ChinAI #96: The "flexible" transformation of "straight-guy" manufacturing

Plus, China's AI talent shortcomings and Trump's additional restrictions on Chinese students

Greetings from a land where when shit hit the fan, is you still a fan?

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Feature Translation #1: The "flexible" transformation of "straight-guy" factories

Context: The conversion of production lines of major factories to producing anti-covid materials such as masks, protective clothing, and ventilators has brought “flexible manufacturing” back into the spotlight. Flexibility in manufacturing = ability to customize design of certain project, manufacture in smaller batches, allow for more variation in parts assembly. Why does flexible manufacturing matter and where does China stand?

This week we dive back into Taihe, a platform on China’s defense/smart manufacturing industry introduced a couple weeks back. In that piece I mentioned how Taihe not only writes articles like this week’s feature translation, but also do think tank/consulting things as well as “supply-demand linkage services” (供需对接). The Taihe editor clarified to me that 供需对接 mainly means helping companies with product/tech find market fits in the industrial chain. Also, I mentioned how Taihe’s 2018 year-in-review post was scrubbed from the web — the editor told me it’s still up in some places, and I was able to track it down. Those interested can read it here.

Key Takeaways:

  • The upshot: the vast majority of Chinese factories, especially in high-end manufacturing, are very far away from getting to flexible manufacturing

  • Taihe argues this goes against the dazzling data covered in the news about how star companies have converted their production over to anti-epidemic materials. Per China’s General Administration of Customs statistics: from March 1 to April 30, a total of 27.8 billion masks, 130 million pieces of protective clothing, and 73.41 million copies of covid detection kits, and 49,100 ventilators were exported.

  • Who are the star companies that give the illusion of a flexible manufacturing paradise? BYD, a car/battery manufacturer backed by Warren Buffett’s Berkshire Hathaway, switched over to mass production of automated mask production equipment in over half a month starting in the end of January. Aviation Industry Corporation of China (AVIC), known for making fighter jets, is now making automatic mask makers.

  • Overall, though flexible manufacturing has lagged in China due to two main factors: 1) demand — why buy equipment with large upfront costs when you can just hire a bunch of cheap labor?); 2) technology — software and the lack of a strong machine tool industry

  • Forget Industry 4.0: the article cites experts arguing that China still needs to start from 3.0 or even 2.0. One senior expert, who returned from Germany to set up a factory to work on high-precision aerospace parts processing, recounts how the knowledge of Industry 4.0 learned in Germany could not be used in the domestic production line, since it still needed to start from 3.0 or even 2.0.

  • “This can also be seen in the production of epidemic prevention materials. The conversion of low-end products such as masks and protective clothing can quickly keep up with demand. However, the production of ventilators, which is more difficult, began to show timidity, and a large number of overseas orders have been pushed back to be fulfilled at the end of the year.”

I was able to get halfway through this as it has a lot of technical material. *Let me know if you’re interested in taking a stab at the rest of the piece. I threw the Google Translate version in for the rest of the piece and you can actually get the general gist of the info. For those interested in my translation process, which does always start with running everything through Google Translate, I reflected on the current state of neural machine translation using an example paragraph from this article:

READ FULL TRANSLATION: The "flexible" transformation of "straight-guy" factories

Feature Translation #2 - Five Shortcomings of China’s AI Talent System

Thanks to Dahlia Peterson for contributing this translation of an August 2019 Xinhua news article on China’s AI talent shortcomings. The five key obstacles:

  1. Supply of AI talent can’t catch up to demand — not a problem unique to China

  2. Large gap in top/outstanding talents

  3. Uneven structural distribution for talent — key point here is that the linkages between industry-academia for AI skill formation are not that dense

  4. Severe brain drain of outstanding AI talents

  5. Weaker technology ethics education

In the wake of the Trump Administration’s recent executive order to restrict the entry of graduate students and researchers from China, a paragraph from shortcoming #4 may be especially relevant: “China has a severe brain drain of outstanding AI talents…However, against the international backdrop of the United States exerting pressure on China's high-tech fields, experts believe that there may be opportunities to enrich China's AI talent pool. China should take this opportunity to create a better environment for outstanding Chinese students and scholars to choose to study or work in China.”

Thanks to Dahlia for contributing this important translation. For further reading, see her co-authored piece with Remco Zwetsloot which argues that the U.S. is throwing away its comparative advantage in attracting the world’s best and brightest and that immigration reform should be a U.S. national security priority.

READ FULL TRANSLATION: 5 Shortcomings of China’s AI Talent

ChinAI Links (Four to Forward)

Must-read: Yangyang Cheng’s Monthly SupChina Column

One of my must-reads every month: Yangyang Cheng’s column takes Mara Hvistendahl’s new book The Scientist and the Spy, which recounts the arrest of Chinese national/US permanent resident Mo Hailong for stealing trade secrets, as a springboard into what I can only describe as what happens when you mix breathtakingly precise surgery and deeply reflective art onto the written page. I don’t know how to recommend this more other than to say this: Reading it will make you a better person, and if more people who were involved in crafting Trump’s recent executive order read this piece, we would be a better nation.

Should-read: 1989 article titled “Hong Kong on Borrowed Time”

A haunting read from the NYT archives by Margaret Scott on the events of 1989: “Earlier this month, while China's leaders were staging a grandiose celebration of their revolution's 40th birthday, thousands of somber Hong Kong residents gathered for a dreary commemoration of their own. Far from the fireworks display in Beijing, Hong Kongers huddled in a rainstorm near the bronze statue of Queen Victoria, singing patriotic songs and listening to mournful poems dedicated to those who died in Tiananmen Square.”

Should-read: The US-China Tech Wars: China’s Immigration Disadvantage

Re-plugging the article by Remco and Dahlia for The Diplomat from earlier. It certainly sticks the landing: “A decade ago, longtime Singapore leader Lee Kuan Yew predicted that China would not overtake the United States in the 21st century because China’s “Sino-centric” culture would force it to rely mainly on its domestic workforce, while the United States’ openness meant that it could draw the best and brightest from a global talent pool of 7 billion and stimulate innovation through diversity. His argument still rings true today. Whether it also will another decade down the line is up to U.S. policymakers.”

Should-read: “National Language” in the Xinjiang Uyghur Autonomous Region

A fascinating journey into the use of the term Guóyǔ 国语 ("National Language") for "Mandarin" in Xinjiang today — a path that intersects with Han-centrism, Chinese national identity, repression of Uyghurs in Xinjiang. From Language Log — a blog that explores the intersection of language, translation, and politics.

Thank you for reading and engaging.

These are Jeff Ding's (sometimes) weekly translations of Chinese-language musings on AI and related topics. Jeff is a PhD candidate in International Relations at the University of Oxford and a researcher at the Center for the Governance of AI at Oxford’s Future of Humanity Institute.

Check out the archive of all past issues here & please subscribe here to support ChinAI under a Guardian/Wikipedia-style tipping model (everyone gets the same content but those who can pay for a subscription will support access for all).

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