What is the main message of AI Superpowers?

The main message of AI Superpowers is the race between China and the US to dominate the AI industry.

How long does it take to read AI Superpowers?

The reading time for AI Superpowers depends on your reading speed. However, the Blinkist summary can be read in just 15 minutes.

Is AI Superpowers a good book? Is it worth reading?

AI Superpowers is a compelling read that explores the future of artificial intelligence. It provides valuable insights and raises important questions.

Who is the author of AI Superpowers?

AI Superpowers is authored by Kai-Fu Lee.

AI Superpowers Summary of Key Ideas and Review

Name: AI Superpowers
Rating: 4.3 (545 reviews)
Author: Kai-Fu Lee

Introduction

What’s in it for me? Find out where China and the US stand as we head into the new AI economy.

With driverless cars, firefighting drones and email programs that finish your sentences, there’s no escaping the fact that artificial intelligence (AI) is going to continue finding applications in our everyday lives. There’s also little debate around the fact that the US and China currently have the largest concentration of bright minds working to develop these applications.

China is so determined to become the world superpower in AI that they’re doing whatever it takes to pave the way for a booming AI industry. This includes heavily subsidizing the rent for AI-tech start-ups, and setting up one-stop-shops to make it easy to launch a new start-up. The Chinese government is even securing placements at competitive schools for the kids of start-up executives.

Is it enough to topple the giants of Silicon Valley? Author Kai-Fu Lee has spent years in both Silicon Valley and its Chinese equivalent, Zhongguancun. He believes China is in a great position beat Silicon Valley, reign supreme in the new AI-based economy and thereby change the world order.

In these blinks, you’ll find out

how the Chinese version of Groupon became one of the world’s biggest start-ups;
how WeChat became the world’s biggest super-app; and
how a cancer scare made the author rethink our relationship to AI.

Key idea 1 of 7

Thanks to a breakthrough in deep learning, we’re on the verge of an AI economy.

Until recently, if people were talking about artificial intelligence (AI), it was likely in the context of science-fiction. But these days, everyone from schoolkids to CEOs are wondering what kind of changes AI has in store for us in the coming years.

In fact, when the author gives talks at schools and executive conferences, he’s found that Chinese kindergarten students ask him the same questions as CEOs, such as, “Are we going to have AI teachers?” and “What kind of jobs are we going to have in the future?”

While the emergence of real-world AI can seem like a relatively new thing, it’s been brewing for decades and has only now started being a major business tool thanks to a breakthrough in deep learning.

The story of how we got to deep learning stretches back to the 1950s, when researchers like Marvin Minsky and John McCarthy had a goal of imbuing computers with human intelligence. And when the author started getting involved in this field in the early eighties, there were two camps working toward this: the rule-based people and the neural network folks.

Rule-based AI believed that the best results would come from programming machines with one rule at a time, such as “cats have triangular-shaped ears.” The neural network camp, on the other hand, preferred to let the machine learn on its own, much as humans do, through experience. This way, a machine can analyze a picture of a cat and respond incorrectly, but this error will become data that it learns from.

What neural network-based AI really needed was loads of data to analyze and faster computing power, which finally arrived in the mid-2000s. With the improved conditions, AI researcher Geoffrey Hinton was able to finally add the right amount of layers to the “neurons” and essentially multiply the AI processing power to a whole new level.

When this happened, neural network was rebranded to deep learning. The big breakthrough was made public at a 2012 contest when Hinton’s new AI algorithm blew away the competition at visual recognition.

Suddenly, AI was capable of processing complex problems, recognizing patterns and coming up with amazing results. It was clear that this technology was now applicable to a whole array of everyday functions, including visual and audio recognition, making complex financial decisions and even driving a car. Thanks to deep learning, an AI economy was on the way.

Key idea 2 of 7

Over the past few years, China has gone from copycat to top contender.

In China, artificial intelligence had what the author calls a “Sputnik moment” in 2016. It happened when the AI program known as AlphaGo beat the champion Go player, Lee Sedol in a three-game tournament.

These games had 280 million Chinese viewers glued to their TVs, and many were heartbroken when the visibly emotional Lee admitted defeat. But rather than breaking the people’s spirit, the people of China became inspired to harness the power of AI to their advantage – much like the launch of the Russian satellite, Sputnik, rallied Americans to be the first on the moon.

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Key idea 3 of 7

China’s unique online world makes it a goldmine for the kind of data that AI thrives on.

There are some fundamental differences between Silicon Valley’s and China’s start-ups, and a big one is having what’s known as a light or heavy touch.

When a business has a light touch, it does one thing and leaves a lot of the particulars surrounding that service for others to deal with. This is the style of Silicon Valley companies like Uber, which connects people with a ride, but doesn’t deal with gas and car maintenance.

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Key idea 4 of 7

China is poised to be the top superpower when it comes to internet AI, but not business AI.

The arrival of AI in our everyday lives is coming in four waves.

The first is internet AI, and it’s already here. YouTube recommends the next video for you to watch based on an AI algorithm, and services like the Toutiao app not only recommends articles, it automatically generates them as well.

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Key idea 5 of 7

China is ahead of the game in perception AI, but the US has an early lead in autonomous AI.

The third wave of AI is perception AI, which includes voice and facial recognition programs. China has an advantage here, due in part to cultural differences. Americans have many “Big Brother” fears about their image and voice being captured, while the Chinese are more agreeable to the idea of giving up some privacy in return for more convenience.

Perception AI has the potential to be an exciting area as it blurs the boundaries of online and offline. This is why this technology often falls under the category of online-merge-offline (OMO).

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Key idea 6 of 7

Experts are still debating whether AI will lead to a utopia or dystopia.

These days, when economists and researchers debate about what a world with an AI economy looks like, they tend to fall into two camps.

Famed geneticist and researcher, Ray Kurzweil, is in the utopia camp. He sees machines as being the supreme tool for humans to enhance our bodies and minds, allowing us to become smarter and live longer. Similarly, AI researcher Demis Hassabis sees AI as the tool that will allow us to finally cure disease and solve problems like global warming.

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Key idea 7 of 7

After a serious health scare, the author is hopeful that we can work in harmony with AI.

In 2013, the author was diagnosed with stage IV lymphoma. Up to this point, he was something of a workaholic, but that all changed. He realized that so much of the effort put into his career was meaningless now. Facing up to his own mortality, he now understood that being productive wasn’t what made him human – in fact, that was more like being a machine. What made him human was his relationships with his family, friends and those close to him.

Thanks to a course of chemotherapy, he’s currently in remission, but the experience changed how he envisioned AI and humans working in harmony.

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