ChinAI #154: Breaking Down SenseTime's 672-page IPO Prospectus

Asia's Largest AI Software Company Files for IPO in Hong Kong

Greetings from a world where…

I think I could be satisfied eating ramen for every meal for the rest of my life

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Feature Translation: Sensetime’s IPO Prospectus

On August 27, SenseTime filed to go public on the Hong Kong exchange. The location itself is newsworthy as it also considered a a U.S. or mainland listing. This week, instead of translating a Chinese-language document, I’ll try to interpret Sensetime’s IPO prospectus, a lengthy financial document filled with fine print. This QbitAI article (in Mandarin) helped guide my reading of the document.

SenseTime is Asia’s largest AI software provider by revenue. It demonstrated consistent growth in the past four years of revenues (RMB): 1.8b in 2018; 3.0b in 2019; 3.4b in 2020; 1.6b in first half of 2021 (861m revenues in first half of 2020)

  • The “largest in Asia” claim is based on market research of 2020 figures by Frost & Sullivan, a firm commissioned by Sensetime to supply an industry report for the listing.

  • SenseTime is also the largest computer vision software provider in China, which boasts the second-largest AI software market, after the United States. China’s AI software market is forecasted to experience impressive growth: “The AI software market in China is expected to grow at a CAGR (compound annual growth rate) of 41.5% from RMB29.5 billion in 2020 to RMB167.1 billion in 2025, which would make it the fastest-growing among major markets globally. The contribution of AI software to the China software market is projected to rise from 9.0% in 2020 to 24.1% in 2025 (p. 122),” report Frost & Sullivan, though much depends on their definition of “AI software.”

All about the R&D

  • SenseTime’s R&D expenditures have increased each year since 2018, and the total R&D expenses exceeded revenues during the first half of 2021: 1.77b

  • Per Frost & Sullivan’s industry report, in the 2015-2021 period, SenseTime published the most papers in CVPR, ICCV and ECCV — the top three computer vision conferences.

  • They plan to allocate 60% of financing raised form this IPO to R&D investment. Interestingly, 1/3 of that planned R&D spending will be for supercomputing centers and AI chips.

What could hold SenseTime back?

  • Negative effects of covid: hampered international growth and delayed deployment of some smart city operations as city managers prioritized counter-pandemic efforts. They claim that the pandemic will, in the long run, “accelerate the digital transformation of enterprises and city management, indicating more opportunities for the AI industry, especially under China’s new national policy of ‘New Infrastructure’ (p. 350).”

  • Overly concentrated customer base: in first half of 2021, largest customer accounted for 23% of revenues, and five largest customers accounted for 59%. This mirrors a trend from IPO listings by other Chinese computer vision startups (ChinAI #147). Yitu, one of the big four CV startups, reported that their largest five customers also accounted for 60% of sales in first half of 2020. The largest customer of DeepGlint, a second-tier CV startup, accounted for about 1/3 of their revenues. I think this is an important indicator for the broader trajectory of AI as a general-purpose technology. At some point, shouldn’t we start seeing a more dispersed customer base as the technology diffuses across a wide range of industries?

  • Entity List: Interestingly, the document argues that the Entity List doesn’t apply to SenseTime entities that are legally distinct from Beijing SenseTime (its subsidiary, which was named in the Entity List addition). Still, it has put in place export control compliance measures for the entire company. It claims “the Entity List Addition has not had any material adverse impact on our business (p. 274).” The document never mentions SenseTime’s engagement with ethnic profiling in China’s Xinjiang region — the underlying justification for its blacklisting.

AI ethics portion of the prospectus was underwhelming:

  • They don’t tell us who’s on their AI Ethics Council, which leads its responsible AI initiatives. All we get is that it “comprises six members, including two external advisors, who are academic experts in the field of AI ethics, and four senior management members. (p. 259)” Why not name the members? We can only speculate, but it’s hard not to see parallels with Megvii’s initial prospectus document for its (withdrawn) Hong Kong listing. In that filing, Megvii also touted its 6-member AI ethics committee, naming Emmanual Lagarrigue, Schneider Electric’s Chief Innovation Officer, as an external advisor. What happened? When IPVM followed up with Emmanuel Lagarrigue, he said he was approached to join but ultimately declined the invitation before the committee was ever assembled.

  • They list 5 main achievements as evidence of “high standards on data security, privacy, and ethics for sustainable AI (p. 199)”: The only one of substance, in my opinion, is the ISO/IEC certifications for various privacy and information security practices. Two others mention their standardization work in areas unrelated to AI ethics. Another achievement is their “Code of Ethics for AI Sustainable Development” which was recognized by the UN — it’s 12 pages of boilerplate, half of which are taken up by stock images. The last one is about AI textbooks to promote education.

  • To be fair, there’s some promising stuff here: collaboration with Shanghai Jiao Tong University on a joint research center that studies algorithmic bias, chairing standards working groups on AI ethics and AI risk assessment, etc. What’s most glaring is what’s missing: i.e., any discussion of the use of facial recognition for ethnic profiling, which has been used to surveil Uyghurs nationally.

Lastly, a few notable numbers on compute:

  • SenseTime’s growth in total computing capacity: 0.3 exaFLOPS, 0.7 exaFLOPS, 0.8 exaFLOPS and 1.2 exaFLOPS as of December 31, 2018, 2019 and 2020 and June 30, 2021, respectively.

  • They are building a large-scale AI computing and empowerment data center in Shanghai, which is expected to launch in early 2022 and quadruple their total computing capacity.

ChinAI Links (Four to Forward)

Should-read: A dog’s inner life — what a robot pet taught me about consciousness

In The Guardian longread, Meghan O’Gieblyn examines eternal questions about consciousness as she trains her Aibo robot dog:

Despite these differences between minds and computers, we insist on seeing our image in these machines. When we ask today “What is a human like?”, the most common answer is “like a computer”. A few years ago the psychologist Robert Epstein challenged researchers at one of the world’s most prestigious research institutes to try to account for human behaviour without resorting to computational metaphors. They could not do it. The metaphor has become so pervasive, Epstein points out, that “there is virtually no form of discourse about intelligent human behaviour that proceeds without employing this metaphor, just as no form of discourse about intelligent human behaviour could proceed in certain eras and cultures without reference to a spirit or deity”.

Should-read: Semiinsights [半导体行业观察] (in Mandarin)

I know a lot of readers are interested in the semiconductor industry, so flagging this platform, which covers the global trends in semiconductors. Might circle back to semiinsights for future translations, as a scan of articles published in just the past month reveals a lot of quality analysis, including this article on the worsening of China’s chip talent shortage.

Should-read: Chinese-Russian Collaboration in AI

In a CSET issue brief, Margarita Konaev et al. evaluate China-Russia collaboration in AI. Their central finding:

“There has been a steady increase in AI-related research collaboration between the two nations and an even steeper rise since 2016. This upward trend mirrors the global expansion of AI research, propelled by increased computing power and the availability of large datasets. The overall number of joint Chinese-Russian AI-related publications, however, remains relatively low—whether as a share of each country’s scholarly output or compared with the number of papers researchers from China and Russia co-authored with researchers from the United States over the same period of time. The AI-related investment data tell a similar story—an upward trend in Chinese-Russian investment deals over the past five years, but the overall value remains relatively low.”

Should-listen: China’s Great Science Leap

Produced by Melanie Brown for BBC Radio 4, this two-part program examines China’s growing scientific prowess in bio-engineering, computing and space. I had a chance to contribute to the first episode in the series.

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.

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