@ChineseWSJ: #HotReadThisWeek Through innovation and imitation, computer scientists from Chinese university labs are closely following in the footsteps of Anthropic and OpenAI. Tang Jie, Yang Zhilin, and their research colleagues are building a virtual Silicon Valley in major Chinese tech centers, as they 'are very good at monetizing research outcomes'.
Summary
Computer scientists from Chinese university labs are closely trailing Anthropic and OpenAI through innovation and imitation, building a virtual Silicon Valley, and excelling at monetizing research outcomes.
View Cached Full Text
Cached at: 08/30/26, 06:10 PM
#Trending This Week: Chinese computer scientists emerging from university labs, through innovation and imitation, are closing in on Anthropic and OpenAI. Tang Jie, Yang Zhilin, and their research peers are building a virtual Silicon Valley across China’s major tech hubs, proving they “really know how to commercialize research.” https://t.co/D16q7Aiyx6
Similar Articles
@dongxi_nlp: A very valuable article, the last 6 takeaways are worth pondering. Among them, the last two: 5. The data industry is far from developed. Anthropic and OpenAI spend over $10 million on a single environment, while Chinese AI labs have a 'build rather than buy' mentality. 6. Countless...
The article summarizes the current state of the AI data industry, pointing out that the data industry is not yet mature. Anthropic and OpenAI spend over $10 million on a single environment, while Chinese AI labs tend to build rather than buy. In addition, many labs have access to Huawei chips but still crave more Nvidia chips.
@shitunote: Andrew Ng: I might be the only person in the world who has had both Sam and Dario work under me. “One thing I absolutely wouldn’t have guessed a few years ago is that China would eventually become much more open than the US in terms of AI innovation. I know the US AI ecosystem very well because I founded Google Brain, etc. I might be the only person in the world who has had both Sam and Dario work under me. So I am very familiar with their teams. When ChatGPT was released in late 2022, the US was far ahead of China. But since then, China has played its cards well—betting on open source and open-weight ecosystems. Chinese teams do research and publish their research papers for free on the internet, accessible to anyone. By the way, many top US teams extensively read Chinese research papers, learn from them, and benefit. Frankly, many technologies used by top US teams now come from research innovations learned from China. So I think knowledge sharing is a two-way street.”
Andrew Ng shares personal experience, noting that Sam Altman and Dario Amodei once worked under him, and comments that China is more open than the US in AI innovation, making progress through open source and open-weight ecosystems. Knowledge exchange between China and the US has become bidirectional.
@ChineseWSJ: #HotReadsThisWeek OpenAI, which once sparked the AI boom, now lags behind competitor Anthropic. The company is striving to catch up and regain its momentum. OpenAI recently not only released a "super app" but also launched a new model. In addition, the industry's growing backlash against Anthropic has also benefited O…
According to The Wall Street Journal, OpenAI, which once sparked the AI boom, has now fallen behind rival Anthropic and is working hard to catch up. Recently, OpenAI released a super app and a new model, while also benefiting from the industry's backlash against Anthropic.
China’s Open AI Models Are Challenging Silicon Valley’s Playbook
Chinese AI labs release competitive open-source models (GLM 5.2, Kimi K3, Qwen 3.8) that challenge Western closed-source dominance, sparking US political backlash and highlighting the diverging open vs. closed AI paths between China and Silicon Valley.
@snowboat84: To add a supplementary note, regarding the phenomena emerging from AI—scaling laws, emergence, double descent, representation geometry—the papers discussing them are already numerous. But there is a big problem: they are all thinking in the way of computer scientists, not physicists. What is a computer sci…
The author comments that current AI research overuses the thinking style of computer science and lacks a physics-based approach, proposing the need to establish an ideal system like 'Cyber Space' to lay a theoretical foundation.