Two years ago, the morning view from my office in northern Beijing was a snaking traffic jam of cars. Today I look down to see a rush of orange and yellow bicycles, as commuters have leapt onto the “smart” bicycles that are reshaping rush hour in China’s busiest cities. In less than a year Mobike (in which my venture fund invested) has reached 25m rides per day. That illustrates another force that will be vastly more transformative in 2018: the boundaries between the online and offline worlds are being erased.
These bikes are not the rusty clunkers you may have seen in old black-and-white photos of China’s capital. They are equipped with solar-powered GPS, accelerator, Bluetooth and a thermos detector. Both NFC (near-field communications) and microphones are activated by smartphone. To sign up to ride, you make a digital payment from your phone, and the bike’s smart lock automatically opens.
As you cycle around the city, the various sensors transmit your moving co-ordinates and other data to a cloud-based server. Each day, millions of cyclists peddling around Chinese megacities generate 20 terabytes of data, which feed back into Mobike’s cloud servers—connecting people, bikes, roads and destinations as one of the world’s largest “internet of things” networks. Mobike’s servers use artificial intelligence (AI) to analyse traffic patterns and to balance supply and demand, maximising usage and alerting the company to any problems.
I call this futuristic but imminent world “OMO” (online merges with offline). Four factors are enabling the arrival of omo: rapid smartphone uptake, frictionless payment systems, cheaper and better sensors, and advances in AI. In each of these areas, China is moving extraordinarily fast, and is poised to see the OMO future first.
China now has 731m people wielding smartphones, all equipped with GPS and other sensors. Some 70% of them use their phones for digital payments, in lieu of credit card or cash. This frictionless digital payment is nearly instantaneous, usually zero-fee, requires no minimum purchase and can be used person-to-person (not only person-to-business, like credit cards).
In the past three years this new way of buying things has taken the Chinese economy by storm. Easy digital payment systems have paved the way for not just Mobike, but also Didi (the Uber of China), Meituan (delivering over 10m take-out meals per day) and many other new companies. Many of these are now also expanding internationally.
In the year ahead, more sensors will be added to more tools of daily life, all generating more data. “Facts”, such as a person’s location, movements and even identity, are beginning to be captured by these sensors and transmitted online. The information will be combined with online data and analysed by AI, transforming the future of many industries.
“Autonomous stores”, such as the F5 Future Store (in which my fund also invested) with headquarters in Guangzhou, are developing another blueprint for OMO. F5 sells popular items common in regular convenience stores, including hot meals. Like Amazon Go, F5 is fully autonomous (done by machine), from meal preparation to check-out. But in a step ahead of Amazon Go, F5 is scalable and profitable. In the future, these stores will be equipped with sensors that can discern a customer’s identity, movements, behaviour and even intent, as seamlessly as if someone were clicking around an e-commerce website.
A final example is in education. Language learning, which is extremely popular in China, will combine native-speaking teachers lecturing remotely, local assistants keeping the atmosphere fun, autonomous software correcting pronunciation and autonomous hardware grading homework and tests. Our investments in VIPKID, Boxfish and Septnet have already built capabilities into schools and training centres in China.
Brave new world
Once there are more sensors in cars, stores, malls, clinics and schools, those with access to the data will know and track each person’s behaviour even better than when that person is online. It will be possible to know what product someone picked up and bought, or put back on a store shelf; whether they are running a fever or just tripped on a stairwell; and where they went and, by inference, what they probably did (eg, a lunch meeting, a hospital visit, returned home). As a next step, offline and online data can be combined, providing accurate customer recommendations, improving in-store services, automating the supply chain and achieving just-in-time inventory management.
OMO and AI will take us into a future where any distinction between these worlds disappears. We will reap great financial benefits, and enjoy unprecedented convenience, but we also need to find ways to protect people’s privacy and safety in this brave new world.
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