Another week and another worsening seven days of Sino-US relations, after Donald Trump triggered tariffs on $200 billion more Chinese goods and then accused China of trying to influence the US mid-term elections with the aim of damaging his administration.
Beijing hit back by branding Washington as an “economic bully” and China’s foreign minister also denied Trump’s claim of election interference, calling it “unwarranted”.
But as the Financial Times pointed out this week the backdrop to the trade row is an underlying dispute over tech leadership and intellectual property: the Americans blast the Chinese for stealing their technology, while China counters that Washington is running scared at the narrowing gap in tech know-how.
That said, Beijing has stepped back from championing the “Made in China 2025” plan, realising that the push to promote high-tech industry is a red rag to the Trump administration’s bull. And there was a similar effort to lighten the tone at the World Artificial Intelligence Conference in Shanghai this month, which attracted a stellar cast of Chinese tech tycoons. Front-and-centre was the ‘AI for Everyone’ theme, alongside a determined debate about how advances in the industry should be wins for all concerned.
Liu He, the senior China negotiator tasked with talking Trump down from his tariffs, even found the time to attend the gathering, glimpsing a “global village” of nations that should “embrace AI together”.
However, the debate inevitably moved back towards the struggle for ascendancy a few days later with the media blitz ahead of the launch of Lee Kai-fu’s new book: AI Superpowers: China, Silicon Valley and the New World Order.
Lee has both the smarts and the background to make credible predictions on AI, a gamechanging technology that some have likened in significance to the industrial revolution. Lee is the head of Sinovation Ventures – a Chinese tech incubator and private equity firm he founded – but was formerly president of Google China, and before that an executive at Microsoft and Apple.
That gives him a foot in both camps of what he describes as “the great AI duopoly”(the US and China) – though he warns in his book against the rhetoric of a winner-takes-all race in the artificial intelligence world.
The problem is that the trade row is hardly fostering a fraternal mood. Most of the media is talking more about who is going to win the AI crown and even Lee seems susceptible at times, with his recurring analysis of the strengths and weaknesses of the two dominant players.
AI is such a vast and varied subject that it can be daunting for technophobes. But Lee’s book is really helpful in framing the topic in digestible terms. One of its key contributions is the distinction that he draws between ideas and implementation: he puts the Americans ahead in the pure science or the raw thinking behind AI, but he positions the Chinese as the pacesetters in how the theory is being applied.
In particular, he points to the massive potential in China for Big Data, which drives ‘deep learning’ in the neural networks that recreate the human brain. The premise is that the bigger the dataset that can be fed into the algorithms, the better the algorithms can fine-tune their performance. Lee even says that algorithms devised by mid-tier engineers will outperform those from world class researchers if the data is abundant enough. “Having a monopoly on the best and the brightest just isn’t what it used to be,” he warns his American readers.
The book also looks at how data matters across three dimensions, and reviews how China and the United States compare in each.
In breadth – the numbers of people whose actions are captured in information – the two countries are evenly matched. China has more than a billion people using 4G devices but the best American tech firms have access to a similarly sized audience because they have more customers outside their home market.
Next is quality, or the way that the data has been captured. Here he says the Americans are ahead because their companies and public institutions are more disciplined in structuring how their data is gathered and stored.
The Chinese need to do more to accumulate information in a similar format, although this is starting to happen as companies grasp the importance of structuring their data in a standardised way.
Finally there is depth, or the range of different bits of data generated by each person. In this dimension the Chinese are leaders, largely thanks to the advent of the smartphone, plus the rise of apps like WeChat, which Lee describes rather niftily as “a kind of digital Swiss Army knife for modern life”.
AI companies in the US rely on more singular snapshots of information, and algorithms there are utilised in narrower areas like digital downloads – think of recommendations for a new series on Netflix or a new book on Amazon.
But social networks like WeChat have been a massive boon for Chinese AI practitioners because they open up a richer trove of information on what people are doing in their daily lives. This includes how they choose their news and entertainment, pay their bills or borrow money, order food and groceries, or book their transport or holidays.
Another useful feature in AI Superpowers is how it breaks the application of the science down into different waves, before identifying which of the two superpowers has the edge.
The first wave is ‘Internet AI’, or how content is personalised for people based on their online behaviour (i.e. suggestions of another golf video on YouTube or a novel based on an earlier purchase on Amazon). Lee reckons that Chinese and American firms are head-to-head in this front. But given the data advantages outlined above, China’s tech giants will take the lead within the next five years, he predicts.
The second wave is ‘Business AI’, in which companies take up the technology to improve their performance. Enterprises are deep diving into their own data in search of what Lee describes as “weak features” or weakly correlated variables that have a much bigger impact on business outcomes than previously understood. Banks are unleashing AI to find better ways to predict default rates, for example, while insurers are doing the same to maximise their returns on premiums.
Lee says that the Americans are well ahead in ‘Business AI’, because companies in China have done less to structure their data by investing in enterprise software or standardised storage. However, the Chinese have a chance to catch up because they are leapfrogging into new technologies that give them a clean slate in business design.
He gives the example of how the surge of mobile payments is triggering AI-powered apps that authorise millions of small loans by taking a digital fingerprint of a borrower’s phone. “It derives predictive power from data points that would seem irrelevant to a human loan officer,” he writes.
The third wave is described as ‘Perception AI’, or the merging of the digital world with the physical environments around us. We glimpse this in concepts like the ‘Internet of Things’ (IoT) and some of China’s initial advances in facial recognition (see WiC380) or unmanned retail outlets (see WiC410).
Progress here will pivot on skills in hardware, Lee believes, where companies like Midea, Xiaomi and Gree have an edge. Shenzhen, a crucible for companies that make ‘intelligent hardware’ –i.e. IoT-embedded tech products – will be at the forefront of China’s advance here. Leadership in manufacturing sensors will also be key.
Finally there is ‘Autonomous AI’, which Lee expects to have the biggest impact on society in the longer term. In its purest form, this is about giving machines the capacity to respond to the world around them. One example is the autonomous vehicles that will eventually navigate smart roads all on their own.
Lee puts America in a commanding lead in the technology behind ‘Autonomous AI’, especially in self-driving cars. But he says that policymakers in China will do their best to support local manufacturers, including the building of transport corridors that are tailor-made for autonomous vehicles.
Predicting a winner in an industry like this will come down to whether technology or policy turns out to be the biggest bottleneck, he says. Lee doesn’t deny that the government is playing a crucial role in creating space for homegrown heroes in AI, saying that Beijing is doing everything that it can to tip the scales in China’s favour.
Companies in Silicon Valley like to claim idealistic goals in their work but Lee says the mission in China is unapologetically mercenary. Changing the world is a lot less important than building a business worth billions. That sort of sentiment can spill over into the kind of copycatting that so enrages China’s Western rivals. But Lee argues that the gladiatorial ethos in China’s tech sector actually gives new ideas more impetus to flourish.
“In Silicon Valley, there is substantial stigma attached to imitating the business models or features of other companies. Doing so violates the ‘think different’ ethos associated with innovators like Steve Jobs,” he explained to the New York Times as part of his promotional tour last week. “The result is that pioneers often go unchallenged for long periods and are allowed to dominate the industry even though they don’t explore or exploit all the technology’s possibilities.”
On Monday he reappeared in the Washington Post to make the same point, even remarking that American tech companies “don’t compete very hard”. He explained: “When you build out a franchise such as Instagram, competitors say: ‘OK, I’m going to do something else. I don’t want to do what you do.’”
In this line of reasoning, China’s super-aggressive marketplace ignites a creative firestorm because it forces start-ups to push into new areas and take greater risks. “It is this combination of a competitive, fight-or-die mentality married to abundant capital and a gigantic networked consumer base that is fueling China’s ascent in commercial technology,” Lee reckons.
China’s dog-eat-dog dynamic doesn’t bode well for the “global village” imagined at this month’s AI conference in Shanghai. But Lee says there is a place too for more cooperative behaviour. He reckons there is a collaborative aspect to the science behind AI, and cites how ideas and implementation both have roles to play if the technology is to reach its full potential.
Yet there isn’t much doubt that national security officials in Washington have begun to see AI as more of a zero-sum game. And one likely outcome of a new ‘Cold War’ in the industry is that the two sides refuse to engage with each other, with both governments barring its rival’s companies from its home market.
Tech moguls take a similar view of the unfolding internet landscap, including Eric Schmidt, the former CEO of Google, who told an event in San Francisco last week that the two countries are taking diverging paths. “The most likely scenario now is not a splintering, but rather a bifurcation into a Chinese-led internet and a non-Chinese internet led by America” was his forecast.
Ultimately, Lee’s argument about how AI is developing takes him in a similar direction. Different business models and different customer habits are going to generate very different ecosystems, he believes. “It is therefore very difficult, if not impossible, for any American company to try to enter China’s market or vice versa. It’s like two different jigsaw puzzles. You can’t take a piece from one and try to fit it into the other – everything is different,” he told the Washington Post.
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