The biggest AI trends in China, according to Kai-Fu Lee

Photo Credit: SheilaShang/Wikimedia Commons

I wrote about my first few lessons previously on Kai-Fu Lee’s new book AI Superpowers and his presentation of it at an Amcham event in Beijing. Here, I’m going to go through another five.

AI is a competition between batteries and grids

During his presentation, Lee mentioned some interesting things on how AI companies are competing. According to him, the big AI giants (Google, Amazon, Facebook, Alibaba, Tencent, and Baidu) are mostly focusing on creating “AI grids.”

These will be similar to electricity grids in that everyone will get access to general and likely commoditized AI capabilities. Machine learning will be a standardized service that any company can purchase, for example. “These platforms—Google Alibaba, and Amazon—act as the utility companies, managing the grid and collecting the fees,” he said.

However, startups are focused on creating “AI batteries.” According to him, “Instead of waiting for this grid to take shape, startups are building highly specific ‘battery-powered’ AI products for each use case.” These companies are focused on depth and specialization—think medical diagnosis, mortgage lending, and autonomous drones.

This raises an important question: Will AI become a winner-take-all competition?

Optimizations and data network effects are going to get more complicated

In software and platform businesses, people like to talk about data network effects. The idea of this is simple: better products get you more users, more users mean more data, and more data means better products. It’s a virtuous cycle.

Thus far, data network effects have mostly been about recommendations and curation. The more videos you watch, the more data Netflix and Youku have on you, and the better they can give you recommendations for videos. Amazon and Alibaba do the same with recommended products in ecommerce. There is real power in this.

However, AI-centric companies like Toutiao are taking such data network effects beyond just recommendations and curation. Toutiao is a news aggregator where AI can also create and police content. The AI is the curator but it can also be the reporter and editor, which means we may soon have AI that writes articles based on what it thinks you want to read. This results in more complicated data network effects.

Another fascinating aspect of this is that AI systems can increasingly make correlations between “weak features.” While humans can see correlations between “strong features” like “people buy more umbrellas when it rains,” AI can see other correlations like “when it rains, people buy more beer.” (I made that one up, but I think it’s true.)

AI increasingly sees performance enhancements and optimizations based on factors that humans cannot see or understand.

Online-merge-offline (OMO) is next

The online-to-offline (O2O) market is pretty great in China. If you live in a Chinese city, you can order food, rent a bike, schedule a masseuse, and pay for anything—all on your phone.

But Lee says this is just the beginning, and online-merge-offline (OMO) is next. This is when the online and physical worlds really combine.

Lee gives an example:

Government support can accelerate AI in China

Some useful slides