The technological, cultural mindset of China is very different from the American mindset. That's an easy first sentence, for China has a history that spans to the 4000BC, and with it, a culture of Confucianism, Taoism, and, therefore, different styles of living and thinking. Then the last 100 years happened, Japan attacked China in WWII, then many internal conflicts also arose. Thus, in the 1990s, China was on the catchup for everything in the economic sphere, but all that has changed in the last 20 years. From what I've followed on the internet where the American mindset has a heavy bias against China, to the personal trip I took to China, I've noticed that if the United States ignore China as a worthy colleague or opponent in terms of technological progress, then China's sleeping dragon will soon dominate all things technology.
This book gives a reason as to why that is, why is China growing so fast? How do their culture allow for such growth? Why is the "copy cat" method of technology copying working? How are they using Copy Cat technology as a method of growth rather than copy? All of those questions are elucidated in the first section of Lee's book. In the later sections of this book, the assumptions made by Lee of the general AI future is are reasonable; nevertheless, there are many other people in the industry with more critical analysis of general AI. However, as I said, his analysis of China is magnificent.
I would heavily recommend this book for anyone who is in finance, technology or has an interest in Chinese culture. This book is meant for the understanding of how China operates, and not for how general AI research would operate in the future.
“They were on roughly parallel tracks, and the United States was slightly ahead of China. But around 2013, China’s internet took a right turn. Rather than following in the footsteps or outright copying of American companies, Chinese entrepreneurs began developing products and services with simply no analog in Silicon Valley. Analysts describing China used to invoke simple Silicon Valley–based analogies when describing Chinese companies—“the Facebook of China,” “the Twitter of China”—but in the last few years, in many cases these labels stopped making sense. The Chinese internet had morphed into an alternate universe.”
* Chinese urbanites began paying for real-world purchases with bar codes on their phones, part of a mobile payments revolution unseen anywhere else. Armies of food deliverymen and on-demand masseuses riding electric scooters clogged the streets of Chinese cities. They represented a tidal wave of online-to-offline (O2O) startups that brought the convenience of e-commerce to bear on real-world services like restaurant food or manicures. Soon after that came the millions of brightly colored shared bikes that users could pick up or lock up anywhere just by scanning a bar code with their phones.
Tying all these services together was the rise of China’s super-app, WeChat, a kind of digital Swiss Army knife for modern life. WeChat users began sending text and voice messages to friends, paying for groceries, booking doctors’ appointments, filing taxes, unlocking shared bikes, and buying plane tickets, all without ever leaving the app. WeChat became the universal social app, one in which different types of group chats—formed with coworkers and friends or around interests—were used to negotiate business deals, organize birthday parties, or discuss modern art. It brought together a grab-bag of essential functions that are scattered across a dozen apps in the United States and elsewhere.
* “As a result, American companies, citizens, and politicians have forgotten what it feels like to be on the receiving end of these exchanges, a process that often feels akin to “technological colonization.” China does not intend to use its advantage in the AI era as a platform for such colonization, but AI-induced disruptions to the political and economic order will lead to a major shift in how all countries experience the phenomenon of digital globalization.”
* Copying ideas or product features is frowned upon as a betrayal of the zeitgeist and an act that is beneath the moral code of a true entrepreneur. It’s all about “pure” innovation, creating a totally original product that generates what Steve Jobs called a “dent in the universe.”
* Startups that grow up in this kind of environment tend to be mission-driven. They start with a novel idea or idealistic goal, and they build a company around that. Company mission statements are clean and lofty, detached from earthly concerns or financial motivations.
* In stark contrast, China’s startup culture is the yin to Silicon Valley’s yang: instead of being mission-driven, Chinese companies are first and foremost market-driven. Their ultimate goal is to make money, and they’re willing to create any product, adopt any model, or go into any business that will accomplish that objective. That mentality leads to incredible flexibility in business models and execution, a perfect distillation of the “lean startup” model often praised in Silicon Valley. It doesn’t matter where an idea came from or who came up with it. All that matters is whether you can execute it to make a financial profit. The core motivation for China’s market-driven entrepreneurs is not fame, glory, or changing the world. Those things are all nice side benefits, but the grand prize is getting rich, and it doesn’t matter how you get there.
* Jarring as that mercenary attitude is to many Americans, the Chinese approach has deep historical and cultural roots. Rote memorization formed the core of Chinese education for millennia.
* “For years, the copycat products that emerged from China’s cultural stew were widely mocked by the Silicon Valley elite. They were derided as cheap knockoffs, embarrassments to their creators and unworthy of the attention of true innovators. But those outsiders missed what was brewing beneath the surface. The most valuable product to come out of China’s copycat era wasn’t a product at all: it was the entrepreneurs themselves.”
* Combine these three currents—a cultural acceptance of copying, a scarcity mentality, and the willingness to dive into any promising new industry—and you have the psychological foundations of China’s internet ecosystem.
* “That first act of copying didn’t turn into an anti-innovation mentality that its creator could never shake. It was a necessary steppingstone on the way to more original and locally tailored technology products.”
* “Early Chinese tech entrepreneurs looking for mentors or model companies within their own country simply couldn’t find them. So instead they looked abroad and copied them as best they could.”
* “It was a crude process to be sure, and sometimes an embarrassing one. But it taught these copycats the basics of user interface design, website architecture, and back-end software development.”
* “They learned what worked and what didn’t with Chinese users. They began to iterate, improve, and localize the product to better serve their customers.”
* “That strikingly fundamental difference in user attitudes should have led to a number of product modifications for Chinese users. On Google’s global search platform, when users clicked on a search result’s link, it would navigate them away from the search results page. That meant we were forcing Chinese “shoppers” to pick one item for purchase and then, in effect, kicking them out of the mall. Baidu, by contrast, opened a new browser window for the user for each link clicked. That let users try on various search results without having to “leave the mall.””
* I’ve found Silicon Valley’s approach to China to be a far more important reason for their failure. American companies treat China like just any other market to check off their global list. They don’t invest the resources, have the patience, or give their Chinese teams the flexibility needed to compete with China’s world-class entrepreneurs. They see the primary job in China as marketing their existing products to Chinese users. In reality, they need to put in real work tailoring their products for Chinese users or building new products from the ground up to meet market demands. Resistance to localization slows down product iteration and makes local teams feel like cogs in a clunky machine.
* Weibo, a micro-blogging platform initially inspired by Twitter, was far faster to expand multimedia functionality and is now worth more than the American company. Didi, the ride-hailing company that duked it out with Uber, dramatically expanded its product offerings and gives more rides each day in China than Uber does across the entire world. Toutiao, a Chinese news platform often likened to BuzzFeed, uses advanced machine-learning algorithms to tailor its content for each user, boosting its valuation many multiples above the American website.
* Underneath this transformation lay several key building blocks: mobile-first internet users, WeChat’s role as the national super-app, and mobile payments that transformed every smartphone into a digital wallet. Once those pieces were in place, Chinese startups set off an explosion of indigenous innovation. They pioneered online-to-offline services that stitched the internet deep into the fabric of the Chinese economy. They turned Chinese cities into the first cashless environments since the days of the barter economy. And they revolutionized urban transportation with intelligent bike-sharing applications that created the world’s largest internet-of-things network.
* They aspire to the mythology satirized in the HBO series Silicon Valley, that of a skeleton crew of hackers building a billion-dollar business without ever leaving their San Francisco loft. Chinese companies don’t have this kind of luxury. Surrounded by competitors ready to reverse-engineer their digital products, they must use their scale, spending, and efficiency at the grunt work as a differentiating factor. They burn cash like crazy and rely on armies of low-wage delivery workers to make their business models work.
* Silicon Valley juggernauts are amassing data from your activity on their platforms, but that data concentrates heavily in your online behavior, such as searches made, photos uploaded, YouTube videos watched, and posts “liked.” Chinese companies are instead gathering data from the real world: the what, when, and where of physical purchases, meals, makeovers, and transportation. Deep learning can only optimize what it can “see” by way of data, and China’s physically grounded technology ecosystem gives these algorithms many more eyes into the content of our daily lives. As AI begins to “electrify” new industries, China’s embrace of the messy details of the real world will give it an edge on Silicon Valley.
* By the end of 2017, 65 percent of China’s over 753 million smartphone users had enabled mobile payments.
* Given the extremely low barriers to entry, those payment systems soon trickled down into China’s vast informal economy. Migrant workers selling street food simply let customers scan and send over payments while the owner fried the noodles. It got to the point where beggars on the streets of Chinese cities began hanging pieces of paper around their necks with printouts of two QR codes, one for Alipay and one for WeChat. Cash has disappeared so quickly from Chinese cities that it even “disrupted” crime.
* “Analysts dubbed the explosion of real-world internet services that blossomed across Chinese cities the “O2O Revolution,” short for “online-to-offline.” The terminology can be confusing but the concept is simple: turn online actions into offline services.” -- The O2O revolution was about bringing that same e-commerce convenience to the purchase of real-world services, things that can’t be put in a cardboard box and shipped across country, like hot food, a ride to the bar, or a new haircut. -- Silicon Valley gave birth to one of the first transformational O2O models: ride-sharing. -- After a day spent commuting on crammed subways and navigating eight-lane intersections, many middle-class Chinese just want to be spared another trip outdoors to get a meal or run an errand. Lucky for them, these cities are also home to large pools of migrant laborers who would gladly bring that service to their door for a small fee. It’s an environment built for O2O.
* From there the O2O models became even more creative. Some hair stylists and manicurists gave up their storefronts entirely, exclusively booking through apps and making house calls.
* “Chinese parents could hire van drivers to pick up their children from school, confirming their ID and arrival home through apps. Those who didn’t want to have children could use another app for around-the-clock condom delivery.”
* “WeChat Wallet linked up with top O2O startups so that WeChat users could hail a taxi, order a meal, book a hotel, manage a phone bill, and buy a flight to the United States, all without ever leaving the app.”
* “In effect, WeChat has taken on the functionality of Facebook, iMessage, Uber, Expedia, eVite, Instagram, Skype, PayPal, Grubhub, Amazon, LimeBike, WebMD, and many more. It isn’t a perfect substitute for any one of those apps, but it can perform most of the core functions of each, with frictionless mobile payments already built in.”
* !!To Chinese startups, the deeper they get into the nitty-gritty—and often very expensive—details, the harder it will be for a copycat competitor to mimic the business model and undercut them on price. Going heavy means building walls around your business, insulating yourself from the economic bloodshed of China’s gladiator wars. These companies win both by outsmarting their opponents and by outworking, outhustling, and outspending them on the street.
* “That willingness to go heavy—to spend the money, manage the workforce, do the legwork, and build economies of scale—has reshaped the relationship between the digital and real-world economies. China’s internet is penetrating far deeper into the economic lives of ordinary people, and it is affecting both consumption trends and labor markets. In a 2016 study by McKinsey and Company, 65 percent of Chinese O2O users said that the apps led them to spend more money on dining. In the categories of travel and transportation, 77 percent and 42 percent of users, respectively, reported increasing their spending.”
* By enrolling the vendors, processing the orders, delivering the food, and taking in the payments, China’s O2O champions began amassing a wealth of real-world data on the consumption patterns and personal habits of their users. Going heavy gave these companies a data edge over their Silicon Valley peers, but it was mobile payments that would extend their reach even further into the real world and turn that data edge into a commanding lead.
* Subsidizing both the client sides (worker and the client side payer) -- A large portion of cars on the leading Chinese platforms were traditional taxis driven by older men—people who weren’t in a rush to give up good old cash. So Tencent offered subsidies to both the rider and the driver if they used WeChat Wallet to pay. The rider paid less and the driver received more, with Tencent making up the difference for both sides.
“Chinese students of AI are no longer straining in the dark to read outdated textbooks. They’re taking advantage of AI’s open research culture to absorb knowledge straight from the source and in real time. That means dissecting the latest online academic publications, debating the approaches of top AI scientists in WeChat groups, and streaming their lectures on smartphones.”
government Funding: Behind these efforts lies a core difference in American and Chinese political culture: while America’s combative political system aggressively punishes missteps or waste in funding technological upgrades, China’s techno-utilitarian approach rewards proactive investment and adoption. Neither system can claim objective moral superiority, and the United States’ long track record of both personal freedom and technological achievement is unparalleled in the modern era.
It’s a self-perpetuating cycle, one that runs on a peculiar alchemy of digital data, entrepreneurial grit, hard-earned expertise, and political will. To see where the two AI superpowers stand, we must first understand the source of that expertise.
* One study by Sinovation Ventures examined citations in the top one hundred AI journals and conferences from 2006 to 2015; it found that the percentage of papers by authors with Chinese names nearly doubled from 23.2 percent to 42.8 percent during that time. That total includes some authors with Chinese names who work abroad—for example, Chinese American researchers who haven’t adopted an anglicized name. But a survey of the authors’ research institutions found the great majority of them to be working in China.
* When Obama made plans for AI, there was no splash in the news pond, when China made similar announcements in 2018, it was a roaring success. This shows signs of political difference.
* Between 2017 and 2020, the Nanjing Economic and Technological Development Zone plans to put at least 3 billion RMB (around $450 million) into AI development. That money will go toward a dizzying array of AI subsidies and perks, including investments of up to 15 million RMB in local companies, grants of 1 million RMB per company to attract talent, rebates on research expenses of up to 5 million RMB, creation of an AI training institute, government contracts for facial recognition and autonomous robot technology, simplified procedures for registering a company, seed funding and office space for military veterans, free company shuttles, coveted spots at local schools for the children of company executives, and special apartments for employees of AI startups. And that is all in just one city.
* Contrast that with the political firestorm following big bets gone bad in the United States. After the 2008 financial crisis, President Obama’s stimulus program included plans for government loan guarantees on promising renewable energy projects. It was a program designed to stimulate a stagnant economy but also to facilitate a broader economic and environmental shift toward green energy.
* “For the past thirty years, Chinese leaders have practiced a kind of techno-utilitarianism, leveraging technological upgrades to maximize broader social good while accepting that there will be downsides for certain individuals or industries.”
* Difference between the self driving car ethical question - West: What should a self-driving car “optimize for” in situations where it is forced to choose which car to crash into? How should an autonomous vehicle’s algorithm weigh the life of its owner? Should your self-driving car sacrifice your own life to save the lives of three other people?|| China: Chinese political culture doesn’t carry the American expectation of reaching a moral consensus on each of the above questions. Promotion of a broader social good—the long-term payoff in lives saved—is a good enough reason to begin implementation, with outlier cases and legal intricacies to be dealt with in due time.
* internet AI, business AI, perception AI, and autonomous AI. Each of these waves harnesses AI’s power in a different way. 1, The first two waves—internet AI and business AI—They are tightening internet companies’ grip on our attention, replacing paralegals with algorithms, trading stocks, and diagnosing illnesses. Perception AI is now digitizing our physical world, learning to recognize our faces, understand our requests, and “see” the world around us. This wave promises to revolutionize how we experience and interact with our world, blurring the lines between the digital and physical worlds. Autonomous AI will come last but will have the deepest impact on our lives. As self-driving cars take to the streets, autonomous drones take to the skies, and intelligent robots take over factories, they will transform everything from organic farming to highway driving and fast food.
** Smart Finance’s deep-learning algorithms don’t just look to the obvious metrics, like how much money is in your WeChat Wallet. Instead, it derives predictive power from data points that would seem irrelevant to a human loan officer. For instance, it considers the speed at which you typed in your date of birth, how much battery power is left on your phone, and thousands of other parameters.
* “OMO: online-merge-offline. OMO is the next step in an evolution that already took us from pure e-commerce deliveries to O2O (online-to-offline) services. Each of those steps has built new bridges between the online world and our physical one, but OMO constitutes the full integration of the two. It brings the convenience of the online world offline and the rich sensory reality of the offline world online. Over the coming years, perception AI will turn shopping malls, grocery stores, city streets, and our homes into OMO environments.”
* The Confucian virtues is why Chinese is okay with follow culture: That type of data collection may rub many Americans the wrong way. They don’t want Big Brother or corporate America to know too much about what they’re up to. But people in China are more accepting of having their faces, voices, and shopping choices captured and digitized. This is another example of the broader Chinese willingness to trade some degree of privacy for convenience. That surveillance filters up from individual users to entire urban environments.
Shenzeng: * entire supply chain available for prototyping is in Shenzhen: At the city’s dizzying electronics markets, they can choose from thousands of different variations of circuit boards, sensors, microphones, and miniature cameras. Once a prototype is assembled, the builders can go door to door at hundreds of factories to find one capable of producing their product in small batches or at large scale. That geographic density of parts suppliers and product manufacturers accelerates the innovation process. Hardware entrepreneurs say that a week spent working in Shenzhen is equivalent to a month in the United States.
* Xiaomi's smart appliance influence: It’s a constellation of price, diversity, and capability that has created the world’s largest network of intelligent home devices: 85 million by the end of 2017, far ahead of any comparable U.S. networks.
* the AI behind it. : Key to that incremental deployment will be the construction of new infrastructure specifically made to accommodate autonomous vehicles. In the United States, in contrast, we build self-driving cars to adapt to our existing roads because we assume the roads can’t change. In China, there’s a sense that everything can change—including current roads. Indeed, local officials are already modifying existing highways, reorganizing freight patterns, and building cities that will be tailor-made for driverless cars
* At this point, we just don’t yet know where that bottleneck will be, and fourth-wave AI remains anyone’s game. While today the United States enjoys a commanding lead (90–10), in five years’ time I give the United States and China even odds of leading the world in self-driving cars, with China having the edge in hardware-intensive applications such as autonomous drones. In the table below, I summarize my assessment of U.S. and Chinese capabilities across all four waves of AI, both in the present day and with my best estimate for how that balance will have evolved five years in the future.