic one, or that they will be more focused on dev tools, support and chatbots, etc. in the near future.

[–] yogthos@lemmygrad.ml 8 points 2 days ago (1 children)

I expect that Chinese companies will focus both on domestic and international markets. Releasing models in the open is a clear appeal to international markets, and it's a way to ensure that Chinese models become the global standard setters going forward. I haven't really seen any indication to suggest which markets companies are favoring, but there are big pushes in places like Africa right now. So, global market is seen as being important at the very least.

In terms of focus, it seems like it's going to be on practical applications, and integration of AI tools into existing products as we see Alibaba doing with Qwen. There does seem to be a steady push in terms of dev tools, Kimi 2.5 is a good example of that. IQuest coder is another recent innovative model that's been trained on git histories for projects to understand how code evolves. Strong coding models is a really important application for LLMs and I think there's going to be a big push in that area in the coming years.

[–] o_d@lemmygrad.ml 3 points 1 day ago (2 children)

[...] there are big pushes in places like Africa right now.

Oh that's interesting. What areas does this push in Africa focus on?

As for dev tools, I think the verdict is still out on whether AI is actually beneficial. Being able to skip the tediousness of typing out some boilerplate can be nice, but the push to use these tools in the west is all encompassing. I've seen a lot of studies that suggests these tools are actually reducing productivity, all while lowering peoples job satisfaction. I've also noticed an increased lack of ability to read and reason about code in less experienced devs. This is a much more problematic bottleneck than the speed of writing code.

I'm not familiar with how these tools are used in China. I have to assume they take a much more pragmatic approach. The goal in the west is certainly to get these models to a place where a junior dev plus an AI tool can replace a senior dev, reducing labour costs. The reduced productivity is seen as a temporary cost to achieve this ultimate goal.

[–] yogthos@lemmygrad.ml 3 points 1 day ago

Bloomberg actually had a good article on this if you ignore the biases. Basically, DeepSeek and other Chinese companies are starting to get used by African companies to build stuff on top of. And since API costs are a fraction of what US companies charge, they're far more popular. On top of that, some companies in Africa are starting to run self hosted models too.

I've been using AI coding tools for the past half a year and I can definitively tell you that they are beneficial. There's no question about that. What we see is that people are still learning to use these tools effectively, and that they're not magic. But once you spend enough time with them, they really do work well.

I've seen the studies you refer to and the problem is that they often have low sample sizes, and that a lot of experienced devs don't really want to use these tools. So, when you have a situation of people who are already biased against this tech, they're obviously not going to be effective at using it. However, that doesn't mean this tech isn't effective.

Personally, I haven't seen much evidence to support the arguments that the code is harder to read and reason about either. The code LLMs produce is often a lot better than the code I've seen written by hand.

All that said, these tools absolutely cannot replace senior devs in their current state. The one thing I've consistently noticed is that you have to be very specific with instructing the model on how the problem should be solved. If you just tell it to do something in a general way, it will almost certainly produce a poor solution. However, if you tell it the steps you want, then it can follow instruction well. And developing the intuition on how to approach a particular type of problem is precisely what makes an experienced dev. A junior who doesn't have enough experience to understand what the correct solution should look like will not be able to instruct the LLM on what needs to be done.

[–] Comprehensive49@lemmygrad.ml 5 points 1 day ago* (last edited 1 day ago) (1 children)

AI for coding is very useful, assuming you're already a senior dev. It allows one senior dev to replace four or five junior devs, ultimately annihilating the market for junior devs. Unlike junior devs, senior devs already know how code should run, so verifying the AI isn't an issue. Instead of senior devs having to "waste time and productivity" training junior devs, senior devs can instead spin up four or five AI agents and supervise them, commanding them to write the code and then review the code at the end.

Now, the question arises, "what will happen when these senior devs retire?" There is no answer to that. The idea is by that time, all dev work will be replaced by AI.

[–] o_d@lemmygrad.ml 3 points 1 day ago

This logic doesn't really track in my experience. Hiring junior devs was never about writing production code. It's an investment with the understanding that a junior will develop into an intermediate and senior in the future. It generally takes more time to mentor a junior and review their code than to simply code it myself. In addition, doing it myself will certainly result in higher quality, scalable, maintainable code.

This is the contradiction. Many seniors are seeing their productivity decline, because being forced to use AI is like mentoring 1 or 2 or 3 or 4 etc. juniors. The AI doesn't improve based on your individual mentorship making this a different type of "investment", if you can even call it that. This isn't about productivity or investing in labour. It's about creating a system by which the value of your labour power can be reduced.