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China’s Perfect Storm AI Moment

Robin Raskin, Founder, Living in Digital Times
In July of 2017 the Chinese government issued a development plan to make the country the world leader in artificial intelligence by 2030. So far things are going better than pretty well.
The government’s commitment to AI dominance, the sheer amount of data that a country as large as China can feed to its AI learning systems, a mobile-dominated infrastructure, and an edge on chip manufacturing for AI-intensive activities like facial and image recognition contribute to China’s AI success story.
Deep machine learning, the ability for machines to ingest data, learn from it and then make predictions from it requires lots of data. “There are 160 cities in China with over 1 million people; there are 10 in the U.S., says Deborah Weinswig, Senior Analyst for Fung. China now has 751 million people online (more than 95 percent of them access the internet using mobile devices, according to the China Internet Network Information Center).
Data Everywhere
The sheer amount of data captured and processed every day in China is staggering. Every time someone enters a search query into Baidu (a Chinese search engine), pays a restaurant tab with their WeChat wallet, shops on Taobao (a Chinese online retailer) or catches a ride with Didi (China's ridesharing app), to name a few, that data is being used to create more accurate algorithms that help predict everything from inventory demand to traffic congestion.
Facial and Image Recognition Plays a Central Role
One of the keystones to intelligent systems is facial and image recognition. In an ambitious program called “Xue Liang,” which can be translated as “Sharp Eyes,” security cameras in China appear just about everywhere: on roads, in malls and shops, in cars and homes.  Ultimately they will all be connected into a single system capable of recognizing all sorts of things from street jaywalkers and highly trafficked areas, to overtired drivers.
In the retail and the medical worlds, image recognition plays a critical part in the AI platform. A few years ago, Baidu added an AI-powered image search to its mobile app, allowing a user to snap a photo of a piece of merchandise that could be identified online along with its price and availability.
Today, the BingoBox, China’s staff-less stores combine online and AI tools with physical stores. These stores have no staff, and operate by scanning QR codes to find out about an item and then pay for it. Facial recognition is used to let you in and out of the store. Personal preferences are recorded and offer you items it thinks you’ll enjoy on your next visit. 
“Shopping”, says Debra Weinswig, “is a sport in China”.  Jack Ma of Alibaba calls these new stores the “harmonious integration of online and offline.”

In medical hospitals, doctors are depending on AI and imaging to scan imaging data faster and looking for irregularities in an x-ray for example that might go undetected by a human technician. MegaVii, a Chinese startup, captures 1.3 billion facial images for applications including insurance, corporations and government.
And, in a controversial social credit system that rates citizens for both good and bad behaviors (say paying taxes on time, or not having parking tickets), AI is amassing data on just about every part of daily life.
Underlying the recognition system are imaging chips capable of seeing very fine granularity are able to make remarkable distinctions. Cambricon Technologies, a chip maker developing optimized chips for AI, has big plans for the next three years. In three years, the company estimates they will have one billion smart devices using its processor and own 30 percent of China’s high-performance AI chip market.
According to the China Morning Star, Cambricon, backed by the Chinese Academy of Sciences and State Development & Investment Corp, is launching an AI processor that focuses on visual applications and specialized applications like intelligent driving.
Finally, startup money for AI projects is plentiful.  According to CB Insights, China accounted for 48 percent of the world’s total AI startup funding in 2017. 

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