ChinAI #43: ChinAI as Two Kung-fu Styles (the Sword and the Qi)

Only Baidu and Huawei are Really Doing AI?

Welcome to the ChinAI Newsletter!

These are Jeff Ding's weekly translations of writings on AI policy and strategy from Chinese thinkers. I'll also include general links to all things at the intersection of China and AI. Please share the subscription link if you think this stuff is cool. Here's an archive of all past issues. *Subscribers are welcome to share excerpts from these translations as long as my original translation is cited.

I'm a grad student at the University of Oxford where I'm based at the Center for the Governance of AI, Future of Humanity Institute.

A Panorama of China’s AI Industry: 3 Layers (Foundation, technology, application), 4 Giants (Baidu, Alibaba, Tencent, and Huawei)

Here’s one core thesis that this newsletter is attempting to test. When it comes to certain areas of China coverage, especially technology, if you are not spending at least 60% of your time reading Chinese-language materials or translations of Chinese-language materials, then you’re missing a lot of the story. It’s nice to see that others who have read 50+ papers in researching AI in China have come to the same conclusion.

In some weeks, I seriously consider upping that percentage to 80% because of a particularly cool article. This is one of those weeks.

This week’s feature translation, titled “A Map to Understand China’s AI Close-quarters Combat: Only Baidu and Huawei are Really Doing AI,” comes from the Huxiu.com, a platform that shares user-generated content but also comes out with their own pieces (this week’s translation is the latter). It was viewed 100,000+ times since being published last week.

Let’s do a brief preview of the full translation on the Google doc linked below:

  • Pages 1-3: Background on why Chinese tech companies are turning toward AI

  • Page 4-5: A very large, nifty visualization of China’s AI ecosystem (it’s a huge graphic, so I’ll paste it into the bottom of this email) — dividing it into three layers (application, technology, and foundation *this is an example of how we can start raising the bar for AI analysis, go one step further and specify what type of AI you are talking about), and grouping companies according to their ties to four giants (Baidu, Alibaba, Tencent, and (interestingly/questionably) Huawei). I want to eventually get out a translation of this graphic and all the companies mentioned. If any ChinAI readers want to contribute or even take the lead on this please let me know.

  • Page 6-7: The application level, the AI products that we ordinary users can intuitively grasp. Piece argues that Alibaba/Tencent are AI-izing their existing areas of advantage but Baidu is a trailblazer in doing something divergent from their corporate genes by going for it in autonomous driving. The piece presents some really interesting arguments and analogies but I think it’s overly biased toward Baidu/Huawei, and underestimates how crucial Qi Lu was to Baidu’s AI strategy.

  • Pages 8-9: The technology level - here’s where it gets fun with a running analogy based on a martial arts novel by Jin Yong (dubbed China’s Tolkien). Full translation has some more background but the gist is that in both of the lower AI layers (tech and foundation), we start to see a Sword-style kung-fu faction (Alibaba and Tencent) that look to optimize existing processes with AI quickly vs. a Qi-style kung-fu faction (Baidu and Huawei) who put more energy into open platforms and complete sets of mature AI solutions (e.g. Baidu’s DuerOS, and Apollo in autonomous driving).

  • Pages 10-11: The foundation level - extends the Sword vs. Qi analogy and shows how it applies in this domain (examples are Baidu’s PaddlePaddle, a deep learning open source framework, and Huawei’s AI chips)

  • Page 12: Conclusion and caveat: “However, Baidu and Huawei's Qi-style route is not necessarily the best choice. At least for Baidu, at the moment, it is suffering relative losses.”

A Map to Understand China’s AI Close-quarters Combat: Only Baidu and Huawei are Really Doing AI

This Week's ChinAI Links

Chinese phrase of the Week:  笑傲江湖 (xiao4ao4 jiang1hu2) - The Smiling Proud Wandering, a wuxia novel by Louis Cha (Jin Yong was his pen name). This is the book that the Qi-style and Sword-style factions are drawn from.

Jin Yong died at age 94 in three months ago in October 2018. From The Guardian’s obituary: “On Wednesday, Cha’s profile on the search engine Baidu was turned to black and white. On Taobao, the e-commerce giant founded by Jack Ma, also a fan, customers who searched for Jin Yong related products were greeted with Cha’s photo and a famous quote from one of his novels: ‘Look at the clouds, gathering and dispersing, dispersing and then gathering. Life is this.’ ”

Another must-read report by colleagues at Center for the Governance of AI (GovAI), Baobao Zhang and Allan Dafoe, on the American public’s attitudes on AI. One complicated finding that you’ll have to read the full report to tease out: “Americans, in general, weakly agree that the U.S. should invest more in AI military capabilities and cooperate with China to avoid the dangers of an AI arms race.”

Friend of the newsletter Austin Wu is generously sharing his notes on Kai-fu Lee’s AI Superpowers book, if you haven’t gotten around to reading the whole thing.

My thing I’m gonna keep harping on is think tank transparency. Transparify is an organization doing good work rating the extent to which think tanks disclose their donors.

Here’s that full panoramic map from Huxiu:

Thank you for reading and engaging.

Shout out to everyone who is commenting on the translations - idea is to build up a community of people interested in this stuff. You can contact me at jeffrey.ding@magd.ox.ac.uk or on Twitter at @jjding99

ChinAI #42: Cloudy AI

Welcome to the ChinAI Newsletter!

These are Jeff Ding's weekly translations of writings on AI policy and strategy from Chinese thinkers. I'll also include general links to all things at the intersection of China and AI. Please share the subscription link if you think this stuff is cool. Here's an archive of all past issues. *Subscribers are welcome to share excerpts from these translations as long as my original translation is cited.

I'm a grad student at the University of Oxford where I'm based at the Governance of AI Program, Future of Humanity Institute.

A BAT Confrontation on the Cloud

Hope everyone’s 2019 has gotten off to a Cumulus cloud-like start. This week’s translations float a bit in China’s cloud computing scene. Cloud infrastructure could make AI capabilities more accessible (e.g. France's AI strategy mentioned creating European-wide private cloud for AI research); at the same time, machine learning capabilities can help optimize and manage cloud infrastructure.

The first translation, a nice overview of the cloud computing skyscape in China and the world, comes from Caijing - a respected business and financial news platform (quite impressive breadth and depth of interviews in this article). Some key takeaways:

  • All three BATs have elevated their cloud division as strategic business lines but Alibaba was way ahead to the trend (Alibaba Cloud formed in 2009, Tecent Cloud in 2013, Baidu Cloud in 2015)

  • Overall market size of China's public cloud services in the first half of 2018 exceeded US$3 billion, Alibaba Cloud's market share reached 43%, followed by Tencent Cloud (11%) and China Telecom (8%). There’s a similar breakdown for the overall Chinese domestic cloud computing market (Alibaba has more than half of the market).

  • Globally, the prediction is that Alibaba will join Amazon, Microsoft, and Google in the oligopolistic public cloud market (think cloud computing solutions for government organizations). But there is still a great deal of uncertainty about who will succeed in private cloud and hybrid cloud markets, especially in China as only 30.8% of Chinese companies used cloud services in 2018, while 80% of U.S. companies were “on the cloud.”

  • One trend to watch: in the past two years, China has made significant efforts in independent, controllable (innovation), and it has encouraged domestic cloud computing to be independent and controllable. Yan Dong, dean of the BAT·Innovation Institute, told Caijing.com that, particularly from a security perspective, getting rid of “foreignization” is an inevitable trend.

READ FULL TRANSLATION: A Confrontation on the Cloud: the future configuration of the BAT may be reshaped

Review of Major Cloud Security Incidents in 2018

What better way to start 2019 than to review all the serious vulnerabilities of information infrastructure exposed by major security incidents in the past year? That’s the subject of this second translation from IDC’s Chinese media platform (IDC is a global consultancy focused on tech that has had a branch in China since 1982). It covers the five major cyberattacks, five major data breaches, and five downtime events of 2018, many of which involved Chinese actors as both perpetrators and victims.

Many of these I had never heard of:

  • Tencent was the target of three of the major cyberattacks, two of which went after Tencent Cloud and the other was a“blackmail virus” that infected WeChat Pay.

  • In June, Someone got ahold of 1 billion pieces of YTO Express — very large Chinese delivery company, in top three along with SF and China Post probably — delivery data, which included name of sender, phone number, address info, and was selling it for one bitcoin on the dark web

  • Also in June, Alibaba Cloud had a large-scale breakdown due to a bug triggered by routine operation and maintenance update, which affected “half of the country’s Internet” (recall the prevalence of Alibaba Cloud infrastructure in the first translation)

Waving Goodbye to a Frustrating 2018, Cloud Computing Will Regain Confidence in 2019

This Week's ChinAI Links

Chinese phrase of the Week:  新瓶装旧酒 (xin1ping2 zhuang1 jiu4jiu3) - old wine in a new bottle, figurative meaning is it’s the same stuff with just a new external label; apparently Baidu’s Robin Li used this phrase to describe cloud computing at a summit back in 2010.

My home base, the Center for the Governance of AI (GovAI), did some awesome work this past year, as captured in our annual report — compiled by our research manager, Markus Anderljung.

The annual AI index 2018 report is a must-read, grounding the conversation about AI in metrics - and the convenors go further to challenge the assumptions and invite expert feedback on those metrics. One China-related tidbit: “Combined AI + ML course enrollment at Tsinghua University was 16x greater in 2017 than it was in 2010.”

MIT Tech Review’s Jan/Feb issue looks at China’s tech scene. You’ll find a short piece of mine in there on self-driving car startups with bases in both China and America, but the one I was blown away by was Yangyang Chen’s story on the University of Science and Technology of China, which goes back through her own family’s history and the relationship between science and state.

Tsinghua University’s December 2018 white paper on AI chip technology - English version linked at the bottom.

Thank you for reading and engaging.

Shout out to everyone who is commenting on the translations - idea is to build up a community of people interested in this stuff. You can contact me at jeffrey.ding@magd.ox.ac.uk or on Twitter at @jjding99

ChinAI #41: The Human Labor Behind AI

Welcome to the ChinAI Newsletter!

These are Jeff Ding's weekly translations of writings on AI policy and strategy from Chinese thinkers. I'll also include general links to all things at the intersection of China and AI. Please share the subscription link if you think this stuff is cool. Here's an archive of all past issues. *Subscribers are welcome to share excerpts from these translations as long as my original translation is cited.

I'm a grad student at the University of Oxford where I'm based at the Governance of AI Program, Future of Humanity Institute.

GQ China Longform Piece on The Human Labor Behind AI

Hope everyone has a great holiday season - we’ll be back in 2019 but signing off this year with a weighty translation on the people who work for data labeling workshops in China. In 2007, when Princeton University assistant professor and computer vision expert Fei-fei Li first started annotations for Imagenet, she hired a group of Princeton undergraduates for $10/hour. Ten years later, this experiment has evolved into an industry of data workshops found throughout the small fourth, fifth-tier towns of Henan, Shandong, Hebei, and other areas.

The piece follows the stories of Ma Mengli, a worker in a data annotation company Qianji Shuju, and one of the company’s founders, Liu Yangfeng. There’s just so much packed in here: they visit a noodle restaurant made famous by an internet streamer, swap stories about giving away free counterfeit Tide laundry liquid to sign people up on finance apps — and it touches on some important broader themes: concern about personal privacy in collecting photos of people, how long the data annotation industry will last and the replaceability of human labor, differences between people we follow in the story and their interactions with workers from top AI startups in Beijing.

READ FULL TRANSLATION: THOSE WHO WORK FOR AI

AI Security White Paper

In September, the China Academy of Information and Communications Technology (CAICT), a think tank under the Ministry of Industry and Information Technology (MIIT), published an artificial intelligence security white paper that outlined how Beijing aims to use AI to automate censorship, control public opinion, and improve public security. For China Digital Times, Lisbeth has excerpted and translated these sections below. Lisbeth can be reached at lisbeth@chinadigitaltimes.net."

READ FULL TRANSLATION: WHITE PAPER OUTLINES POTENTIAL USES OF AI

This Week's ChinAI Links

Chinese phrase of the Week:  比上不足比下有余 (bi3shang4bu4zu2 bi3xia4you4yu2) - no match to those above but better than those below, middling, passable. In context of the article, used to characterize the monthly salary of a data annotator.

Cool stuff from Allan Dafoe and Jade Leung at GovAI on AI and the future of humanity in this Oxford Futuremakers podcast.

Paul Scharre and Michael Horowitz present an excellent roadmap for how a new National Security Commission can help U.S. maintain its global leadership in AI.

A new white paper from MIT Tech Review Insights on Asia’s AI agenda.

Great article by Paul Triolo and Graham Webster on China’s efforts to build the semiconductors at AI’s core, with an overview of China’s AI-optimized semiconductor efforts to-date.

Thank you for reading and engaging.

Shout out to everyone who is commenting on the translations - idea is to build up a community of people interested in this stuff. You can contact me at jeffrey.ding@magd.ox.ac.uk or on Twitter at @jjding99

New MacroPolo ChinAI Interactive

Welcome to the ChinAI Newsletter!

Hey ChinAI subscribers, after 40 issues with no promotions, ads, subscription fees, please excuse my inbox intrusion to plug MacroPolo’s new, must-view interactive, which looks at the building blocks of China’s AI ecosystem. It was a blast working with Matt, Joy, Annie, Chris, and the MacroPolo team on this, and we think it’s a nifty balance of engaging/fundamental explanations along with in-depth/hard-hitting research. I hope you’ll check it out and share it with both your friends and your frenemies, your lovers and your haters alike.

Back with our regular programming on Monday.

ChinAI #40: NeurIPS 18 - Taking Stock of Chinese AI Labs

Welcome to the ChinAI Newsletter!

These are Jeff Ding's weekly translations of writings on AI policy and strategy from Chinese thinkers. I'll also include general links to all things at the intersection of China and AI. Please share the subscription link if you think this stuff is cool. Here's an archive of all past issues. *Subscribers are welcome to share excerpts from these translations as long as my original translation is cited.

I'm a grad student at the University of Oxford where I'm the China lead for the Governance of AI Program, Future of Humanity Institute.

NeurIPS Metrics with Shanghai Jiaotong’s Acemap Tool

We looked at a lot of universities last week; let’s get back into the industry labs this week, with two translations featuring NeurIPS, which took place last week in Montreal. First one features a nifty tool by the Acemap team of Shanghai Jiaotong University, which has done some really cool scientometrics on NeurIPS papers from this year and throughout history. The big takeaways:

  • At this year’s conference, almost all of the top 10 institutions in terms of papers published are American, showing the absolute leading position of the United States in this field

  • Among Chinese institutions, Tsinghua University, Chinese Academy of Sciences, and Peking University publish the most papers in NeurIPS.

  • Interestingly the Acemap piece highlights (ethnic) Chinese scholars among the top 10 publishing authors, which includes some who work at American institutions, such as Eric Poe Xing, who is a professor at CMU.

  • Other things you can play around with in the Acemap official site: author relationship diagrams, evolution in popular NeurIPS paper topics, and useful short summaries of 1010 papers.

READ FULL TRANSLATION: NEURIPS METRICS WITH SHANGHAI JIAOTONG’S ACEMAP TOOL

Roundup of Chinese AI Labs by AI Impact Factors

In Issue #31 of ChinAI we introduced Leiphone’s AI Impact Factors, a database that takes stop of Chinese AI research institutes along four lines: conference/journal papers, competitions, development projects, and corporate activities (e.g. personnel changes). Let’s check back in with the November summary of the AI Impact Factors - a few highlights:

  • Baidu took the top spot in the monthly AI Impact Factors for the first time, with victories by its NLP team in an AI prosthetics challenge at NeurIPS 2018, and the announcement of the Baidu Research Institute Advisory Board

  • Starting to notice a lot of competitions/events hosted in China and they pop up in this translation (China National Computer Congress, China Collegiate Programming Contest)

  • Other notable happenings: Tencent AI’s Transmart (AI-assisted translation product), Alibaba’s open source framework, “X-Deep Learning,” for big data marketing, and many more.

READ FULL TRANSLATION: NOVEMBER REVIEW OF AI IMPACT FACTORS

This Week's ChinAI Links

Chinese phrase of the Week:  一波三折 (yi1bo1 san1zhe2): full of twists and turns, used in first translation’s recounting of NeurIPS/NIPS name change

Connie Chan’s must-read piece on AI becoming the product itself rather than just the tool, features TikTok, dating app Soul, and LingoChamp. Get ready for a flood of TikTok coverage after high-profile celebrity endorsements - just remember we covered its rise 4 months ago with a translation of Li Guofei’s comparison of Bytedance (maker of TikTok) and Tencent.

Lawfare’s Sinotech section is doing some good stuff.

Jason Si (Si Xiao), head of Tencent Research Institute, on an ethical framework for AI, based on ARCC (Available, Reliable, Comprehensible, and Controllable) — Mandarin section first, English translation midway through article

Good piece by Dr. Yujia He on AI & global governance, developing resilient economies in the age of AI.

Thank you for reading and engaging.

Shout out to everyone who is commenting on the translations - idea is to build up a community of people interested in this stuff. You can contact me at jeffrey.ding@magd.ox.ac.uk or on Twitter at @jjding99

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