Following my review of Radical Candor, another summer’s reading I wanted to share with you is AI Super-Powers: China, the Silicon Valley and the New World Order. The author, ex-Microsoft, ex-Apple, was also the president of Google China until 2009. To say that he has a fair grasp of both the US and Chinese digital markets, would be an embarrassing understatement.
AlphaGo, the Sputnik moment
The author discusses first the seismic Sputnik moment for the Chinese government, of Google’s AlphaGo beating Ke JIE (柯洁), the nineteen-year-old Chinese Go world master. We then have a broader perspective on how the cultural gap between the US and China expanded more and more when eBay and Google tried to take foot in the country and reign in the market around them. In that regard, the discussion on how Jack MA (马云) waged war and circumvented eBay by innovating the local internet business models was especially illuminating.
There is also a very critical — and if I dare to say ‘refreshing’– take on the Silicon Valley. For the author, China is a far more ruthless market for startups and it does drive the innovation ecosystem at unprecedented high-speeds:
American startups like to stick to what they know: building clean digital platforms that facilitate information exchanges. Those platforms can be used by vendors who do the legwork, but the tech companies stay distant and aloof from these logistical details. (…) Chinese companies don’t have this kind of luxury. Surrounded by competitors ready to reverse-engineer their digital products, they must use their scale, spending, and efficiency at the grunt work as a differentiating factor.
The Saudi Arabia of data
Add to this mix the leapfrog to mobile-everything, unlocked by powerful payment platforms nested in the digital bazaar where WeChat reigns supreme… All this combined led to an explosion of startups and tech businesses exploring every side of the Chinese market. From food delivery to shared bikes or IT services, no stones were left unturned if there was money to make. Which in turn, built-up (I quote) a Saudi Arabia of data, with very few regulations from the central government to hold the zeal of local entrepreneurs.
Soon enough the four building blocks for creating an AI superpower were plugged in: abundant data, tenacious entrepreneurs, a specific policy environment (or lack of policy), and well-trained AI scientists.
The “well-trained AI scientists” part being as we speak actively built through top-down incentives described in the July 2017, “New Generation Artificial Intelligence Development Plan” which outlines China’s goal of an AI industry worth $150 billion by 2030.
To quote Kai-Fu LEE again:
Silicon Valley’s edge in elite expertise isn’t all it’s cracked up to be. And in the crucial realm of government support, China’s techno-utilitarian political culture will pave the way for faster deployment of game-changing technologies. (…) real economic strength in the age of AI implementation won’t come just from a handful of elite scientists who push the boundaries of research. It will come from an army of well-trained engineers who team up with entrepreneurs to turn those discoveries into game-changing companies.
An (AI) chip on the shoulder
One grain of salt in this rosy picture of China as a soon-to-be consecrated AI superpower? Silicon chips.
Although the Chinese Ministry of Science and Technology is throwing a lot of sponsoring money at the problem and a throve of startups were onboarded, there is nothing much to show for it. And while Nvidia just bought back AMD to consolidate its huge pipeline of dedicated silicon, who’s heard of Horizon Robotics, Bitmain, or Cambricon Technologies yet?
But if you’re willing to consider the admittedly less complex market of electric cars manufacturing, and how it kicked in explosive growth within a few years, you could expect China local AI microchip manufacturers pretty soon.
The other half of the book discusses with a solid perspective the end of blind optimism about AI, the perspective of China on job loss (and creation), and what kind of dystopia we will be able to deal with depending on our cultural frame of reference. This part would be quite difficult to summarize here and in my opinion digressed a bit on topics that matter for readers that are US democrats and care about say universal income.
Should you read it?
All in all, I had not a lot of expectations in this book. Partly because, yes I’ve been working in China for some years and even though I’m not a specialist in AI, I understand quite a few things about the local business culture and their digital markets. But also because technical books branded as New York Times Bestsellers are often like reading Twilight if you’re into Romero’s movies.
But I must say that not only did I find it a very enjoyable read, I also learned quite a lot and had at the same time a very handy and insightful timeline on a fairly complex puzzle of moving pieces that lead to where China is (or will be soon): the #1 among AI super-powers.
Should you read it too? I’d say most definitively. Kai Fu LEE strikes a good balance between explaining business cultures, their history, and some key technical sides of AI. But what seems very interesting to me is that even if you don’t care about AI, understanding how the two super-powers are battling over tech supremacy will very much translate in your own market. Are you in hospitality, airline, car manufacturing, banking, or luxury? These markets will be disrupted along the same fracture lines as AI. Not so much because of AI technology per se (but yes, there’s that). It’s more than the race for AI to illustrate to an extreme how the US and China are dealing with scaling up new networked markets globally. So whatever your current market is, if it’s a global one it will be facing these super-powers that are thinking and acting in very distinct ways.
Could Europe be an AI super-power too?
At this point a last burning question might remain in your mind: But Philippe what about Europe then? And my answer would be: Yes, exactly.
The fact that Europe is pretty much invisible in this book shouldn’t be attributed to the author’s inevitable cultural bias. Europe is suffering from the same old venerable disease: top scientists disconnected from business. Whether it is by lack of education or simple cultural disdain, doesn’t matter so much at this point because the race for AI can only be fueled by data, and data is coming from business interactions in a networked economy.
If there’s only one practical thing that Europe should learn very fast is that China leapfrogged the US on AI, it’s not because they got better scientists. It’s largely because they went all-in with digital and mobile payments.
Data, data and data.