Who are the key AI superpowers of the world?

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? In AI Superpowers, 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.

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.

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.

And just as John F. Kennedy declared US intentions to land on the moon, following the Go tournament, the Chinese government issued a rallying cry declaring their ambition to become the global leader of AI innovation within the next ten years. This is particularly remarkable since just a few years prior, China was known more for being a hub of copycat technology than for its innovation.

Indeed, in the early 2000s, China was copying every successful Silicon Valley product. This caused many in the West to write off China’s abilities as an innovative competitor. What the doubters failed to recognize though is that by being copycats, Chinese entrepreneurs were actually learning how to make their own world-class products.

The best example may be Wang Xing, who made copycat Friendster, Facebook, Twitter and Groupon sites. In doing so, Wang not only learned how to design seamless products, he became a battle-hardened competitor who knew how to thrive in the cutthroat Chinese market. So by the time he turned his attention to his group discount service Meituan, he was ready to outperform Groupon itself.

This time around, Wang didn’t copy the interface. He made it Chinese-friendly with densely-packed page designs. He also held back from overspending early on to woo customers and instead spent money for the long-term win by signing exclusive deals with vendors and creating a fast and reliable payment system.

Unlike Groupon, Wang didn’t try to coast on one idea, either. He expanded and offered new products based on whatever was popular at the time, including movies, food delivery and local tourism. So, by 2014, Groupon was on the decline, selling for less than half its IPO, while Meituan was becoming the fourth most valuable start-up in the world.

Check out my related post: Are we ready to trust Artificial Intelligence?

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