According to the plan, the government will provide great capital resources, market guiding and political support to AI development, and meanwhile strengthen links among private entreprises, research institutes and military bodies to promote mutual development (Yifei Fan, 2018).
In October 2017, at the 19th Party Congress, President Xi Jinping outlined the objective of developing China into a “country of innovators,” which aims for “the frontiers of science and technology.” Developing AI technologies, which found a mention in Xi’s speech, is critical for achieving that objective (Manoj Kewalramani, 2018).
“From 2013 to the first quarter of 2018, China’s investment and financing in the AI industry accounted for 60% of the world’s total,” China’s AI Development 2018 report stated (Gordon Watts, 2018).
With a $14 trillion GDP, China is predicted to account for over 35% of global economic growth from 2017 to 2019—nearly double the US GDP’s predicted 18%. And AI is responsible for a big chunk of that (Peter H. Diamandis, 2018).
PricewaterhouseCoopers recently projected AI’s deployment will add $15.7 trillion to the global GDP by 2030, with China taking home $7 trillion of that total, dwarfing North America’ $3.7 trillion in gains (Peter H. Diamandis, 2018).
According to AI Superpowers written by Lee Kai Fu, there are four main drivers are tipping the balance in China’s favor:
1. Abundant data
2. Hungry entrepreneurs empowered by new tools
3. Growing AI expertise
4. Mass government funding and support
1. Abundant Data
China’s biggest advantage is the sheer quantity of its data. Tencent’s WeChat platform alone has over one billion monthly active users. That’s more than the entire population of Europe. Take mobile payments spending: China outstrips the US by a ratio of 50 to 1. Moreover, Chinese e-commerce purchases are almost double US totals (Peter H. Diamandis, 2018).
Chinese AI giants like Tencent have created unified online ecosystems that concentrate all your data in one place. Whereas American users’ payment and transportation data are fragmented across various platforms (Peter H. Diamandis, 2018).
That means mobile payment platforms like WeChat Wallet and Alipay have data on everything from your dumplings purchase from a street vendor to your recent RMB 100 donation to an earthquake relief fund. This allows them to generate complex maps charting hundreds of millions of users’ every move (Peter H. Diamandis, 2018).
With the unequaled rise of bike-sharing startups like China’s ofo and Mobike, Chinese companies can now harness deeply textured maps of population movement, allowing them to intuit everything from your working habits to your grocery shopping routine (Peter H. Diamandis, 2018).
As Chinese tech companies continue merging users’ online behavior with their physical world, the data they collect offers them a tremendous edge over their Silicon Valley counterparts (Peter H. Diamandis, 2018).
2. Hungry Entrepreneurs
Former founder-director of Google Brain Andrew Ng noted the hunger raving among Chinese entrepreneurs: “The velocity of work is much faster in China than in most of Silicon Valley. When you spot a business opportunity in China, the window of time you have to respond is very short.” (Peter H. Diamandis, 2018)
Now home to three of the seven AI giants (Baidu, Alibaba, and Tencent), China also sees a thriving AI startup ecosystem (Peter H. Diamandis, 2018).
Just this year, China’s computer vision startup SenseTime became the most valuable AI startup in the world. Capable of identifying your face, gauging your age and even your potential purchasing habits, SenseTime is now a world-class leader in facial recognition technologies, applying their AI to everything from traffic surveillance to employee authorization (Peter H. Diamandis, 2018).
3. AI Expertise
China had barely woken up to the AI revolution in 2012. But in a few short years, China’s AI community has caught up fast. While the world’s most elite AI researchers still largely cluster in the US, favoring companies like Google, Chinese tech giants are quickly closing the gap (Peter H. Diamandis, 2018).
Chinese AI researchers stand shoulder-to-shoulder with their American contemporaries. At AAAI’s 2017 conference, an equal number of accepted papers came from US- and China-based researchers (Peter H. Diamandis, 2018). China published the largest number of AI-related research papers, as well as highly cited papers. China was also ranked first in the number of AI-related patents, most of which focus on application (Gordon Watts, 2018).
Nearly 19,000 scientists and technicians were actively involved in artificial intelligence research last year, and the number will continue to rise. Tech companies are sprouting up and there are more than 4,000 AI enterprises with half of them startups (Gordon Watts, 2018).
We’ve also seen increased collaboration between China’s top tech firms and emerging student talent. Tencent, for instance, sponsors scholarships for students at a lab in Hong Kong’s University of Science and Technology, granting them access to masses of WeChat data (Peter H. Diamandis, 2018).
Meanwhile, Baidu, Didi, and Tencent have all set up their own research labs (Peter H. Diamandis, 2018).
As far back as 2013, Baidu started an internal research lab it called The Institute of Deep Learning. Now, it runs several other labs, including the 200-persons outpost in Silicon Valley. Baidu employs more than 1,800 researchers and engineers who work on AI, including driverless cars and other robotics as well as many online services. Deep learning technology is already driving everything from the Baidu search engine to the company’s image and speech recognition services (Yifei Fan, 2018).
Tencent has established an AI lab in Seattle in May 2017, and the company is also building a talented research team in China. Tencent already makes use of machine learning in its products (for personalized news recommendations and search, for example). Tencent’s AI Lab has so far around 50 world-class AI scientists, researchers and experts, focusing on AI related research fields such as machine learning, computer vision, speech recognition, and natural language processing. Its massive data from more than 980 million users and its technical advantages constitute a great asset to the company’s top AI team (Yifei Fan, 2018).
The e-commerce giant Alibaba not only applies AI-enabled chatbot, image recognition and machine learning based recommendation to its platform, the growth of its affiliate company Ant Financial is almost being shaped by the company’s AI research team. Yuan (Alan) Qi, a vice president and chief data scientist at Ant, says that “AI is being used in almost every corner of Ant’s business, we use it to optimize the business, and to generate new products.” For instance, Ant Financial is offering for free their AI-driven image recognition system to aid vehicle insurance claims adjustors. It enables insurers to assess automobile damage by algorithm in six seconds (Yifei Fan, 2018).
China’s Face++ now leads the world in face and image recognition AI, beating out top teams from Google, Microsoft and Facebook at the 2017 COCO image-recognition competition (Peter H. Diamandis, 2018).
Voice recognition software company iFlyTek has not only outcompeted teams from Alphabet’s DeepMind, Facebook and IBM Watson in natural-language processing, but has done so in its “second language” of English (Peter H. Diamandis, 2018).
Now the most valuable AI speech company in the world, iFlyTek’s cutting edge technology could one day enable translation earpieces that instantaneously translate speech into any language (Peter H. Diamandis, 2018).
4. China’s Government Directive
At national level, Chinese government published in 2016 a 3-year guidance in support of AI development, including capital funding and IP protection. It then approved a 15-year project (China Brain Project) the same year to research into the neural basis of cognitive function, with additional goals of improving diagnosis and prevention of brain diseases, and driving information technology and artificial intelligence projects that are inspired by the brain (Yifei Fan, 2018).
The central government then established China’s AI Lab in March 2017 to boost the country’s overall competence in AI: Baidu is in charge of the lab in partnership with other Chinese elite universities. The lab is responsible for researching topics in: machine learning-based visual recognition, voice recognition, new types of human-machine interaction and deep learning (Yifei Fan, 2018).
Within a year, Chinese VC investors were pouring record sums into AI startups, surpassing the US to make up 48% of AI venture funding globally. Over the past decade, Chinese government spending on STEM research has grown by double digits year on year (Peter H. Diamandis, 2018).
Mayors across the country (largely in eastern China) have built out innovation zones, incubators and government-backed VC funds, even covering rent and clearing out avenues for AI startups and accelerators (Peter H. Diamandis, 2018).
In the meantime, local governments have begun to team with China’s leading AI companies to build up party-corporate complexes. Acting as a “national team,” companies like Baidu, Alibaba, Tencent, and iFlyTek collaborate with national organizations like China’s National Engineering Lab for Deep Learning Technologies to pioneer research and supercharge innovation in self-driving cars, smart cities, computer vision for medical diagnosis, and voice intelligence (Peter H. Diamandis, 2018).
A number of local governments call for the establishment of dedicated AI industry parks or hubs. For instance, Shanghai aims to build AI industrial clusters across the city with different focuses such as intelligent driving, intelligent robots and intelligent software and hardware, while Beijing is planning to build an $2.01 billion AI intelligence development park (Manoj Kewalramani, 2018).
Most local governments are looking to leverage their distinctive advantages while devising their AI strategies. So Anhui province is seeking to build on the speech recognition expertise available in the capital city, Hefei. Hebei province wants to focus on intelligent equipment and manufacturing industries. And the Hubei provincial government is banking on leveraging the clout of the East Lake High-tech Development Zone (Optics Valley) in Wuhan to develop an AI industrial cluster of global influence (Manoj Kewalramani, 2018).
China’s government is flooding the market with AI-targeted funds as Chinese tech giants and adrenalized startups rise to leverage this capital (Peter H. Diamandis, 2018).
China’s Four Competitive Advantages in AI Development
1. Data Availability
As machine learning algorithms become more and more commoditized, access to huge volumes of training data is starting to become the core competitive advantage. Chinese users have different notions of and expectations for privacy and willing to provide personal information for convenience. By 2020, China’s digital data universe is going to surpass US. China’s share of the global digital universe will grow from 364 exabytes from 2012 to 8.6 zettabytes in 2020, whereas US from 898 exabytes to 6.6 zettabytes (Yifei Fan, 2018).
2. Talent Pool
Chinese researchers are already savvy in AI. In 2015, 43% of the top academic papers relating to AI were published with one or more Chinese researchers worldwide. China traditionally has strong math training which has already generated a large number of data scientists domestically. In addition, there are more and more US-trained computer science PhD returnees (Yifei Fan, 2018).
3. Funding
KPMG found investment by venture capital (VCs) in China reached a record high in 2016, despite a global slowdown. China is also prompting provincial governments to acquire companies and invest in start-ups: Chinese regions are armed with $445 billion for VC investments. The other way round, China investors are investing heavily in American AI startups: over the past six years, they helped finance 51 American artificial intelligence companies, contributing to the $700 million raised, according to the recent Pentagon report (Yifei Fan, 2018).
4. Chinese Pragmatism
Chinese companies are more pragmatic about turning generic work into value-oriented applications to drive business value, especially Alibaba and Tencent. Alibaba, for example, is good at using AI to provide customized service and support based on users’ purchasing behavior and interests; Tencent is researching AI under 3 main topics closely tied to their core business: content, social and game (Yifei Fan, 2018).
Read more: Why Learning Chinese Is Important ?
Application of AI by Alibaba
1. Tmall Smart Selection
This AI-powered algorithm backed by deep learning and natural language processing helps recommend products to shoppers and then communicates to the retailers to increase inventory to keep up with the demand (Bernard Marr, 2018).
2. Dian Xiaomi
This AI-powered chatbot can understand more than 90% of customer’s queries according to Alibaba and serves more than 3.5 million users a day. The latest version of the chatbot can understand a customer’s emotion and can prioritize and alert human customer service agents to intervene (Bernard Marr, 2018).
3. Robots to Pack & Drones to Deliver
More than 200 robots in automated warehouses can process 1 million shipments each day. Once the robots received the orders, they packaged and shipped the goods, and, in some cases, their efficiency allowed same-day shipment. Alibaba also used drones for some deliveries (Bernard Marr, 2018).
4. Investment in SenseTime and DAMO Academy
Alibaba is the largest single investor in SenseTime: an AI start-up known for its facial-recognition technology, that launched an AI lab in Hong Kong. The lab hopes to "advance the frontier of AI" by supporting other start-ups as they commercialize their AI tech and develop ideas and products (Bernard Marr, 2018).
Alibaba plans to spend $15 billion over three years on DAMO (discovery, adventure, momentum, and outlook) Academy (Bernard Marr, 2018).
5. City Brain: AI Control for Cities
With its City Brain project, Alibaba hopes to help cities run their operations by artificial intelligence. City Brain uses a cloud-based system where data about a city and everyone in it is stored and processed through AI algorithms. The project’s success in reducing traffic jams by 15% was achieved by monitoring every vehicle in the city (Bernard Marr, 2018).
In addition to these examples, Alibaba uses AI to optimize its supply chain, build products and drive personalized recommendations. Ultimately, Alibaba aspires to be the tech giant to provide cloud-based AI which would make AI available to anyone with a computer and internet connection (Bernard Marr, 2018).
Read more: China's One Belt and One Road Initiative (OBOR)
Application of AI in Fintech and Insurtech
1. Process Automation
Ant Financial launched in June 2017 an AI-driven, image-recognition system to automate the investigation of vehicle insurance claims. According to Ant Financial, exterior damage claims make up about 60% of the 45 million private vehicle insurance claims filed in China every year. In a demonstration, Ant Financial’s algorithm took 6 seconds to assess the damage in 12 different cases, whereas human investigators needed over 6 minutes to reach a verdict over the same claims (Yifei Fan, 2018).
ZhongAn applies biometric recognition to automatically insure accident insurance, which is more efficient than traditional identity registration and insure/claim application. Once runners’ face identified and matched with the ID photo they provided, Zhong An will activate their sport accident insurance immediately to cover them during the race, thus eliminating any procedure and avoiding other people replacing registered runners to participate in the marathon and benefit from insurance coverage. This technology has already be successfully used to identify marathon players in 4 races. It resulted an average of 40% reduction of manpower (Yifei Fan, 2018).
For customer onboarding (selfie vs administrative tasks), Ping An’s agent only needs to take a selfie of the customer and him/herself, to immediately authenticate through ID photos. Then, by using natural language processing, voice recognition, the agent follows the script/steps while the customer replies. Depending on how the customer replies, the script will be different and the engine will know what kind of questions the customer should be prompted. In 5 minutes instead of 45 minutes, customers can get their policy done and sign by touching the phone screen (Yifei Fan, 2018).
2. Underwriting and Credit Scoring
ZhongAn is leveraging deep learning and machine learning to empower its big data analytics, which has significant impact on: real-time insurance pricing, credit analysis and rating, credit risk pricing, user behavior analysis, accurate marketing and customized products and services (Yifei Fan, 2018).
For example, for its Flight Delay Compensation Insurance (FDCI), ZhongAn applies its big data platform to gather various data sets - the flight dynamic state of Airline Company, the passenger identification of AIR Regulation, weather data from Meteorological Bureau to estimate the probability of flight delay. Thanks to AI, customers can purchase this insurance product even 15 minutes before departure (Yifei Fan, 2018).
3. Fraud Claims Detection
PingAn created its big data platform “PingAn Brain” in 2015. The platform applies data mining, machine learning, deep learning in analyzing both structured and unstructured data (its historical customers’ data, internet data, financial transaction data and tens of million enterprises’ data ) to help the company in: customer profiling, risk management, fraud claims prevention and detection, claim management automation as well as health management. In one year, its machine learning model saved PingAn $ 302 million from fraudulent claims and achieved a 78% accuracy in fraud detection, compared to 21% the previous year (Yifei Fan, 2018).
PICC, China’s largest property insurer, is applying Chinese start-up 4Paradigm’s own machine learning algorithm to root out fraudulent claims. 4Paradigm’s approach not only identifies suspect claims but continuously improves the accuracy of this identification by parsing petabytes of claim data in order to broaden its ability to highlight subtle fraud indicator (Yifei Fan, 2018).
Application 0f AI in Other Sectors
1. Health
Dermatology is among the first health disciplines to embrace AI. Using computer vision and AI analysis, software can identify 90% of the 700 diseases most common among outpatients (Pablo Robles, 2018).
2. Driverless Vehicles
China is still lags behind the US in developing driverless vehicles for the road. The Chinese government has set the goal of having a manufacturing industry in place for sensors and embedded chips with a value exceeding $1.4 billion by 2020 (Pablo Robles, 2018).
3. Facial Recognition
China is developing a facial recognition system with a database of 1.3 billion ID photos that can be matched in seconds, with an accuracy rate of 90%. This programme may eventually power China’s Social Credit System: a metric to gauge the “trustworthiness” of citizens. Recently, SenseTime became the most valuable AI start-up in the world. The company drives China’s ambition to dominate global AI (Pablo Robles, 2018).
4. Robots
The Chinese robot market is forecast to grow at an average annual rate of 23.4% in the four years to 2019, much faster than global shipment growth of 13%, according to the International Federation of Robotics. China’s robot makers aim to supply 50% of the domestic market by 2020, rising to 70% by 2025 (Pablo Robles, 2018).
Final Thoughts
Once disregarded as a market of ‘copycats’ looking to Silicon Valley for inspiration and know-how, China’s AI ecosystem has long departed this stage (Peter H. Diamandis, 2018).
Propelled by an abundance of government funds, smart infrastructure overhauls, leading AI research, and some of the world’s most driven entrepreneurs, China’s AI ecosystem is unstoppable (Peter H. Diamandis, 2018).
Edited by: 浪子
Bibliography
Peter H. Diamandis. (2018). China Is Quickly Becoming an AI Superpower. Retrieved from
https://singularityhub.com/2018/08/29/china-ai-superpower/#sm.0000tjaat9otgcq4r3l1fgppefobf
Yifei Fan. (2018). China: The ‘Powerhouse’ of AI? Retrieved from
https://www.axa.com/en/spotlight/story/china-the-powerhouse-of-ai
Manoj Kewalramani. (2018). Breaking Down China’s AI Ambitions. Retrieved from
https://factordaily.com/china-ai-policy-and-industry/
Bernard Marr. (2018). The Amazing Ways Chinese Tech Giant Alibaba Uses Artificial Intelligence And Machine Learning. Retrieved from
https://www.forbes.com/sites/bernardmarr/2018/07/23/the-amazing-ways-chinese-tech-giant-alibaba-uses-artificial-intelligence-and-machine-learning/#305eb868117a
Gordon Watts. (2018). Artificial Intelligence and the Rise of the Robots in China. Retrieved from
http://www.atimes.com/article/artificial-intelligence-and-the-rise-of-the-robots-in-china/
Pablo Robles. (2018). China Plans to be a World Leader in Artificial Intelligence by 2030. Retrieved from
https://multimedia.scmp.com/news/china/article/2166148/china-2025-artificial-intelligence/index.html
Artificial Intelligence Powerhouse - China
Reviewed by 浪子
on
October 20, 2018
Rating:
Reviewed by 浪子
on
October 20, 2018
Rating:
