AI Wars: Will China Defeat The US?

This week’s plunge in Apple’s shares was another sign of the impact of the relations between the US and China. It does look like President Trump’s tariffs are taking a toll and that the tensions maybe lasting.

So this why Kai-Fu Lee’s book, AI Superpowers: China, Silicon Valley, and the New World Order, is so timely. He provides a detailed look at how China is poised to win one of the most important markets. Keep in mind that – according to a research report by PWC – AI is forecasted to add $15.7 trillion to global GDP by 2030. The main reason is that this technology is general purpose, having applications that span industries like healthcare, transportation, financial services, energy and so on. Some consider AI to be on par with what we saw with the revolution of electricity during the 20th century.

Lee certainly has the credentials to make convincing arguments. He got his Ph.D. in computer science from Carnegie Mellon University in 1988, where he focused on AI. Lee worked on leveraging concepts like Bayesian networks for games and voice recognition.

He would then move on to the corporate world. Some of the companies he worked for included Apple, Silicon Graphics, Microsoft and Google. As of now, he’s a venture capitalist with Sinovation Ventures, which is focused on AI opportunities in China.

The Book

Lee notes that China has AI fever, galvanized by heavy investments from the government and VCs.  Yet success is more than just about money.  Lee points out that there are four key factors for AI:  “abundant data, hungry entrepreneurs, AI scientists and an AI-friendly policy environment.”

In light of this, it’s actually easy to see why China is in a strong position to benefit.  After all, the ubiquity of smartphones has meant the accumulation of gigantic amounts of data. But China has also seen more usage of real-world applications, such as with bike-sharing, mobile payments and ride-hailing. Part of this has been due to massive private/public investments. But China’s willingness to be permissive with issues of privacy has been another big factor.
Data is essential for AI because it is required for developing sophisticated neural networks. This makes it possible to better understand language, recognize objects or come up with useful insights.

Once the data threshold is met, which seems to be the case with China (it is the largest producer in the world and the country has more than 700 million internet users), then there is less of a need for top-notch engineers. Lee writes: “Algorithms tuned by an average engineer can outperform those built by the world’s leading experts if the average engineer has access to far more data.”

What Now?

Now the US is not doomed to failure.  We still have many advantages. The university system is standout and there are mega companies that are pushing innovation (Google, Microsoft, Facebook, and Apple).

But much still needs to be done. According to Jason Tan, who is the co-founder and CEO of Sift Science (a company that uses AI to help online businesses prevent fraud and abuse in real time), he believes there needs to be the following:

  • Make much more investments in homegrown STEM talent.
  • Make it attractive for overseas STEM talent to remain in the US
  • Get more government support for entrepreneurship — creating workplace opportunities for that talent to be applied
  • Get more government support for AI research — so that we continue to push the frontier

No doubt, all these would make a difference.  But unfortunately, there has been little progress on these fronts.  So unless there is major change – and soon – Silicon Valley may no longer be the center of gravity in the next 10 years.

Leave a Comment