China uses AI to upgrade textiles, coal and steel manufacturing

This piece is a ground-level look at what Beijing’s “AI Plus” strategy actually means on factory floors. Rather than focusing on headline-grabbing chatbots, it shows textile makers like Bosideng partnering with universities to build generative models that cut sample development time from around 100 days to under a month, and coal and steel-furniture producers wiring whole plants with AI and IoT systems for predictive quality control and unmanned operations. ([globaltimes.cn](https://www.globaltimes.cn/page/202512/1351840.shtml))

For the race to AGI, these deployments matter in two ways. First, they generate exactly the kind of rich, structured data about physical processes and human workflows that advanced agents will need to master in order to act in the real world, not just on text. Second, they create enormous commercial pull for more capable, robust and explainable models that can be trusted with safety-critical decisions in mines, heavy industry and logistics.

If China can systematically apply AI across hundreds of traditional industrial clusters, its demand for compute, custom models and robotics will climb in lockstep. That scale of industrial feedback loop could give Chinese labs a distinctive edge in training AI systems that understand materials, energy and manufacturing constraints—key ingredients for any AGI that aims to design and build in the physical world, not just talk about it.