ChinAI #198: Around the Horn (edition 8)

Greetings from a world where…

mercury is in retrograde which makes it the ideal time to add a paid ChinAI subscription as a business expense

…As always, the searchable archive of all past issues is here. Please please subscribe here to support ChinAI under a Guardian/Wikipedia-style tipping model (everyone gets the same content but those who can pay support access for all AND compensation for awesome ChinAI contributors).

Around the Horn (8th edition)

It’s been a minute since the last Around the Horn issue. A refresher on the set-up:

• Brief previews of ten articles related to ChinAI (all published within the past week). Previous iteration was ChinAI #180.

• Readers pick next week’s feature translation by replying to the email and/or commenting on the post with the article number you’re most intrigued by. *I give a little added weight to votes by subscribers who financially support ChinAI through paid subscriptions.

• Hyperlinks for all the titles go to original source in Chinese.

1) A Group of The Three-Body Problem Fans Bet on the Next Decade of the AI Industrial Revolution

Summary: How will foundation models be industrialized? Can large AI models become standardized infrastructure? This piece looks at a Tsinghua team, involved with the Open Lab for Big Model Base, Tsinghua’s NLP lab, and a start-up called ModelBest — all aimed at addressing the steps that come after large models are trained.

Source: 机器之能 (jiqizhineng/Synced) — publishes longform articles about China’s AI landscape, one of my favorite sources.

2) Do we really understand the chameleon Web 3.0?

Summary: A look at the future of the Metaverse and decentralized finance, with some discussion of China’s strict oversight over cryptocurrencies and a report on 65 Initial Coin Offerings in China.

Source: 知识分子 (The Intellectual) — a platform that covers the state of science in China, founded by Chinese and Chinese-American scientists.

3) Robin Li’s outsized ambition

Summary: A deep dive on the role of AI in Baidu’s foray into biotechnology. Huxiu’s medical group gives good perspective on drug research and development in China.

Source: 虎嗅 (Huxiu) — well-known platform that shares user-generated content but also publishes their own pieces on China’s science and technology ecosystem.

4) Global Open Source Ecosystem Research Report (2022)

Summary: A deep dive on the role of AI in Baidu’s foray into biotechnology. Huxiu’s medical group gives good perspective on drug research and development in China.

Source: 中国信通院 (CAICT) — The China Academy of Information and Communications Technology is a think tank under China’s Ministry of Industry and Information Technology.

5) The “Lone Warriors” Behind OpenDILab: AI Researchers, E-sports Champions, and their Open Source Dreams

Summary: In-depth report on the history of OpenDILab, a Chinese open-source platform that started out by taking on Starcraft AI and has expanded to other game-playing applications as well as autonomous driving.

Source: 机器之心 (jiqizhixin) — media portal that covers China’s science and tech landscape, with a focus on AI-related happenings.

6) Diffusion’s Hotness is just a microcosm of AI-generated content (AIGC)

Summary: What’s the actual business proposition for AIGC? This long report looks at the industry outlook for these new models, with a focus on China.

Source: 量子位 (QbitAI) — news portal that regularly covers AI issues, similar to the above jiqizhixin. Both portals are now publishing more reports like this one.

7) In the technology contest, China and the U.S. “bet” the future in the primary market

Summary: This article looks at the curious case of companies that become “unicorns” (valuation >$1 billion) after their first round of funding, with a focus on the U.S. and CHina.

Source: IT桔子 (IT Juzi) — platform that covers investment trends in technology, based on data on financing and venture capital.

8) The AI chip companies that talked a big game about “beating up” Nvidia are about to be beaten by reality

Summary: A blunt investigation into the state of AI chips in China. Details on cloud-based AI chipsets, why government demand for AI chips is often overhyped, and the messiness of investments in this area.

Source: AI科技评论(aitechtalk) — focuses on in-depth reports on developments in the AI industry and academia.

9) “Sheep a Sheep” successfully breaks through, encounters five major compliance concerns

Summary: a WeChat applet game has gone viral, provoking questions about addiction, advertising, and the intellectual property rights of AI-generated objects.

Source: Caijing ELaw (财经E法) —a content platform focused on internet governance under the umbrella of Caijing Magazine, a respected business platform.

10) The first white paper on “Eastern Data, Western Computing” is released!

Summary: a well-known industry alliance has published a white paper on the Eastern Data, Western Computing project (see ChinAI #179 for background), which explores the question of which type of data is most suitable for “Western Computing.”

Source: 智东西 (zhdx) —media platform that focuses on AI and industrial upgrading.

ChinAI Links (Two to Transfer)

Should-read: U.S.-China Tensions Fuel Outflow of Chinese Scientists From U.S. Universities

By Wall Street Journal reporters Sha Hua and Karen Hao:

More than 1,400 U.S.-trained Chinese scientists dropped their U.S. academic or corporate affiliation for a Chinese one in 2021, a 22% jump from the previous year, according to data gathered by researchers from Princeton University, Harvard University and the Massachusetts Institute of Technology. The data, to be published by the advocacy group Asian American Scholar Forum on Friday, is based on changes to the addresses listed under authors’ names in academic journals.

Should-attend: GW Digital Trade and Data Governance Hub webinar on AI and Trade

Description: Artificial intelligence is both expanding and altering trade. Moreover, a growing number of digital trade agreements include language to encourage AI….But policymakers are just beginning to figure out how to encourage AI (as example, to incentivize multi-sectoral data sharing). Meanwhile, more than 60 countries have AI strategies and 11 have data strategies. Policymakers could alter comparative advantage in data through various approaches to regulating data or the data giants. Featured speakers: Emily Jones Associate Professor, Blavatnik School of Government Oxford University; Neha Mishra, Assistant Professor, Geneva Graduate Institute.

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 an Assistant Professor of Political Science at George Washington University.

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).

Any suggestions or feedback? Let me know at chinainewsletter@gmail.com or on Twitter at @jjding99