10 Big Lessons in Chinese AI – From Kai-Fu Lee’s Book AI Superpowers (Pt 1 of 2)

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Kai-Fu Lee has released a new book titled AI Superpowers. It broadly compares artificial intelligence in China and the USA and it’s getting a lot of press. I was fortunate to hear him present part of his book at an Amcham event in Beijing.

The book doesn’t go into AI or business questions too deeply. It’s more personal and high-level. But peppered throughout are some fascinating details about how AI is evolving in China. So here are my 5 take-aways from AI Superpowers.

Lesson 1: China is well positioned for AI’s age of implementation

One of Dr. Lee’s main points is the below chart (from his Amcham talk). His point is that we are moving from an age of discovery to one of implementation in AI. And China is better positioned to win in implementation.

AI is no longer about elite cutting-edge AI researchers making big breakthroughs (which the USA is better at). It is more about taking existing discoveries and implementing them in companies and industries. He cites several key factors that matter in this implementation – such as having lots of AI engineers, a robust entrepreneurial culture and favorable government policies.

Lesson 2: China has an advantage in data – and that is what will matter most in AI.

Successful AI algorithms need three things: computing power, big data and an army of solid but not elite AI engineers. However, once you get to a sufficient volume of engineers and computing power, it is having more data that makes the difference. More data is how you win. And China has a wealth of data, especially on the consumer side.

It is really consumer and digital China (my area of study) that matters. The enterprise-side of digital China is not that developed and evolves slowly (try getting SOEs to digitize). But on the consumer side (Tencent, Alibaba, Didi, etc.) things happen very fast and there is tons of data.

China has already surpassed the US in quantity of data. But the quality of data is also superior. Chinese consumers are now paying for real world things with their phones. This includes food delivery, on-demand masseuses, bike riding, bus tickets, and just about everything else. Mobile payments are generating valuable data on what consumers buy and eat, where they are and how they commute. It is a sea of data about actions in the real world – which is a lot more valuable that online data such as likes, clicks and video watches.

Lesson 3: Scrappy entrepreneurs are China’s secret weapon in AI

I was happy to read his comments about China’s entrepreneurs. My mantra for many years has been that China’s defining factor is not its big markets. It is the ferocious competition and the battle-hardened companies it produces.

Dr. Lee repeatedly talks about China’s scrappy entrepreneurs and their “sharp instincts for building robust businesses.” He says Silicon Valley looks “downright sluggish compared to its competitor across the Pacific”.

He has an good summary of digital China – saying “survival in the internet coliseum required relentlessly iterating products, controlling costs, executing flawlessly, generating positive PR, raising money at exaggerated valuations, and seeking ways to build a robust business “moat” to keep the copycats out”. That is a pretty great summary.

Keep in mind, China’s digital giants (Alibaba, Tencent, Didi) are the champions of a ferocious market. They have beaten off tens if not hundreds of competitors. So when a company like Didi takes on Uber in Mexico and Brazil (happening no), I always bet on the Chinese company. And they aren’t just good at competing and coding. They are also good at navigating messy markets and responding to dirty tricks.

Lesson 4: AI-driven automation will impact economies based on cheap labor and manufacturing

This was more of a macro point. That AI-driven robots and other types of automation are going to impact countries like China, Vietnam and Indonesia. Basically, economies that have benefited from cheap labor and manufacturing. As robotics take over factories, manufacturing will become cheap everywhere. And it will be more about being close to urban centers and local markets. So putting a factory in Asia will make less and less sense for many companies.

Many Asian economies have risen based initially on such cheap-labor and manufacturing. South Korea, Japan, Singapore and China all started as exporting nations with this advantage. But China may be the last country to make it up that path.

Lesson 5: Meituan’s “war of a thousand Groupons” is a good example of digital China

Dr. Lee gives a good summary of how Meituan ended up winning in group buying and food delivery, in what he calls the “war of a thousand Groupons”.

In the first phase of this war, there was a venture capital funded battle that was about raising the most money and outlasting your opponents. Basically, there was a sea of copycat competitors and the strategy was to use raised capital to buy customers. Then whoever had the most market share could continue to raise the most money. It was also important to create stickiness with customers and manage the burn rate.

In the second phase, they rapidly expanded their lines of business and reshaped and deepened their core offering (especially by increasing in data and stickiness with customers). Meituan did well in the first “money war” phase and then was particularly fast at moving into lots of different businesses (hotel reservations, dining reservations, bike-sharing, etc.) in phase two.

This is a really common pattern in digital China. We just saw it in bike-sharing.

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Ok. That’s it for Part 1. In Part 2, I have my take-aways 6-10 from the book.

Cheers from California, Jeff

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I write and speak about the Chinese consumers and digital China.

 

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