Global artificial intelligence industry whitepaper
Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
1. New trends of AI innovation and integration 5 1.1 AI is growing fully commercialized 5 1.2 AI has entered an era of machine learning 6 1.3 Market investment returns to reason 9 1.4 Cities become the main battleground for AI innovation, integration and application 14 1.5 AI supporting technologies are advancing 24 1.6 Growing support from top-level policies 26 1.7 Over USD 6 trillion global AI market 33 1.8 Large number of AI companies located in the Beijing-Tianjin-Hebei Region, Yangtze River Delta and Pearl River Delta 35 2. Development of AI technologies 45 2.1 Increasingly sophisticated AI technologies 45 2.2 Steady progress of open AI platform establishment 47 2.3 Human vs. machine 51 3. China’s position in global AI sector 60 3.1 China has larger volumes of data and more diversified environment for using data 61 3.2 China is in the highest demand on chip in the world yet relying heavily on imported high-end chips 62 3.3 Chinese robot companies are growing fast with greater efforts in developing key parts and technologies domestically 63 3.4 The U.S. has solid strengths in AI’s underlying technology while China is better in speech recognition technology 63 3.5 China is catching up in application 64
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Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
4. AI reshapes every industry 68 4.1 Financial industry: AI enhances the business efficiency of financial businesses and reforms their internal operations 71 4.2 Education: AI application covers the whole education process 78 4.3 Digital government services: favourable policies expedite intelligent transformation 83 4.4 Healthcare: AI-based applications are getting mature 85 4.5 Autonomous driving: leading force in auto industry reforms 89 4.6 Retail: Industry convergence driven by AI 93 4.7 Manufacturing: Huge potentials for application of smart manufacturing 97 4.8 Smart city: AI-based urban infrastructure innovation system 102 Deloitte China Contacts 105
03 Global artificial intelligence industry whitepaper | Key findings
Key findings:
1 AI is growing fully commercialized, bringing profound changes in all industries. AI technologies have been deployed in financial, healthcare, security and a number of other areas, with widening application scenarios. The commercialization of AI is playing a positive role in accelerating business digitalization, improving industry chain structures and enhancing information use efficiency.
2 AI has entered an age of machine learning, and the future of AI development will depend on the integration of key technologies and industries. Every development of AI has been associated with breakthroughs in research methods, and deep learning is one of the most important technological breakthroughs of machine learning. As AI research and application continues to expand in scope, AI will see deeper integration and application of more technologies in the future.
3 AI investment is returning to reason, with underlying technologies and easy-to-deploy applications more favored by AI leading institutions. As the investment and business communities deepen their understanding of AI, the AI investment and financing market becomes more rational, with reduced frequency of investment and financing but continued increase of investment amounts. Especially after a round of competition within the industry, underlying technology companies and deployable application areas, such as startup projects in healthcare, education and autonomous driving, continue to be favored by leading AI institutions.
4 Cities are the vehicle that carries the innovation, integration and application of AI technologies, and also the center where humans build up full sense of AI technological experience. Different cities perform differently in the top-level design, algorithm breakthrough, factor quality, integration quality and application quality, forming diverse and individualized AI development models.
5 Policies and capital are driving Beijing-Tianjin-Hebei region, Yangtze River Delta and Pearl River Delta to be regions with the most AI companies, with Beijing and Shanghai taking the lead. For example, Shanghai put in place measures in terms of tax incentives, capital subsidies, talent attraction and government process improvement to enhance its business environment, and has attracted large amount of investment and financing capital, AI companies and talents, significantly enhancing its R&D strengths. This would also facilitate the scale up of upstream and downstream enterprises on the AI industry chain and help strengthen the city's AI industry capabilities.
1 Global artificial intelligence industry whitepaper | Key findings
6 First tier cities represented by Shanghai and Beijing have long been leading in terms of the number of talents and enterprises, capital environment and R&D strengths. Beijing and Shanghai each have more than 600 AI companies, and Shanghai has established enterprise AI labs with tech giants Tencent and Microsoft, as well as AI unicorns SenseTime and Yixue Education—Squirrel AI.
7 AI is driving the financial industry to build a broader high-performing ecosystem with enhanced business efficiency for financial enterprises and transformed enterprise process of internal operation. Traditional financial institutions and tech companies are working together to promote deeper penetration of AI in the financial industry, restructure services framework, increase service efficiency, and reduce financial risks while providing individualized services to long tail clients.
8 As application of AI in education further deepens, application scenarios are shifting to cover full process of teaching. Among the types of AI applications in education, AI-adaptive learning is applied most widely in all the learning processes. In addition, intelligent adaptive learning system is expected to catch up from behind benefited from China's large population base, shortage in education resources and commitment to education.
9 Digital government is mainly driven from top down achieve digitalization goals of government processes to accelerate intelligent transformation of the government. The needs for digital government construction vary by regions, thus enterprises require customized solutions. As the threshold for the public security sector grows higher, the strong remain strong in the sector with deepened industry convergence.
10 The auto industry dominated by autonomous driving will see a transformation of its industry chain. The production, channels and sales models of traditional auto makers will be replaced by emerging business models. The boundary between rising tech companies of autonomous driving solutions and traditional auto makers will be broken. With the emergence of shared cars, shared mobility under autonomous driving will replace the concept of private cars. The development of industry norms and standards for autonomous driving will facilitate the emergence of more secure and more convenient unmanned cargo delivery and logistics.
2 Global artificial intelligence industry whitepaper | Key findings
11 The potential of AI application in manufacturing have been underestimated, and quality data resources are not fully utilized. As a highly specialized industry, manufacturing requires highly complex and customized solutions. Thus, AI technologies in this sector are mainly applied in areas that are easy to duplicate and expand, such as product quality control, sorting, and predictive maintenance. However, the massive data—reliable, stable and updated constantly—generated by production facilities has not been fully utilized. Such data could provide good examples of machine learning for AI companies to address actual problems in the manufacturing processes.
12 Application scenarios in retail have developed from separation to convergence, and traditional retailers are partnering with startups to build scenarios around human, goods, stores and supply chains. The development of AI diversifies in each retail link, and application scenarios become fragmented and enter a period with scale pilots. Traditional retailers begin to engage AI technologies, and will compete with tech giants in big data application and AI, which means retailers would be more proactive in forming partnerships with startups.
13 AI applications in healthcare sector are growing rapidly, but the sector needs to establish standardized mechanisms of market entry for AI products and speed up the construction of healthcare data base. The emergence of AI will help address the shortage and uneven allocation of medical resources as well as many other livelihood issues in the healthcare sector. However, in a strictly regulated sector that concerns people's life and health, whether AI could be applied extensively as expected will depend on the development of medical and data regulation standards.
3 Global artificial intelligence industry whitepaper | Key findings
4 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
1. New trends of AI innovation and integration
1.1 AI is growing fully enterprises have been able to collect and users may also shift from individual commercialized and make use of user information consumers to enterprise consumers, Now AI has entered a new stage from multiple dimensions via various or both, due to the change of product to become fully commercialized, technological means and provide features. The last is labor change: exerting different impacts on players consumers with pertinent products and The application of new technologies of traditional industries and driving services, at the same time satisfy their such as AI is enhancing the efficiency changes in the ecosystems of potential needs through insights into of information use and reducing the these industries. Such changes are development trends gained via data number of employees. In addition, the mainly seen at three levels. First is optimization. Second is industry change: wider use of robots would also replace enterprise change: AI is engaged in the The change brought by AI would drive labors in repetitive tasks and increase management and production processes fundamental changes in the relationship the percentage of technological and of the enterprise, with a trend of being of upstream and downstream sectors management personnel, bringing increasingly commercialized, and some on the traditional industry chain. The changes in the labor structures of enterprises have realized relatively engagement of AI has expanded the enterprises. mature intelligent applications. These types of upstream products providers,
Figure 1-1: All-round changes brought by AI
1. Enterprise change
Sales Security Anti-fraud HR management Marketing Personal assistant Smart tools
2. Industry change
Finance Healthcare Education Autonomous driving Retail Manufacturing
Digital government Media Legal Agriculture Logistics Oil & gas
3. Labor change
Augmented reality Gesture recognition Robotics Emotion recognition
Source: Public information, Deloitte Research
5 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
1.2 AI has entered an era of machine stored by machines within the near research motivation has been to equip learning future. Computer algorithms growing computer systems with the human As technology advances and develops, more powerful would obtain human-like ability to learn, in order to achieve the way humans learn is evolving from abilities, including vision, speaking, sense artificial intelligence. Machines find evolution, experience and legacy into of direction, etc. gaps in existing knowledge, then imitate communication and storage using human brain and simulate evolution computers and Internet. With the Machine learning is one of AI's core to reduce uncertainties systemically, advent of computers, it has become research areas among all the subfields identify similarities between new and old more efficient and easier for humans of AI. 89% of AI patent applications and knowledge, and complete learning. to acquire knowledge. A vast majority 40% of related patents within the AI of knowledge will be extracted and realm fall in machine learning. The initial
Figure 1-2: Illustration of all levels of AI
Technological support Areas of AI application
Smart healthcare Smart Smart city education Smart Areas of AI technology Digital finance government Robotics Smart Knowledge Autonomous Sensors Intelligent manu- extraction adaptive learning driving facturing Research methods Computer Planning & Chips (schools) vision Optimizing Connectionism (e.g. deep learning) …
Data Expert NLP Bayesian Symbolicism system Backpropagation neural networks Software Probabilistic Inverse … Evolutionism Analogizers framework inference Linear deduction Decision Genetic tree Kernel Cloud service programming Logistic machine regression Support … Random Vector forests Machine
Algorithms
Source: Deloitte Research
6 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Algorithms are the core of AI immature technological capability and of experience, knowledge and rules. As the underlying logic for AI, overpraised reputation sent it to an Capital and government support were algorithms are the direct tools "AI winter" from 1974 to 1980, when once again pulled out, push AI into a that generate AI. From the course research and investment in AI saw second "winter". of history, we can see that AI has substantial declines. developed through three phases The third phase was in the 1990s since brought up in 1956, which also From 1980 to 1987, the research and after. During 1993-2011, with reflect the alternation of algorithms method of expert system became a significantly enhanced computing and research methods. In the first hot topic for AI research, re-igniting power and data volume, AI technology phase during 1960s to 1970s, AI the fever of capital and researchers. were further improved. Till now, the entered into a golden period when During the period from 1987 to 1993, surge in data volume and computing research methods dominated by there had been significant progress in power has helped AI achieve major logics became the mainstream. AI the capability of computers compared breakthroughs in machine learning, attempted to achieve machine-based with those decades ago. People tried especially in the area of deep learning logical deduction and verification, to create an expert system based on dominated by neural networks. AI's but failed at last. The period from computers to solve problems, but development based on deep neural 1970s to 1990s saw the second phase could hardly build an effective system network technology is now in a period of AI development, during which due to lack of data and constraints of rapid growth.
Figure 1-3: The history of AI development
GAN
development Self-adaptive breakthrough Human consciousness system Image analytics breakthrough Neuromorphic technology Deep learning breakthrough
Multi-level text analytics Natural language processing breakthrough Simple neural networks Classic symbolic AI
1956 1984 2000 2008 2012 2014 2016 2017 2022 2030
Source: Public information, Deloitte Research
7 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
In addition, data is an essential element that underpins AI's underlying logic. Without data, data processing for AI will not be possible. With data mining's cleaning, integration, reduction and other pre-treatment means, AI could have adequate data for learning. As AI technologies iterate, the production, collection, storage, calculation, transmission and application of data will all be completed by machines.
Figure 1-4: Development stages of data processing
Computer Internet Internet of Things AI
Data production Labor
Labor Labor
Data collection
Data storage
Machine Machine Machine
Data calculation Machine
Data transmission
Labor
Data application Labor Labor
Source: Public information, Deloitte Research
8 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
1.3 Market investment returns to and policy support, but also powered billion in 2015 - the starting year of reason by the capital market. As the capital China's AI development, and investment From R&D and academic topic to market deepens its understanding of frequency continued to increase in 2016 technological startups, it only takes a AI, market investment in AI is maturing and 2017. The first half of 2019 has few years for AI. Such shift is not only and returning to reason. During the past seen a total investment of over RMB47.8 driven by people's appeals for new five years, China's investment in AI grew billion in China's AI sector with great technologies to unleash productivity rapidly, with a total investment of RMB45 achievements.
Figure 1-5: Changes of AI investment and financing
AI exploration AI commercialization 1,400 700
1,200 600
1,000 500
800 400
600 300
400 200
200 100
0 0 2012 2013 2014 2015 2016 2017 2018
A o nt raised 1 i ion inan ing events
Source: Public information, Deloitte Research
9 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
We identify the following trends through service, robotics, healthcare, industry market investors. From industry our analysis of investment in AI: solutions, basic components and perspective, however, new retail, finance are all higher than those autonomous driving, healthcare and ••Investors favor easy-to-deploy AI in other sectors. From enterprise education, all easy to deploy, indicate application scenarios. Investment perspective, those with a top global more opportunities, and companies and financing data in recent years team, financial strength and high-tech engaged in such sectors could see show that investment frequencies gene are more favored by secondary more investment opportunities. and amounts raised in business
Figure 1-6: Distribution of investment and financing frequency by AI sectors
Healthcare
Financing
Robotics
Transportation
Retail
Education
Security
Manufacturing
0 100 200 300 400 500 600
2016 2017 2018 2019H1
Source: Public information, Deloitte Research
10 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
••Underlying technology startups important support for AI development, decreasing, investors remain vigorous become popular within the investment in underlying technologies in "A" round investment, which at investment market. Unlike the is expected to continue growing with present is the one with the highest preference for application-oriented the advancement of AI in China. investment frequency. Strategic AI companies in earlier stage, the investment started to explode in 2017. ••The proportion of companies investment market is turning its eyes As AI market sectors grow mature, that complete "A" and "B" on startups engaged in AI underlying leading enterprises, mostly Internet round financing remains the technologies. Such companies can giants, turn to strategic investment highest, with growing strategic easily become popular and are more seeking for long-term partnership investment. More than 1,300 AI competitive in the market with a and development. This also suggest enterprises have secured venture high ceiling. As China falls behind the that strategic cooperation between AI capital investment . Though proportion US in terms of development of AI sector and industries begin grow on of investment before "A" round is underlying technologies, which are an capital domain.
Figure 1-7: Rounds of investment in AI from 2013 to 2019
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0% 2013 2014 2015 2016 2017 2018 2019H1
Before A round A round B round C round D round Strategic investment
Source: Deloitte Research
11 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
••Internet giants' AI investment the implementation of a national AI and smart home as their priorities links to the upstream and development strategy. of investment. Companies under downstream of industries related CAS Holdings backed by the Chinese For example, Alibaba focuses its to their businesses. The boom of Academy of Sciences, however, are investment in security and basic AI development also drives Internet involved in AI technological and components, with major companies giants with a keen sense of smell to application fields including chips, invested including SenseTime, MEGVII pursue their own strategic plans. Led healthcare and education. As digital and Cambricon; Tencent mainly by Alibaba, Tencent, Baidu and JD.com, technologies transform and integrate invests in areas such as intelligent they have invested in all fields of AI in each of the industries, AI application health, education and smart car, with sector. Projects invested by investment in areas such as autonomous driving, representative companies including institutions all fall in the upstream and healthcare, education, finance and NIO and iCarbonX; Baidu's investment downstream domains of the industries smart manufacturing will be of vital mainly falls in auto, retail and smart in their future strategic plans, and importance for top enterprises. home, and JD.com sees auto, finance these projects are also driving for
Figure 1-8: Major fields of investment by leading AI enterprises
SIG SIG IBM WELTMEISTER GOOGLE SIG Apple XtalPi Syngli Synetiq Abc fintech Apple Silk Labs Apple ABEJA (Acquired) IBM Drive AI (Acquired) Tecacent (Acquired) Microsoft Volley Labs Hafnium Labs VocallQ (Acquired) DeepMind (Acquired) Voiceitt LearnSprout Microsoft Explorys Kaggle (Acquired） (Acquired) Datazen (Acquired) JDcom IBM GOOGLE Software Tiantu Capital NIO (Acquired) Accrue Edwin CASH Capital IDRIVERPLUS ZMT Open AI Carrobot Tongdun Apple Yunhu CASH Capital CICC DATA Healthcare CAS FreightWaves Squirrel AI Learning W&R Investment Simpleware Alibaba JD.com Technology Xiao-i Robot Bitmain Baidu Taicang TMiRob BAIDU Video++ ICkey Technology Raysight Knowbox NIO Cambricon ChinaScope Medical Zike Idriverplus Baidu Linking Med Alibaba Juxinli.com Zuoyebang smartereye MiningLamp Cambricon Hesaitech Yonghong Tech Tencent JD.com Tencent DeePhi Tech Orbbec Zhongan RIMAG Afanti SIG Zhizhen Alibaba Kneron Insurance Yuantiku Bytedance C-SKY Internet yangcong345 Xpeng Motors AISpeech Video++ Technology Alibaba Alibaba DeepMap Alibaba SenseTime Zhongan Tencent Xiaobao Online MEGVII Tencent Insurance iCarbonX Tencent Knowbox IrisKing Hesai Ant Financial Xtalpi NIO Moredian Technology Technology SoundAI
Finance Healthcare Education Autonomous Enterprise Basic driving service components
*Incomplete statistics, only include some representative companies Source: Deloitte Research
12 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
As an emerging industry in the future, artificial intelligence companies are characterized by high growth. Thus, we screened out 50 high-growth companies based on growth rate data collected from incomplete public information and among the artificial intelligence companies in the Deloitte Technology Fast 500 list.
Figure 1-9: Global High-growth AI Enterprises
Ranking Company name Country Growth rate Segment 1 Shape Security U.S.A ~23,000%** Business Services 2 BrainChip U.S.A ~16,000%** Chip 3 Razorpay Software India ~11,000%** Finance 4 BioCatch Israel ~10,000%** Finance 5 Signifyd U.S.A ~6,000%** Business Services 6 Yixue Education—Squirrel AI China ~5,000%* Education 7 UiPath U.S.A ~4,000%** Robotics 8 Remark Holdings, Inc. U.S.A ~3,700%** Data Services 9 Domino Data Lab U.S.A ~3,200%** Finance 10 Voltari U.S.A ~3,000%** Advertisement 11 Mujin Inc Japan ~1,200%* Industrial 12 Vectra AI U.S.A ~1,000%** Security 13 DataRobot U.S.A ~900% Deep Learning 14 Bytedance China ~700%* Business Intelligent 15 Pinduoduo China ~650% Retail 16 Cloudwalk China ~600%* Facial Recognition 17 Welltok U.S.A ~500%** Healthcare 18 Tesla U.S.A ~430%** Autonomous Driving 19 SenseTime China ~400% Computer Vision 20 BounceX U.S.A ~400%* Marketing 21 CrowdStrike U.S.A ~374%* Network Security 22 Alteryx U.S.A ~370%** Data Mining 23 SequoiaDB China ~363%* Finance 24 Avant U.S.A ~360%** Finance 25 Cloudera, Inc. U.S.A ~350%** Data Services 26 JiaHe Info China ~330%* Aguriculture 27 GumGum U.S.A ~310%** Computer Vision 28 Blue Prism UK ~304%* Robotics 29 Unisound China ~300% Speech Recognition 30 SparkCognition U.S.A ~260%** Network Security 31 SmartDrive Systems U.S.A ~250%** Autonomous Driving 32 HireVue U.S.A ~230%** Business Services 33 Alibaba Group China ~225%** Comprehensive 34 Iflytek Co.Ltd China ~223%** Speech Recognition 35 Facebook U.S.A ~210%** Comprehensive 36 Uber U.S.A ~193%* Autonomous Driving 38 Splunk U.S.A ~190%** Business Analysis 37 MEGVII China ~190% Computer Vision 39 BYJU'S India ~184% Education 40 ZeMoSo Technologies Pvt Ltd India ~170%* Comprehensive 41 XiaoMi China ~162%** IoT 42 Conversica U.S.A ~150%** Marketing 43 9FGROUP China ~140%* Finance 44 Amazon U.S.A ~110%** Comprehensive 45 NVIDIA U.S.A ~107%** Chip 46 Globant U.S.A ~106%** Data Services 47 Salesforce U.S.A ~90%** Cloud computing 48 Alphabet U.S.A ~80%** Comprehensive 49 Ant Financial China ~60% Finance 50 Domo U.S.A ~40% Business Intelligent
Note: In the table, “~” is the estimated range; the growth rate is based on three years **, and in the absence of three years ** data, it is based on two years * and in the absence of two years * data, it is based on the year-on-year growth rate; the data are incomplete statistics, which are derived from published public data and private databases, and do not guarantee the accuracy and timeliness of the data. 13 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
1.4 Cities become the main ecosystems that facilitate integration • Factor quality, including AI leading battleground for AI innovation, of technologies and the city. Through figures, capital support, pay level integration and application continuous monitoring of more than of scientists, influence of industry Cities serve as the vehicle that carries 50 AI application segments, over 100 conferences, etc. the innovation, integration and AI related universities and research • Integration quality, including application of AI technologies, and also institutions, over 200 top enterprises, connectedness of frontier disciplines the center where humans build up full more than 500 investment entities, (AI: +Cloud、+Blockchain、+IoT、+5 sense of AI technological experience. 7,000 AI companies and over 100,000 G、+Quantum Computing and other Over the past few years, major cities key AI talents, we have outlined frontier technologies), diversity of around the world have played various the characteristics, framework and innovation entities (top enterprises, roles in driving the development of AI development path of AI technologies academic institutions, etc.), cultural technologies, established their own and industry ecosystems centered on diversity, etc. ecosystems, and achieved initial success cities. Considering the factors in overall, in empowering industry applications we believe that the degree of innovation • Application quality, including and facilitating regional economic and integration of AI technologies in a finance, education, healthcare, digital development, raising thoughts, city can be measured via the following government, autonomous driving, perception and actions on the new five aspects: retail, manufacturing, integrated round of industrial revolution. With AI vehicle development, etc. •• Top-level design, including AI applications being deployed at city level, industry supporting policies, special cities become the main battleground Based on the performance of cities legislations, open data policy and the for AI innovation, integration and globally in terms of the above five level of openness, etc. application. indicators, Deloitte has selected a • Algorithm breakthrough, including total of 20 representative cities of AI Though with varied key success core R&D links of key AI software and innovation, integration and application factors of AI, cities across the world hardware, such as AI chips from three categories: in general have built up development
Figure 1-10: 20 global cities of AI innovation, integration and application in 2019
oronto
an ran is o New or ondon ei ing a Area oston ang ai
en en o o to o
in inga ore ontrea er in aris os Ange es A sterda e Aviv a as idne
Comprehensive hub cities Integrated application cities Innovation-led cities
Source: Deloitte Research
14 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Comprehensive hub cities
Figure 1-11: Comprehensive hub cities
Comprehensive hub cities Top-level design
Application Algorithm quality breakthrough
Integration Factor quality quality
San Francisco London o re ensive Boston Tokyo ities ave e e ent erfor an e in a the five indicators
Source: Deloitte Research
San Francisco Bay Area hosted the AI forum with global impact scientists, which is highly attractive for As a region known globally for AI - 2018 AAAI Conference - to further the concentration of AI talents. As to innovation, San Francisco Bay Area enhance its influence in AI development. application quality, the Silicon Valley performs well in all the five indicators In terms of integration quality, San serves as the core carrier of AI industry of AI innovation, integration and Francisco Bay Area is home to Stanford, for the region, and has attracted IBM, application. For factor quality, San Berkeley, San Diego and a number of Google, NVIDIA, Intel and many other Francisco Bay Area is a center of global other top research universities, and leading tech companies to actively AI capital. Data shows that the region has transferred lots of AI talents to tech expand their operations in different attracted 38% of AI investment globally giants including Facebook, LinkedIn, fields of application including smart during 2000-2016, and over one third Amazon, Apple, and Google. It should home, smart transportation, smart of AI companies in the US have grown be noted that2 the above companies healthcare, smart retail, smart energy out of this region1 . Moreover, San offer an average annual pay of up to and smart water resources. Francisco Bay Area has also actively USD293,000 for machine learning
1. Global AI Development Report 2017, Wuzhen Institute 2. Qianzhan Research Institute
15 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
London Boston Tokyo London has always been standing at The birthplace of AI, Boston has huge Tokyo is the capital city of AI industry the forefront of AI industry innovation influence both in the academic and in Japan. In terms of top-level design, as an AI hub with the highest density of the business communities. From the Japanese government set up innovation in Europe. For application perspective of factor quality, Boston an "AI Strategy Council" to promote quality, AI star company DeepMind, is the host of the world-class AI World the development of AI in Tokyo, headquartered in London, developed a Conference & Expo, and John McCarthy, and has developed various policies Go game robot AlphaGo that defeated father of AI, and Marvin Lee Minsky encouraging enterprises to develop AI. the world's No.1 Go champion Ke have emerged from Boston's academia, As to application quality, Tokyo tends to Jie, which was a milestone in AI's who first came up with the concept of develop towards autonomous driving development. Now DeepMind has "artificial intelligence" at the Dartmouth and robotics. Honda has established partnered with UK's medial institutions Conference and was granted the Turing its AI research base in Tokyo in recent and electrical energy authority to Award for their outstanding contribution years, with a focus on enhancing develop solutions that apply AI in in AI sector. In terms of integration its competitiveness in autonomous healthcare, power and other sectors, quality, Boston houses a number of cars, while Yaskawa is the most in order to enhance disease control world-class universities, with a total representative company in robotics, and energy use efficiency. In terms of 35 universities including Harvard, whose industrial robots have been of integration quality, London is Boston University, UMASS and MIT deployed to conduct assembly and the locomotive of AI financing and continuously providing high-end talents welding tasks in auto, machinery and investment in Europe. Data shows for the development of AI in the region. other areas. As to factor quality, Tokyo that UK's aggregated funds raised In addition, as indicated by MIT, Boston has been active in hosting AI EXPO, an for AI accounted for 49% of that in also has many top-notch AI research international AI exhibition that gathers Europe during 2000-2006, of which institutions, including the world's largest industry leaders including Alibaba, more than 60% concentrated in campus lab – MIT's Computer Science Salesforce and FujiSoft. With regard London3 . According to statistics, UK's AI and Artificial Intelligence Laboratory to integration quality, the Japanese companies have raised up to USD1.251 and the MIT-IBM Watson AI Lab set up government has built a number of AI billion with 145 rounds of financing, by IBM with an investment of USD240 research institutions, including the an average of USD 8.6276 million million. As to application quality, Boston Artificial Intelligence Research Center for each round4 . As to talent, a great takes the lead in AI application in (AIRC) and the Center for Advanced number of AI talents from top schools robotics and bioscience benefited from Intelligence Project, and more than 20 such as Cambridge, Oxford and King's the region's accumulated research universities such as the University of College have significant promoted the experience in the two fields. According Tokyo, Osaka University and Waseda development of cloud computing and AI to Emerj Artificial Intelligence Research, University has also set up AI-related hardware in London. For example, the more than 90% of land mobile robots disciplines, laying a solid foundation for well-known semi-conductor company used by the US military are developed in the development of AI. ARM was separated from Cambridge. Boston.
3. Global AI Development Report 2017, Wuzhen Institute 4. Global AI Development Report 2018, Wuzhen Institute
16 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Integrated application cities
Figure 1-12: Integrated application cities
Integrated application cities Top-level design
Application Algorithm quality breakthrough
Integration Factor quality quality Integrated a i ation ities ave e e ent Beijing Shanghai erfor an e in New York Tel Aviv indi ators s as Los Angeles a i ation a it and fa tor a it
Source: Deloitte Research
New York including Warby Parker, Blue Apron, residential region in Manhattan West, As a financial and technological center Buzzfeed, FanDuel, OscarHealth and and installed large number of electronic in the US, New York performs especially ZocDoc, creating a strong atmosphere detectors utilizing digital technologies to well in AI's integration quality and for enterprise innovation. In terms of monitor transportation, energy and air application quality. With regard to application quality, New York is the quality in real-time within the region. At integration quality, New York's good leader of smart city development in the same time, as the world's financial investment environment and open the US. The New York government capital, New York has also pursued a channels of financing has provided has cooperated with Cisco and IBSG unique path for the development of essential support for the development to launch the Smart Screen City 24/7 Fintech. Many famous global financial of AI startups. Based on the reported program, aiming to convert its traditional institutions, including Citibank, J.P. published by New York State, New York telephone booths into smart screens Morgan and Morgan Stanley, has City has a total of 7,600 tech companies with touch, audio and video features, launched their financial service products in 2016, an increase of 23% compared which provide information inquiry targeting at financial scenarios such as with that in 2010. In addition to the tech service to citizens and serve as WiFi hot smart investment advisory and smart giants from Silicon Valley, there are also spots to build the largest urban WiFi credit. a great number of tech "unicorns" with network in the US. In addition, New York a market value exceeding USD1 billion, has also constructed a commercial and
17 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Shanghai Microsoft-INESA AI Innovation Center Development of AI Industry, aligning As the leader of China's economic and the Shanghai Brain Science and with the country’s planning objectives development, Shanghai has been Brain-Inspired Intelligence Research and putting it ahead of other cities. striving to deepen its AI innovation, Center. The city has also attracted In terms of integration quality, top integration and application, working to Amazon, Baidu, Alibaba, Tencent, research institutions, including Tsinghua build a "Shanghai highland" of AI. With iFLYTEK and other industry innovation University, Beihang University and regard to top-level design, Shanghai centers and AI labs. In terms of Peking University, provide a large continues to improve and refine its application quality, Shanghai as the first number of talents for Beijing’s AI development strategy and policies in national pilot zone for AI innovation industry. The effect of talent aggregation the AI sector. Following the Opinions on and application focuses on developing in the capital makes Beijing an attractive Promoting the City's Next Generation of autonomous driving, AI + 5G, smart cluster of 43% of Chinese AI startups AI Development, Shanghai published the robots, AI + education, AI + healthcare, and AI research centers of domestic Implementation Measures on Speeding AI + industrials and other application and foreign tech giants, such as Google Up High Quality AI Development in scenarios. For example, Tesla is building Beijing AI center, Baidu’s National Shanghai at the World AI Conference a super factory in Shanghai which will Engineering Laboratory for Deep in September 2018. The Measures fully deploy smart and automated Learning Technology and Applications. put forward 22 specific policies on the production technologies. Moreover, Regarding application quality, at the building of AI talent pool, sharing and Shanghai is actively working to construct meeting of promoting the building of application of data resources, industrial the Maqiao Artificial Intelligence application scenarios in Beijing held in distribution and cluster, introduction Innovation Experimental Zone, with June 2019, Beijing Municipal Science & of government funds and support, etc. an aim to build a model for the future Technology Commission released the As to integration quality, as a world- deployment of AI scenarios in Shanghai. first list of ten application scenarios renowned financial center, Shanghai and decided to invest RMB3 billion in has become the core region driving Beijing city construction and administration the setup and operation of AI industry As China’s political and economic and people’s livelihood improvement, investment funds. From the perspective center, Beijing is playing a key role in the creating application scenarios based of investment projects, Shanghai has an innovation, integration and application on AI, Internet of Things (IoT) and big optimal investment environment with of AI technologies in China. In terms of data in order to enhance the city’s lean spatial carriers focusing on incubating top-level design, Beijing has introduced management capability and public AI innovations, where projects launched several policies to accelerate the growth security. In application scenarios for self- cover healthcare, education, big data of AI industry since 2016, including driving, Beijing has issued a self-driving and other popular fields. At present, Measures on Promoting the Innovation testing license to Baidu and provided Shanghai is home to nearly 400 core AI and Development of Intelligent testing venues. companies, and has launched several Robot Industry in Zhongguancun and basic research platforms including the Guiding Opinions on Accelerating the
18 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Tel Aviv oriented on companies and consumers, including the United States AI summit, AI innovation is deeply rooted in the involving social media, e-commerce, Los Angeles Forum for Big Data & DNA of Tel Aviv, Israel, empowering the agriculture, oil, natural gas, mining and Artificial Intelligence and Southern city to take lead in the quality of factor, manufacturing. Take the application California AI & Data Science Conference integration and application around in social media as an example. Cyabra which attracted many established the world. Regarding factor quality, AI helps social media companies identify AI institutions, including Salesforce, startups in Tel Aviv maintain high-level and forecast fake social media accounts IBM, Redis Lab, Microsoft and Uber to volumes of financing and continue to with technologies including user profile release their industry reports at the grow. According to a report released and corpus for sentiment analysis. 2018 conference. In terms of application by a non-profit organization Start-Up quality, Los Angeles has successfully Nation Central, Israel’s AI startups raised Los Angeles applied AI in smart transportation, USD2.25 billion in 20185 . With regard Los Angeles, another key city of AI in smart healthcare, digital governance to integration quality, Israel has 1,150 the United States, is prominent in top- and digital security. The application of AI startups6 covering machine learning, level design and the quality of factor AI in transportation as an example, by deep learning, computer vision and and application. Regarding top-level creating an automated transportation NLP. Besides, Israel also has several top design, the United States introduced the monitoring system composed of a set of research-oriented universities including National Artificial Intelligence Research road sensors, hundreds of cameras and the Hebrew University of Jerusalem, and Development Strategic Plan to 4,500 systematically controlled traffic Israel Institute of Technology and Tel develop public datasets for AI training lights, the city has reduced the traffic Aviv University. In respect of application and evaluate AI technologies. In terms of flow by 12% and improved the vehicle quality, Tel Aviv-based AI companies factor quality, Los Angeles has organized speed by 16%7 . are engaged in several service areas a series of high level AI conferences
5. Source: Start-Up Nation Central 6. Source: Start-Up Nation Central 7. Source: Smart City Council
19 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Integrated application cities
Figure 1-13: Innovation-led cities
Integrated application cities Top-level design
Application Algorithm quality breakthrough
Integration Factor quality quality Innovation ed ities are in eading Toronto Shenzhen Singapore osition severa eva ation indi ators Paris Dallas Amsterdam in ding to eve Berlin Montreal Stockholm design a gorit Sydney Dublin rea t ro g and fa tor a it
Source: Deloitte Research
Toronto Toronto’s AI industry, such as Geoffrey Lab are making concerted efforts to As one of three AI hubs implementing Hinton, are actively contributing to the gather local technical and commercial the Pan-Canadian Artificial Intelligence development of Toronto’s AI industry. talents together to drive AI innovations Strategy developed by the Canadian In respect of integration quality, two in the city. In terms of application government, Toronto is a global model world-leading academic institutions, quality, Toronto focuses on developing city in driving AI innovation. In terms of University of Toronto and University application scenarios of AI in healthcare, top-level design, the flexible and friendly of Waterloo are educating core AI finance, biopharmaceutical industry and environment makes Toronto attractive industry talents including engineers, e-commerce and building AI-powered to large numbers of AI researchers and developers, computer specialists and communities. In biopharmaceutical engineers and significantly boosts the data scientists for Toronto every year. industry, for example, Toronto’s AI growth of local AI industry compared to Besides, Mars Discovery District, one of company Cyclica successfully developed increasingly strict immigration policies the world’s largest innovation centers a new type biological big data and AI of the United States. Regarding factor located in Toronto, Vector Institute from platform that is used in developing better quality, local strong investors, incubators University of Toronto and a non-profit drugs in the pharmaceutical industry. and technical experts and leaders in organization Creative Destruction
20 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Shenzhen the first governance framework on start-ups. Regarding integration quality, Shenzhen, one high-tech center in ethical use of AI to drive companies some leading companies, such as IBM, China, has 20% of Chinese AI companies and the society to consider relevant Google, Samsung and Facebook, set up with extensive industry experience in issues. Regarding factor quality, the their AI headquarters in Paris. A number manufacturing and hardware. In terms of Singapore government released the of top labs, over 1,000 AI startups and algorithm breakthrough, Shenzhen has plan of AI.SG in recent years. According world-renowned research universities developed a world-class internet giant to the National Research Foundation including University of Paris 1 Pantheon- Tencent and a world-renowned mobile (NRF), the NRF and other public Sorbonne enable Paris to be a thriving AI device provider Huawei in the past agencies and private companies will innovation base and ecosystem. decades. Besides, a batch of AI algorithm invest SGD150 million in developing and software and hardware startups, AI industry. In respect of integration Dallas including MEGVII, YITU, SenseTime, quality, several giants including SAP and Dallas, one of model AI cities in the UBTECH and iCarbonX, set up offices Salesforce set up AI research centers to United States, is leading in the quality in the city. In fact, as a concentration of provide abundant resources for local AI of factor, integration and application. In AI talents in Southern China, Shenzhen industry. The country also has several terms of factor quality, Professor Vibhav attracts a great deal of talents from excellent industry leaders, including Gogate, one leading figure in Dallas’s AI top universities such as Sun Yat-sen scientific talents, such as Professor industry, won CAREER award granted University, South China University of Steven Hoi who released over 200 by the National Science Foundation Technology and Jinan University to research papers in top-level industry and received USD1.8 million research provide steady talent reserves for the conferences and magazines. In terms of funding9 provided by the Defense growth of all parts in local AI industrial application quality, Singapore focuses Advanced Research Projects Agency. The chain. In respect of application quality, on the AI application scenarios covering Big Data & AI Conference held in early Shenzhen is a real tech industry tycoon healthcare, transportation, finance and 2019 attracted many AI industry leaders by contributing the most of AI patents in commercial services and manufacturing to attend, including Google, Amazon, China. Shenzhen is leading in industrial to empower local economy. Oracle, IBM and Verizon. Regarding robots, civilian drones and smartphones integration quality, the University of in China while many new industries and Paris Texas at Dallas provides top AI research business formats are emerging, such as As one of the most attractive AI hubs talents and its computer science ranks smart manufacturing, smart healthcare, for investment in Europe, Paris has sixth in the world in AI and NLP sectors10 smart home and agriculture. strengths in top-level design, the quality . The university published a series of of factor and integration. In terms of research reports at the International Singapore top-level design, the release of France’s Joint Conference on Artificial Intelligence. Singapore is a typical country where the Artificial Intelligence Strategy prioritizes In respect of application quality, Dallas AI industry is developed both by public AI as France’s national strategy. And the stands out in the application of AI in and private sectors. In terms of top-level country plans to build public bodies retailing. An AI start-up Symphony Retail design, the government is actively leading and private data sharing platforms to AI, one of industry leaders in Dallas, the growth of AI industry by introducing improve the data sharing. With regard won the “Best Use of AI in Retail” award traffic regulations on autonomous driving to factor quality, the French government granted by Awards.AI, the world’s biggest vehicles in 2018 to drive investment in plans to invest EUR1.5 billion to support global annual achievement awards for the application scenario. Moreover, the research and innovation in the field8 . artificial intelligence. government of Singapore worked with Besides, the government of Paris Region the World Economic Forum in building also provides financial supports for AI
8. Le Figaro, France 9. Official website of the University of Texas at Dallas 10. Official website of the University of Texas at Dallas
21 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Amsterdam Google, Intel, Microsoft, BMW and SAP. Amsterdam is growing to be an Besides, a world renowned non-profit important AI city in Europe with a leading research institution Max Planck Institute position in algorithm breakthrough and is also located in Berlin, which owns over the quality of factor and application. 80 research institutes11 . All these equip In terms of algorithm breakthrough, Berlin with world leading strengths in Amsterdam has achieved certain basic research. Regarding integration milestones in core technical areas in quality, the cluster gathering large computational intelligence, sensing numbers of AI talents, 40.2% of German intelligence and cognitive computing. AI startups12 and research institutions Regarding factor quality, the Netherlands makes Berlin a diversified environment International Artificial Intelligence for integration and innovation. In Exhibition and International Internet respect of application quality, Berlin of Things Exhibition are the biggest AI is internationally competitive in drone industry events in Europe. The event sector. For example, German carmakers, held in the RAI International Exhibition e.g. Audi, are leading the world in the and Congress Centre in June 2018 application of AI technologies. attracted numerous world-renowned AI institutions and experts from IBM, DHL Montreal and KLM. In terms of application quality, Montreal is an emerging AI center a host of Netherlandish AI startups dubbed as the “New Silicon Valley” in AI, are established in Amsterdam mainly with a strong lead in the top-level design engaged in financial services, retailing, and the quality of factor and integration. healthcare, manufacturing, real estate, In terms of top-level design, the Quebec media and agriculture. For example, provincial government introduced the machine learning model and visual a series of incentives including tax systems that can adapt to existing incentives, favorable policies, and systems provided by the enterprise BI investment and loan incentives to attract platform Pyramid Analytics are applied many AI companies to settle into the city. by many industry clients, e.g. Siemens. Regarding factor quality, the government provides funding supports for Montreal Berlin to develop its AI industry. The Quebec Berlin is the strongest city in AI basic provincial government will invest CAD330 research in Germany with outstanding million over the next five years in AI performance in algorithm breakthrough industry, of which about CAD38 million and the quality of integration and will be used for attracting AI talents and application. In terms of algorithm CAD65 million for the application of AI13 . breakthrough, Berlin has the world’s The innovative research in AI developed largest non-profit AI research institution by Yoshua Bengio, one AI leader in German Research Center for Artificial Montreal, attracts research funding Intelligence (DKFI) whose shareholders from several high-tech giants including include global tech giants such as Facebook, Microsoft and Google.
11. Official website of Max Planck Institute 12. Handelsblatt, Germany 13. 2019 Quebec provincial budget
22 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Besides, the Conference and Workshop (IJCAI), European Conference on teams up with Dell EMC on AI and robot on Neural Information Processing Artificial Intelligence (ECAI), International application research; CAI has published Systems (NIPS), a top-level AI conference Conference on Machine Learning (ICML) over 740 papers related with AI, among with international influence was also and Nordic Business Forum, covering them, 337 articles have been published founded in Canada. In respect of machine learning, computer vision, multi- by industry leading journals15 . integration quality, some international AI entity system and NLP. giants, e.g. Google, Facebook, Samsung, Dublin set up their research centers in Montreal Sydney Dublin, the capital and the largest city where also locate many AI research Sydney is a world-renowned AI center, of Ireland, is holding a leading position institutions such as algorithm study it has made outstanding achievements in top-level design, factor quality AI labs (MILA), AI labs (IVADO), McGill in algorithm breakthrough, factor and integration quality. In the aspect University and the University of Montreal. quality and integration quality. In of top-level design, the Investment terms of algorithm breakthrough, Dr. and Development Agency (IDA) and Stockholm Ross Quinlan from Sydney University Enterprise Ireland develop an AI island Stockholm is a leading AI city in Northern invents the world’s best AI data mining plan with joint efforts, which rolls out Europe with strengths in the top-level algorithm C4.5, demonstrating Sydney’s postmaster program led by industry design and factor quality. In terms of top- advantage in data mining algorithm. As experts and relevant short-term level design, the Swedish government for factor quality, Sydney has several education courses, to increase AI talents has defined AI and machine learning as leading AI talents. For example, Tao in Ireland. In terms of factor quality, a priority area that is able to strengthen Dacheng, computer science professor Dublin’s AI industry has enough financial Swedish competitiveness and welfare. from Sydney University, is a member support. AI startups have attracted more Sweden is one of the 25 European of the American Association for the than EUR5.8 billion investment.16 On countries who signed the Declaration Advancement of Science (AAAS), which the integration quality, Dublin has built on Cooperation on Artificial Intelligence is the highest honor in computer vision, complete ecosystem for AI startups by and also one of eight Nordic and Baltic deep learning and data learning sectors. attracting tech giants such as Facebook, countries who signed the Reinforcement Besides, the Australian government also Google and Microsoft. Moreover, many of Declaration of Cooperation on allocates USD250 million to support AI tech companies are interested in setting Artificial Intelligence in Stockholm, related CRCs14 . Regarding integration their AI research centers in Dublin, including Denmark and Finland, to quality, Sydney University has established including the EUR4-million cooperation drive the growth of AI through national the UBTECH Sydney Artificial Intelligence project between Samsung and University strategies. With regard to factor quality, Centre and the University of Technology College Dublin17 and EUR17.7-million Stockholm has held several international Sydney has the Sydney Centre for project between Huawei and Trinity AI conference, including International Artificial Intelligence (CAI). UBTECH College Dublin18 . Joint Conference on Artificial Intelligence Sydney Artificial Intelligence Centre
14. Department of Industry, Innovation and Science of Australia 15. Official website of University of Technology Sydney (UTS) 16. Tech Ireland 17. Official website of University College Dublin 18. Official website of Trinity College Dublin
23 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
1.5 AI supporting technologies are method, k nearest neighbor algorithm, provides infrastructure for the advancing k-means algorithm, PCA analysis; core development of AI technologies. By 2020, The troika that driving the advance models include: linear regression, logic devices connected with IoT will increase of AI technologies, algorithm, data regression, decision tree, clustering, to 50 billion units. As a milestone in the and computing power, have been support vector machine etc. Mainstream development of telecommunication constantly innovated in the past 5 to algorithm model base enables highly technologies, 5G will be able to provide 10 years. In terms of algorithm, human efficient realization of frequent algorithm up to 1Gbps transmission speed. beings have made breakthroughs in models: Tensor Flow framework, Caffe machine learning algorithm, especially framework, CNTK framework collect and Thanks to improvement in the the achievement in vision and voice integrate data for different algorithm processing capability of chips and technologies. As for data, the coming of models, they are very practical for the decline of hardware prices, mobile internet era enables explosive algorithm development and application. computing power has been greatly growth of data volume. With constant advance in big data improved. So far, most AI computing technology, the cost to gain flag data that are executed on GPU chips. However, After long-term development, AI- AI requires for learning was reduced and with technology iteration, cell categories based algorithm models have been the speed to process data significantly including ASIC and FPGA will become applied in several sub-sectors. Taking improves. The efficiency of broadband underlying technologies to support the machine learning as an example, its also improves. Constant iteration of IoT development of AI technologies. core algorithms include: least square and telecommunication technologies
24 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Figure 1-14: Forecast on the size and growth of China’s AI chip market (2016-2020)
80 75.1 80%
70 70% 56.1 60 60%
50 45.6 50%
40 40% 33.3 30 30% 19 20 20%
10 10%
0 0% 2016 2017 2018 2019E 2020E
Size of AI chip market (100 million yuan) Growth rate
Source: Qianzhan Industry Research Institute, Deloitte Research
Figure 1-15: Classification of AI chips
Advantages Disadvantages
Only a small amount of hardware resources can be Unable to process massive data; applied in control points and most hardware resources GPU Should be based on instruction system; can be used as Arithmetic Logic Unit (ALU), which High power consumption; decoding is needed creates conditions for large-scale data processing
Don’t need instruction and decoding; Customization is needed; ASIC Focus on data processing or transmission Limited functions
Speed and power consumption are superior than general CPUs; Require function DIY; FPGA Programmable and iterateable (through fast trail-and- Programming languages are inconsistent error)
Source: public information, Deloitte Research
25 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
1.6 Growing support from top-level policies Considering the growing impact of AI on social and economic development, many governments have released favorable policies to include AI into national strategies. So far, state-level AI policies have been issued in many countries and regions including the US, China and the European Union.
Figure 1-16: AI policies released by different countries
Robot Plan “BRAIN” Plan AI & Machine XAI Preparing for the Artificial American AI learning Future of Artificial Intelligence, Initiative The US The US committee Defence Intelligence and Automation,
government 4 government 5 8 Advanced 0 2 2 White House
0 0 0 1 National Artificial 1 and the 0 3 ......
1 White House 3 6 6 Research 6 Intelligence 6 9
0 Economy 1 1 1 1 1 1 2 0 0 0 Projects 0 Research 0 0 2 2 2 2 2 White House 2 Agency Development Strategic Plan White House
Future and Industry Human “SPARC” Robot and French Growing the Artificial Ethics Emerging 4.0 Brain Plan Plan Artificial Intelligence Artificial Intelligence Guidelines for Technologies Intelligence Artificielle Intelligence for Europe Trustworthy AI 4 Germany 1 Germany 6 0 3 0 4 0 0 0 1 0 1 0
9 2 EU . . . . . Industry . 0 1 3 4 6 7 7 8 9 . EU 0 EU 0 France EU 1 1 1 1 1 1 UK in the UK 1 2 2 0 0 0 0 0 0 0 2 2 2 2 2 2 2 UK
Made in Robot Industry Report on Three-Year College Artificial Work Plan Report on the Work China 2025 development the Work Action Intelligence for of the Government Planning of the Plan on Innovative Action Completing (2019) 4 5 3 2 1 3 1 0 12 0 0 1 State 0 . . . . . (2016-2020) Government Promoting the Plan Key . 8 6 5 7 7 7 . Implement national
Council 1 1 1 1 1 1 (2017) Development Build multilevel Innovation 1 9 0 0 0 0 0 0 0 AI-education project, 2 2 2 2 2 2 Ministry of Tasks of 2 of New AI education introduce AI-related Industry and State Council New Generation system. Introduce courses into primary Information AI Industry universal education Generation Technology and secondary MIIT of AI into primary AI Industry (MIIT), National education, gradually and secondary promote Development schools. MIIT and Reform programming Commission Ministry of Education education (NDRC), MOF State Council
Source: Annual Government Work Report, Public information, Deloitte Research
26 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
In 2019, the Chinese government still 2015, China has published a series To promote the application of AI provide support for the development of favorable policies, providing great technologies, the Chinese government of AI via some national departments, financial, talent and innovation support have applied homemade AI-based including MOST, NDRC, National for AI industry. These policies are also products into several smart city and Internet information office, MIIT and positive signals for the capital market as smart government programs. Chinese Academy of Engineering. Since well as industry interest stakeholders.
Figure 1-17: China's national AI development policies
Made in China 2025 2015.5 Develop intelligent equipment, intelligent products and intelligent production
13th Five-Year Plan for Economic 2016.3 Include AI development into the 13th Five-Year Plan and Social Development of the People’s Republic of China
Robot Industry Development 2016.4 By 2020, increase the output of self-developed industrial robots to Planning (2016-2020) 100,000 units, among them, over 50,000 have 6 or more axles
13th Five-Year Plan for National 2016.7 Focus on developing big data-driven quasi-AI technologies Technological Innovation
Special Campaign on Advancing 2016.9 Prioritize the research of wearable devices, intelligent on-board Innovative Development of equipment, intelligent healthcare equipment, intelligent service Intelligent Hardware Industry robots, industrial grade intelligent hardware equipment etc. (2016-2018)
13th Five-Year Plan on Developing 2017.3 Come up with the concept of AI 2.0; include AI into national strategies; Emerging Sectors of Strategic mention AI into government work report for the first time Importance
Notice on New Generation of 2017.7 Establish a new education system that include intelligent learning Artificial Intelligence Development and interactive learning; promote the application of AI technologies Plan in teaching, management and resource construction; promote AI courses in elementary and secondary schools; higher institutions encourage more students to pursue “AI+x" master/doctor's degrees; and build more intelligent and interactive education platforms
19th CPC Congress report 2017.10 Include AI into the report to promote deep integration of Internet, big data and AI with the real economy
Three-Year Action Plan on 2017.12 To refine and implement tasks outline in the plan; focus on the Promoting the Development of industrialization and integrated application of new generation AI New Generation AI Industry (2018- technologies; and promote deep integration of AI and the real 2020) economy
27 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
2.0 Action Plan on Promoting IT- 2018.4 Energetically advance intelligent education, create student- based Education centered intelligent teaching environment, promote the application of AI technologies in teaching and management, expedite the reform of talent cultivation model and teaching method with AI technologies, and explore ubiquitous, flexible and intelligent teaching environment and application models
Modernization of Chinese 2019.1 Innovate education service formats, co-construct and Education Industry 2035 share digital education resource mechanism, improve interest allocation mechanism, IPR protection system and new education service regulation rules. Drive the reform of education governance approaches, accelerate to build modernized education management and monitoring system, and realize precise management and scientific decision- making.
Source: public information, Deloitte Research
From the perspective of strategy, New Generation of Artificial Intelligence Development Plan is the first document on systemic deployment of AI technologies in China. It specifies the general idea, strategic goals and tasks and safeguard measures for China’s AI development till 2030. The plan clarifies the requirements on underlying technologies, AI technologies as well as AI application, and proposes three development stages (2020, 2025 and 2030) according to the development situation of AI technologies in China.
28 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Figure 1-18: Three stages of AI development proposed by national strategic planning
By 2030, China will develop world-class AI theories, By 2025, China will make technologies and applications, By 2020, China will significant breakthroughs in AI and become a major AI keep up with leading AI basic theories and develop innovation center across the technologies and world-class AI technologies world applications and applications 12
10 10
8
6 5
4
2 1 1 0.15 0.4 0 2020 2025 2030 Target size of AI market Target size of other AI related markets
Source: the State Council, Deloitte Research
Regarding local policy, many Sichuan set the top five targets). To Measures on Promoting Innovative local governments have made greatly promote the implementation Development of Intelligent Robot AI development plans based on and development, cities represented Industry in Zhongguancun and their actual situations. 19 out 31 by Beijing, Shanghai, Guangdong Guiding Opinions on Accelerating provinces/municipalities have and Shenzhen made effective the Development of AI Industry to issued AI planning, among them, policies, becoming major players accelerate the construction of AI 16 provinces/municipalities have and leaders in Chinese AI industry. industry. Beijing has set a target set industry size targets (Shanghai, For example, Beijing has published higher than other Chinese cities Beijing, Zhejiang, Guangdong and several measures such as Several according to national AI strategies.
29 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Figure 1-19: AI development policies issued by local governments
Province/ Policies Municipality
Several Measures of Zhongguancun on Promoting Innovative Development of Intelligent Robot Industry Beijing Guiding Opinions of Beijing Municipality on Accelerating Scientific and Innovative Development of AI Industry AI Industry Development Action Plan of Zhongguancun National Independent Innovation Demonstration Zone
Implementation Measures on Accelerating High-Quality AI Development Implementation Opinions of Shanghai Municipality on Promoting the Development of New Generation AI Industry Shanghai Outline of the Plan of Shanghai Municipality on Integrating AI into Urban Appearance Improvement Campaign Implementation Details of Shanghai Municipality on Providing Special Support for AI Innovation and Development
New Generation AI Industry Development Plan of Guangdong Province Action Plan of Guangdong Province on Guangdong Advancing big data development (2016-2020)
Zhejiang New Generation AI Industry Development Plan of Zhejiang Province
New Generation AI Industry Development Plan of Anhui Province Anhui Development Plan of China (Hefei) Intelligent Speech and AI Industry Base (China Speech Valley) (2018-2025)
Guangxi Implementation Opinions on Implementing the Development Plan of Promoting New Generation AI Industry
AI Development Plan of Heilongjiang Province Heilongjiang New Generation AI Industry Development Plan of Shenyang Municipality
Sichuan Notice on the New Generation AI Industry Implementation Plan of Sichuan Province
Three-Year Action Plan of Tianjin Municipality on the Development of New Generation AI Industry Tianjin Overall Action Plan of Tianjin Municipality on Advancing the Development of AI Technologies Action Plan of Tianjin Municipality on Promoting Precise AI Innovation in 7 Major Industrial Chains
Henan Three-Year Action Plan of Henan Province on the Development of Intelligent Manufacturing and Industrial Internet
Hebei Three-Year Action Plan of Hebei Province on the Development of Emerging Industries of Strategic Importance
Guizhou Smart Guizhou Development Plan (2017-2020)
Several Measures of Changsha Municipality on Accelerating the Development of New Generation AI Industry and Hunan Promoting the Construction of National Intelligent Manufacturing Center
Hubei 13th Five-Year Plan of Hubei Province on Scientific and Technological Innovation
Fujian Implementation Opinions on Accelerating the Development of New Generation AI Industry
Jiangsu Smart Jiangsu Construction Action Plan (2018-2020)
Jiangxi Several Measures on Accelerating the Development of AI and Intelligent Manufacturing
Source: public information, Deloitte Research
30 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
For instance, Shanghai is improving Implementation Measures of Shanghai cluster, government capital attraction and refining AI development strategies Municipality on Accelerating High- and support. These new rules can and policies in order to build a national quality AI Development in September be combined with existing AI policies AI development highland. Following 2018. The measures include 22 to effectively use various capital, the Implementation Opinions on detailed rules, covering AI talent projects and service resources and Advancing the Development of New cultivation, data and resource sharing create broad development space for Generation AI, Shanghai published the and application, industry layout and Shanghai’s AI industry.
Figure 1-20: Development plan of AI applications in Shanghai
Baoshan District Yangpu District
Intelligent hardware Chongming District Intelligent education Intelligent recognition
Xuhui District Putuo District Intelligent healthcare Intelligent security Intelligent chip design Intelligent hardware Intelligent security Baoshan Jiading District Changning District District I Minhang District G H Intelligent recognition F Intelligent recognition E A Intelligent retail Qingpu D B Intelligent healthcare District C Pudong Pudong New Area New Area Minhang Intelligent chip design Songjiang District District Intelligent healthcare Songjiang Intelligent speech recognition District Intelligent manufacturing Intelligent chip design Fengxian Intelligent security District Jinshan District
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: Shanghai Municipal Economy and Information Technology Commission, Deloitte Research
31 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
After the launching of the science such as Montage Technology, a star big data. Moreover, Shanghai municipal and technology innovation board AI company in chip service sector. government also provide support for in Shanghai on 13 June 2019, the In terms of investing institution, a series of companies specialized in integration of investment and industries Shanghai has many well-capitalized AI innovation. Most of these startups will be further enhanced, providing and influential financial companies. In successfully expand and even gain tens financial support for AI innovation. As of terms of investment project, Shanghai of millions of financing for advanced 5 July, 25 companies have successfully has established incubation parks for technologies and high business value, registered for the sci-tech board, five of AI innovation star-ups engaged in hot which are be very likely to apply for them are Shanghai-based enterprises areas such as healthcare, education and listing on the sci-tech board.
Figure 1-21: Distribution of Shanghai-based AI innovation companies
Jiading District Putuo District
Songhong—vehicle R&D Chongming District Ferlytech—intelligent corporate service Hesai Tech—laser radar Celepixel—sensor system Shanghai Internet of Things Co., Ltd.—IoT Yangpu District Roadefend—machine vision Minhang District UCloud—cloud service ReadSense—machine vision Baoshan Jiading Flexiv—robot system District Jing’an District District I G H CHYETH—education F E A Zamplus—big data service Changning District Qingpu D B Westwell—intelligent port District C DeepBlue—intelligent service Pudong Xuhui District system Minhang New Area Telepathcloud.com—cloud diagnosis District — Songjiang United Image IT-based healthcare District Leyan Technologies—intelligent Jinshan District Fengxian customer service — Winner intelligent business District Laiye.com—intelligent service robot Jinshan District Fengxian District Pudong New Area Zhicheauto—intelligent vehicle Fourier—rehabilitation robot Horizon Robotics—intelligent chip Qiniu—cloud service Cloudwalk—face recognition Wind—financial big data Tunicorn Technology—machine vision Cambrian—intelligent chip
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: Shanghai Municipal Economy and Information Technology Commission, Deloitte Research
In summary, AI industry is flourishing in many places of China. Provinces and municipalities respond actively after the release of national AI development plan. Due to technology, talent and industry advantages, first-tier cities have become hot areas of AI industry development in China and will promote the development of AI industry in surrounding areas.
32 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
1.7 Over USD 6 trillion global AI services, new markets and more concerning national strategic practices market employment opportunities. Increasingly and business activities. The global AI AI will improve social productivity and aware of the importance of AI at market is likely to see phenomenal bring disruptive changes to people's the economic and strategic levels, growth and achieve a market value of production and life including lower governments and businesses across over USD6 trillion by 2025 and a CAGR labor cost, better products and the world are investing in AI application of 30% from 2017 to 2025.
Figure 1-22: Global AI market size
USD trillion
7.00 6.40
5.73 6.00
5.00 4.48
4.00 3.50 3.04
3.00 2.43 1.90 2.00 1.18 0.69 1.00
0.00 2017 2018 2019E 2020E 2021E 2022E 2023E 2024E 2025E
Source: Deloitte Research
33 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Traditional industries with large market 2030, respectively accounting for 16%, factories and smart logistics. As AI size will maintain their leadership. 16% and 14% of the market share. application in education is expanding Manufacturing, telecommunications, Manufacturing is the fastest-growing across the whole learning process, media and service, and natural industry, with large manufacturers growth in this sector should not be resources and materials are expected accelerating their digital transformation underestimated. to be ranked among the top three in to realize smart management, smart
Figure 1-23: AI market size (by industry)
USD10 billion 90
80
70
60
50
40
30
20
10
0 2018 2019 2020 2021 2022 2023 2024 2025
Manufacturing Telecommunications, Natural resources Consumer products Healthcare Banking media and service and materials
Transportation Automobile Trade Retail Energy Life sciences
Government IT hardware Education Insurance Public utilities
Source: Gartner
34 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
China's AI industry has reached a Shanghai, Shanghai has embraced of all parties including governments market size of over RMB100 billion. This rapid development of AI industry, and companies about the future of the figure is expected to rise to RMB160 which is likely to achieve a market size technology, AI will undoubtedly become billion by 2020, and is likely to stimulate of RMB120 billion in 2019. Based on an important driver for economic more than RMB1 trillion value in other geographical advantages of Yangtze development. AI-related industries.19 The scale of River Delta, Shanghai's AI companies artificial intelligence related industries have access to sufficient quality talent Local governments are publishing in Beijing, Shanghai, Zhejiang, Jiangsu and capital resources. Significant guidance on AI-related industry and Guangdong is in the forefront of enterprise cluster effect will drive the planning, aiming to promote industrial all provinces and municipalities, and is increase of company and industrial size. upgrading and change of economic expected to reach 140 billion, 130 billion, growth drivers. They take active 270 billion, 100 billion and 280 billion 1.8 Large number of AI companies measures to create a desirable business respectively in 2020. located in the Beijing-Tianjin-Hebei environment by providing preferential Region, Yangtze River Delta and tax policies and subsidies, brain gain Since the issuance of the Pearl River Delta and optimizing government affairs Implementation Opinions on AI technology has extended across system, with the purpose to attract well- Promoting the Development of a New various industries for business positioned enterprises and develop local Generation of Artificial Intelligence in application. With general confidence AI companies.
Figure 1-24: Distribution of AI companies in China
1,400
1,200
1,000
800
600
400
200
0 Beijing Shanghai Guangdong Zhejiang Jiangsu Anhui Fujian Shaanxi Sichuan
Source: Publically available information, Deloitte Research
19. Speech of the Ministry of Industry and Information Technology of PRC on "World Telecommunication and Information Society" Day in 2018
35 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Driven by policies and capital, AI in western China are also the hubs Beijing, Shanghai, Shenzhen and companies see a rapid growth in for AI companies, as many traditional Hangzhou are tier-one cities attracting number. According to incomplete manufacturers in the region need to the most AI companies, with more than statistics, there are over 4,00020 leverage AI technology for intelligent 600 in each of them. AI companies across China, mostly transformation. Government's incentive located in the Beijing-Tianjin-Hebei policies are also attracting AI companies Region, Yangtze River Delta and Pearl to the region. River Delta. Sichuan and Chongqing
Figure 1-25: Distribution of key AI companies in Shanghai
Jiading District Chongming District Yangpu District 37 companies, account for 7% 43 companies, account for 8%
Huangpu District Jing'an District 38 companies, account for 7% Baoshan 43 companies, account for 8% Jiading District District I G H F E A Changning District Qingpu D B Xuhui District District C 69 companies, account for 13% 24 companies, account for 4% Pudong Minhang New Area District Songjiang District Minhang District Fengxian Pudong District 46 companies, account for 9% District 145 companies, account for27% Jinshan District
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: ASKCI Consulting, Deloitte Research
20. China AI Development Report2018, Tsinghua University
36 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Investment and funds raised: AI startups in Beijing and Shanghai rank the top in investment and funds raised An active capital environment can improve a city's competitiveness in AI industry, as it is favorable for AI startups to improve technologies, attract users and develop markets, and may facilitate connection between up-stream and down-stream players across the AI industrial chain to trigger scale effect.
Figure 1-26: Funds raised by AI startups in different cities (2015-1H 2019)
(RMB100 million)
1,800
1,600
1,400
1,200
1,000
800
600
400
200
0 Beijing Shanghai Shenzhen Hangzhou Guangzhou Nanjing Suzhou
Source: ITJUZI.COM, Deloitte Research
As startups are pioneers in the of RMB159.9 billion and RMB58.2 Universities, colleges and other research and development as well billion. Most AI startups with strong research organizations are important as business application of new technical capabilities in China are platforms for the research and technologies, the amount of capital located in Beijing and Shanghai, where development of AI technology. China raised by this group indicates the customers are more willing to use new has surpassed the US in the number of prospect of new technologies in the technologies. Therefore, there are AI research papers since 2014, leading region. AI technology has been applied more opportunities for AI application far ahead of other countries. It is in a wide range of sectors including in the two cities. closely related to the fast development finance, transportation, healthcare and of universities, colleges and other manufacturing for business purpose. Variance in the number of organizations engaged in AI research, Funds raised by startups will provide universities, colleges and which are also major applicants for financial support for the application of other research organizations: AI patents. Thus, analysis of these AI in more industries. Beijing is strongly competitive, organizations will provide insights into while Shanghai mainly relies the technological competitiveness of Since 2015, AI startups in Beijing and on universities and colleges, related cities. Shanghai have respectively raised Shenzhen on companies and more than RMB50 billion, with a record Hangzhou on limited platforms
37 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Figure 1-27: Characteristics of different cities by universities, colleges and other organizations engaged in AI research
Governmental or Universities and research institutes and Characteristics Corporate labs colleges labs of universities and colleges
• Most competitive in AI More than 50%: More than 10: • 360 research • Tsinghua University • National Laboratory of • Baidu • Peking University Pattern Recognition • Xiaomi • Beihang University • CSAI • Meituan • Institute of Automation, • National Engineering • JD.com Laboratory for Deep Chinese Academy of • Sinovation Ventures Learning Technology Beijing Sciences and Applications • Toutiao • Institute for Artificial • Lenovo Intelligence, Tsinghua • UBTECH University • Peking University Law Artificial Intelligence Laboratory
• Mainly relying on Many universities and • SJTU-Versa Computer • SAIC Motor universities, and colleges: Science and AI Joint Lab • Philips colleges, with corporate • Shanghai Jiao Tong • AI adaptive education • SenseTime Shanghai research institutes/ University lab jointly established labs (although less than • Tencent • Fudan University by Chinese Academy of Beijing) laying academic Sciences and Squirrel AI • Squirrel AI • Tongji University foundation • Microsoft
• Mainly relying on • Shenzhen University Mainly led by the • Tencent corporates • Southern University of government: • Huawei Science and Technology • Shenzhen Academy of • ZTE henzhen Robotics • Shenzhen Institute of Artificial Intelligence and Big Data
• With gap from Beijing, • Zhejiang University • Alibaba Hangzhou Shanghai and Shenzhen • NetEase • Geely Auto
Source: Publically available information, Deloitte Research
38 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
These four cities have different efforts to improve the city's technological Brain-like Chips and Intelligent Systems characteristics in universities and competitiveness, as evidenced by the on Chips, International Innovation colleges and other institutes engaged establishment of Shenzhen Academy Center for Brain and Brain-like in AI research. Beijing is the most of Robotics and Shenzhen Institute Intelligence and Center for Cognitive completive in AI research, with over of Artificial Intelligence and Big Data. Machines and Computational Health 50% of China's research universities Hangzhou lags behind Beijing, Shanghai of Shanghai Jiao Tong University. and colleges and more than 10 national and Shenzhen in the number of Shanghai is also considered as a hub labs. Internet giants located in Beijing universities and colleges, university and of AI-related research, education and such as Baidu, JD.com and Meituan college labs and corporate labs, mainly production, attracting tech giants such are establishing corporate labs, relying on giant Alibaba in AI research. as Alibaba, Tencent, SenseTime, MEGVII, investing large amount of capital in AI Microsoft and Amazon to locate their research and development. Shanghai Shanghai has obtained a leading AI R&D bases in the city and establish is ranked among the top nationwide position nationwide in the establishment joint labs with local universities and in AI development, based on leading of research and technical platforms. colleges. These joint labs will enhance universities including Fudan University, Many AI function platforms have been the cooperation between businesses Tongji University and Shanghai Jiao established in Shanghai, including and academic community in AI research, Tong University. As a hub of many tech Shanghai Research Institute for providing strong intelligent support enterprises such as Tencent, Huawei Intelligent Autonomous Systems, for the development of Shanghai's AI and ZTE, Shenzhen is a key player in AI Collaborative Innovation Center for Brain industry. research and development. Meanwhile, Science of Fudan University, Platform the local government is also making for the Research and Development of
39 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Figure 1-28: Distribution of AI research centers in Shanghai
Chongming District
Platform for the Research and Development of Brain-
Shanghai Research Institute Baoshan like Chips and Intelligent for Intelligent Autonomous Jiading District Systems on Chips District Systems I G H F International Innovation E A Qingpu D B C Center for Brain and Brain- Collaborative Innovation District like Intelligence Center for Brain Science of Pudong Minhang New Area Fudan University District Center for Cognitive Songjiang Machines and District Fengxian Computational Health District of Shanghai Jiao Tong Jinshan University District
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: Publically available information, Deloitte Research
Figure 1-29: AI giants' research centers in Shanghai
Company name Cooperation
Alibaba AI Innovation Center
Tencent Tencent Computer Vision Research Center and head office of Eastern China
Amazon AWS AI Research Institute (Shanghai)
Microsoft Microsoft Research Asia (Shanghai)
iFLYTEK iFLYTEK Shanghai Institute of Artificial Intelligence and Brain Science
SenseTime Global R&D Headquarters with an investment of RMB6 billion
MEGVII Joint lab with ShanghaiTech University
Yixue Education—Squirrel AI Artificial intelligence self-adaptive learning Institution
Source: Deloitte Research
40 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
AI talent resources: concentrated in Pearl River Delta. Central and western is about twice as much as that of the economically developed regions regions of China, in particular the second-place city Shanghai (12.1%). AI competition comes down to talent area along Yangtze River, have also Shenzhen and Hangzhou are ranked competition. AI talent resources are attracted many AI talents. Beijing takes among the tier-two with a percentage of unevenly distributed in China, mainly the first place among all Chinese cities less than 10%. concentrated in the Beijing-Tianjin- in the percentage of AI talents, with a Hebei Region, Yangtze River Delta and prominent figure of nearly 28%, which
Figure 1-30: AI talent percentage of different cities
30.0% 27.9%
25.0%
20.0%
15.0% 12.1% 10.0% 8.5% 6.5% 5.0%
0.0% Beijing Shanghai Shenzhen Hangzhou
Source: Global AI Talent White Paper, Report on China's AI Development 2018, Tencent, Deloitte Research
Note: The color indicates the number of AI talents in each province or city; the darker the color, the more AI talents there are. The bar chart illustrates AI talent percentage=number of AI talents in each city/total number of AI talents in China.
41 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Domestic universities and colleges as well as research institutes are the major incubators of AI talents. First-tier cities such as Shanghai have significant advantages in developing AI industry, with a large number of high-quality research and educational platforms. Over 75% of AI talents in China are from local universities and colleges. With strong research capabilities, Tsinghua University, Shanghai Jiao Tong University and Zhejiang University are the major sources of AI talents.
Figure 1-31: Percentage of AI papers published in international journals across different universities
Tsing Hua University
Shanghai Jiao Tong A University
Zhejiang University
Harbin Institute of Technology
Bei Hang University
Peking University
Wuhan University Huazhong University of Science and Technology Beijing Institute of Technology
Nanjing University
0.00% 0.50% 1.00% 1.50% 2.00% 2.50% 3.00% 3.50% 4.00% 4.50%
Source: Report on the Development of Next-generation Artificial Intelligence Industry in China 2019, Deloitte Research
42 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
Intelligent city management: city framework. This approach will have generally realized resources significantly influenced by policies drive data integration among different sharing and collaboration among with Shenzhen, Shanghai and sectors to provide data support for departments and have established Hangzhou taking the lead intelligent city management. Shenzhen, online-approving systems. Beijing's Integration of information technology Shanghai and Hangzhou stand out low ranking is attributed to more into government affairs system in intelligent city management, as considerations of the government in is widely applied to improve city governments of these cities are early intelligent city management. management efficiency under a smart information technology adopters that
Figure 1-32: Rankings of cities by intelligent city management
1
2 3 4
Shenzhen Shanghai Hangzhou Beijing
Source: Super Smart City, Deloitte Research
43 Global artificial intelligence industry whitepaper | 1. New trends of AI innovation and integration
44 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
2. Development of AI technologies
2.1 Increasingly sophisticated AI adaptive technology have made great applied most extensively in China, with technologies strides over the last decade. According each accounting for 34.9%, 24.8% and AI technologies including machine the data of Tsinghua University, 21% of AI application in the market. learning, natural language processing, computer vision, speech processing computer vision and intelligent and natural language processing are
Figure 2-1: Ranking of AI technologies by popularity
Autonomous Speech Expert Intelligent adaptive Machine Driving recognition system learning vision
2012
2013
2014
2015
2016
2017
2018
2019H1
Source: Baidu Index, Deloitte Research
The implementation of autonomous computing equipment such as GPUs has five core capabilities including and unmanned systems is around and computing frameworks including obstacle perception, decision making the corner: With the development of Caffe, Theano and Tensor Flow can and planning, cloud simulation, high- AI and machine learning, self-driving support designers and engineers to precision map service and end-to-end cars, drones and medical robots establish innovative autonomous and deep learning. Horizon Robotics has have achieved significant progress, unmanned systems. Intelligent bicycle launched deep learning processor IPs mainly attributed to autonomous systems developed by Alibaba AI Labs and platforms for self-driving sector. and unmanned system algorithm. can provide round-the-clock centimeter- As for industrial application, Westwell Deep learning proves to be able level positioning which applies to all has taken some initiatives in exploring to handle complex tasks. Modern scenarios. Baidu's self-driving technology unmanned cargo.
45 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
Speech recognition technology Intelligent adaptive learning Computer vision technology is becomes a "must win" for giants: technology is increasingly developing fast: Computer vision Speech recognition enables machines to sophisticated: As one of the most is a machine vision technology to automatically recognize and understand disruptive technologies in education identify, track and measure objects with human language and convert to texts industry, intelligent adaptive learning computers instead of human eyes. It and instructions, using signal processing enables learning systems to provide has been applied in a wide range of and recognition technologies. Relevant personalized education, by simulating scenarios including smart home, audio- application scenarios include smart TV, one-to-one education scenarios. visual interaction, augmented reality, intelligent vehicle information systems, Compared with the traditional teaching virtual reality, image search for products call centers, voice assistants, intelligent model designed for all students, on e-commerce platforms, tag search, mobile terminals and smart appliances. intelligent adaptive learning system beauty effects, intelligent security, Major platforms such as Baidu, iFLYTEK brings personalized learning experience livestream regulation, video platform and Sogou have achieved an accuracy to students, improving their involvement marketing and three-dimensional of over 97% in speech recognition. and efficiency in learning. Intelligent analysis. Significant progress has been Meanwhile, emerging tech companies adaptive learning technology has been achieved in the application of computer including Unisound are also playing used in the US and Europe for more vison in these scenarios. This filed prominent roles in speech recognition than ten years, with over 100 million has attracted active investment from sector. iFLYTEK's deep fully convolutional users across different ages. Both tech giants and unicorn companies, neural network-based speech product and technology have evolved represented by Baidu, Tencent, recognition framework possesses to an advanced level in these regions. Hikvision, Tsinghua University, Chinese an accuracy rate of 98% in input China, however, is still at the initial stage Academy of Sciences and other business recognition. Sogou's speech recognition in the application of intelligent adaptive and research organizations. PyramidBox technology is able to support a highest learning technology, lagging behind of Baidu is a deep learning-based face dictation rate of 400 words per second. in data accumulated. Despite of such detector; Hikvision proposes to predict Alibaba AI Labs has developed AI- situation, China is likely to catch up human body central axis rather than based shopping products with speaker from behind, based on large population labelling frame against the dim target recognition function. and rapid development. Intelligent problem in pedestrian detection. adaptive learning companies in China Tencent Youtu and the Chinese represented by Yixue Education— University of Hong Kong jointly launched Squirrel AI have been applying a wide PANet at CVPR2018, which aggregates range of technologies such as Bayesian low-level and high-level features network, Deep Neural Network based on Mask R-CNN and integrates Evolutionary algorithms, Transfer the feature grids obtained from learning, and the other machine learning sampling candidate areas on multiple algorithms. feature levels by ROI Align to support subsequent prediction. Innovative companies such as CloudWalk Technology, DeepBlue Technology and Qiniu are leading in computer vision technology.
46 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
2.2 Steady progress of open AI Technologically leading AI companies technologies such as image recognition, platform establishment are establishing their open AI platforms, natural language processing, speech A wide range of industries and broad aiming to make better use of tech recognition, system recommendation solution market provide significant advantages to drive business growth and predictive analysis. advantages for China's AI development. and facilitate the development of AI In addition to the support from large industry. Open AI platforms intend to support volumes of search data, considerable the establishment of an AI industrial product lines and extensive industries, AI platforms provide tools for AI chain which expands technology the efforts of overseas and domestic application development. These innovation from the source to the whole tech giants in promoting open source tools enable developers to create industry. Open platforms connect two tech communities have helped business solutions through platforms, ends of the industrial chain, building startups break technology barriers and combining intelligence, decision-making a bridge between developers and apply AI directly in the research and algorithms and data. Some AI platforms research institutions and enhancing development of end-user products. AI provide solutions to basic application the connection between downstream technologies have been used in various development, based on Platform as a companies with other organizations vertical sectors including medical care, Service (PaaS) function enabled by pre- across the industrial chain. For example, health, finance, education and security. set algorithms and simple frameworks, an open AI platform mainly designed while other platforms leave developers for image recognition can share related As business application of AI to complete application development technologies with startups that seek to technologies is accelerating, tech and programming by themselves. develop business in this field. giants and emerging AI startups have These algorithms can provide obtained their technology advantages. functional support for machine learning
Figure 2-2: Open technology and application platforms developed by Chinese and foreign companies
Related fields of the open platforms China Overseas
Autonomous driving Baidu Autonomous Driving NVIDIA DRIVE Platform
Smart city Alibaba City Brain IBM Watson, Microsoft Citynex
Intelligent healthcare Tencent Medical Imaging IBM Watson
Microsoft Azure Cognitive, Google Cloud ML Intelligent speech iFLYTEK Intelligent Speech Service, IBM Watson
Amazon Rekognition, Google Cloud Services, Intelligent vision SenseTime Intelligent Vision IBM Visual Recognition
Smart education Squirrel AI Intelligent Adaptive Leaning Knewton
Smart retail JDAI Google Cloud for Retail
Source: Corporate websites, Deloitte Research
47 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
The Ministry of Science and Technology Baidu's open platform Apollo has The open platform is mainly and other government bodies established alliances with over applied in a city's traffic sector for announced the first new-generation 120 organizations across the the establishment of unified data open AI platforms at the national level industrial chain, including OEMs, integration engines, traffic prediction after full research and surveys in 2017. parts manufacturers, travel service systems, mass data integration control The four platforms for self-driving, city providers, startups, telecom engines and general traffic condition brain, medical imaging and intelligent companies, universities and colleges, detecting systems. The platform speech were established with the and local governments. King Long has provided more than 1,000 support of Baidu, Alibaba Cloud, Tencent Motor, BMW and Daimler are engaged cloud servers for local governments and iFLYTEK. The Ministry of Science in cooperation with Apollo. In addition, of Hangzhou, Quzhou, Shanghai, and Technology established the first Apollo has been used for commercial Jiaxing, Macau and Kuala Lumpur, open AI platforms for intelligent vision operation in Xiongan New Area of etc. to support real-time analysis and at the national level with the help of Beijing, Shenzhen, Pingtan County of processing of mass multi-channel SenseTime in September 2018. Multiple Fujian, Wuhan of Hubei and Kyoto of video data. City brain algorithm teams areas including education, retail and Japan, etc. provide public security, traffic and government affairs have established municipal administration organizations ••Open and innovative city brain open application platforms driven by with algorithms in image detection, platform core technologies: identification and segmentation, AI-based national open city brain etc. Take Hangzhou's city brain as ••National open autonomous platform has been established with the an example, Enjoyor and SUPCON driving platform support of Alibaba Cloud. Modelled cooperate to calculate panoramic National open autonomous driving after city brain systems, this platform data of videos, coils, microwave and platform provides open, complete provides open ecosystems with internet timely, integrating the traffic and safe hardware and software diverse elements for AI application management and control experience as well as services for developers in city security governance, public of traffic police with the traffic light to support their establishment of services and other sectors, supporting timing strategy of city brain. Practices comprehensive autonomous driving the innovative application of new- in Hangzhou's urban area, Xiaoshan systems, based on Baidu Apollo. In generation AI technologies in different District and Yuhang District have August 2019, Baidu's Apollo self- areas of an intelligent society. achieved favorable results. driving cars demonstrated how L3 and Algorithm system platforms can L4 models run in high-speed driving optimize large-scale vision computing scenarios under cooperative vehicle- platforms; round-the-clock and full- infrastructure system (CVIS) for the coverage automatic traffic patrol alarm first time in China, through road testing systems can detect all traffic accidents in Changsha. Up to this point, Baidu in the city in a real-time manner, had finished over 2 million kilometers presenting an accuracy rate of over L4 autonomous driving test on urban 95%; traffic prediction systems can roads. predict smooth flow of traffic across the city timely and accurately, based on historical and real-time video data.
48 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
••Open and innovative medical ••Open and innovative intelligent ••Open and innovative intelligent imaging platform speech platform vision platform Tencent Miying, an AI medical imaging National open intelligent speech National open intelligent vision platform, has been applied in the platform is set up mainly based on platform is established based diagnosis of multiple diseases, from iFLYTEK's speech platform technology. on SenseTime's vison platform early diagnosis of esophageal cancer Related AI research and data centers technologies. SenseTime's open to the diagnosis of lung cancer, have been established. As of late intelligent vision platform is committed diabetic retinopathy, breast cancer, October 2018, a complete AI industrial to the research and development of colorectal cancer and cervical cancer, chain covering technology research, core technologies related to intelligent etc. AI diagnosis platform is able to basic platforms, IoT and intelligent vision tool chain, fundamental assist doctors in the diagnosis and hardware, etc. had taken shape, intelligent vision technology prediction of more than 700 diseases with over 860,000 teams engaged breakthrough and establishment of and has been used in 90% high- in platform development and more an international intelligent vision talent frequency diagnosis of the outpatient than 200 companies participating in system, with the aim to drive China's service. the platform. Six intelligent speech development of AI application in vision related national standards have been sector. SenseTime's core technologies Tencent has established an open approved and released, as a part include face detection and tracking, and innovative medical imaging of proprietary intellectual property facial feature points localization, facial platform, which integrates participants rights and standards system for the authentication and scene recognition, from various sectors including development of intelligent speech etc. medical care institutions, scientific technology and relevant application, research organizations, equipment creating a sustainable innovation SenseTime's platforms in video manufacturers, AI startups, mechanism facilitating cooperation content audit, city-level visual analysis, information technology solution among enterprises, universities and driver monitoring system and providers, universities and colleges, research institutions. augmented reality provide solutions and pro bono organizations. The for various scenarios including platform connects core players in iFLYTEK's key intelligent speech security, commerce and finance. Public innovation and entrepreneurship, technologies involve speech synthesis, security system checks the identity of cooperation across the industrial speech recognition, machine suspects through view information chain, scientific research, and translation, speech assessment research and judgment system. Facial public welfare, aiming to drive and cognitive intelligence. In open recognition is applied in self-service the implementation of national AI source, the platform shares core store and payment verification, based strategies in healthcare. So far, open technology development interfaces on cooperation with large retailers. medical imaging platforms based and cloud online service capabilities. Employment of identify authentication on Tencent Miying have established The industrial chain service platform technology in financial sector leads cooperation relationships with integrates solution providers, to lower financial risks and better more than 100 hospitals, playing an industrial design resource, sales customer experience. important role as evidenced by the channels and production supply practices of interpreting 106 million chain resources, etc. Seven business radiographs, serving 950,000 patients, incubators covering over 100,000 identifying 130,000 high-risk lesions square meters have been launched and analyzing 6.14 million medical in Hefei, Changchun, Luoyang, Xi'an, records. Chongqing, Tianjin and Suzhou, based on the support of developer service communities and local governments. These incubators have attracted more than 500 development teams and companies in intelligent speech and AI.
49 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
••Open intelligent adaptive data. AI-based education companies solutions to support platforms education platform are exploring open education platforms in improving intelligent adaptive The State Council proposes to to accelerate industrial development capabilities, with larger amount establish intelligent schools and and support China in realizing AI of data and more comprehensive platforms integrating teaching, development objectives. Pioneers such student profiles. Crowdsourcing management and service; and as Yixue Education—Squirrel AI are partners can provide platforms with leverage modern technologies taking the lead in developing intelligent more extensive and reliable contents to drive the reform of talent adaptive education platforms. and diverse personalization abilities, development model, combining through optimization and innovative mass education with personalized The five national open AI platforms transformation of contents, teaching development in a reasonable manner and intelligent adaptive education logic and user experience. Intelligent in China's Education Modernization platform mentioned above intend to adaptive capability access partners 2035. Education is technologically connect players across the industrial can help platforms optimize intelligent sophisticated in AI application, having chain. In education industry, intelligent adaptive algorithm engines for more accumulated mass and scattered adaptive education technology can inclusive application and higher resources in technology, content and provide personalized education efficiency.
50 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
2.3 Human vs. machine the accumulation of labelled data in language processing (14%) and speech AI allows machines to perform tasks supervised learning requires large processing (13%). Biometrics and scene including cognition, recognition, amount of human labor and cost understanding, two sub-categories analysis and decision making that are input, significantly restricting the under computer vision, ranked among traditionally performed by human, development of AI application in the top with a growth of 31% and 28%. exploring how to enable computers to relevant fields. Speech processing technologies speech simulate human in performing some recognition and speaker recognition ••External factors: The development thinking and intelligent behaviors. It both realized a growth of 12%. In of AI application is slow in some mainly studies how to allow computers education, intelligent adaptive education fields, subject to policy factors. For to perform intelligent behaviors, performs the same as or even better example, data in some sectors such as produce computers with the ability than human teachers in terms of healthcare are exclusively owned by a to think as human and realize more teaching effectiveness, user experience few organizations, which proves to be sophisticated computer application. and testing scores. Domestic and obstacles for data sharing. AI involves many different subjects overseas intelligent adaptive education including computer science, psychology, companies including Knewton, Yixue Stage 1: AI technologies better than philosophy and linguistics. The ability Education—Squirrel AI, Realizeit and human in recent years to perform tasks as or better than ALEKS have compared the effect of AI Application of AI technologies from IBM human is an important indicator of AI education technologies and human DeepBlue to OpenAI Five in various development. teachers through experimental practices sectors such as chess and cards, in the trend of "human vs. machine". debate, e-sports and even healthcare Compared with human, AI can be and education proves that the battle classified into weak AI, strong AI and AlphaGo is an AI-based Go program of "human vs. machine" can test a super AI. The development of AI operating with deep learning, and is company's technology capabilities and application varies in different sectors, the first AI robot to defeat a human draw more public attention to AI, thus mainly affected by the following key Go professional and the first to defeat is playing an important role in assessing factors: a Go world champion. In March 2016, the development of AI application in AlphaGo played against Lee Sedol, Go ••Clarity of rules and assessment each sector. world champion and 9-dan professional, standards: Some activities such and won 4-1. From the end of 2016 to as chess and cards games can be In 2015, Microsoft and Google early 2017, the program registered an assessed by computers according to developed image recognition account named "Master" at a Chinese simple, clear and quantitative criteria. technologies which are better Go website and played games with than human skills. Baidu's speech ••Frequency of exceptional cases: dozens of Go master-hands from China, recognition technology is also better Processing in typical scenarios Japan and South Korea, recoding 60 than related human ability. According and processing in scenarios with consecutive wins and 0 losses. In the to the statistics of World Intellectual exceptional cases, such as facial Future of Go Summit held in Wuzhen Property Organization (WIPO), recognition and autonomous driving. in May 2017, AlphaGo played three among all AI application technologies, Machines have advantages in handling games with Ke Jie, the world No.1 ranked computer vision ranked No.1 in terms uncertainties. champion, and won 3-0. The emergence of patent filings from 2013 to 2016, of AlphaGo is pushing the battle of man ••Size of training data: Many fields accounting for 49% of total filings with versus machine to a whole new era. are at the initial stage in training an increase of 24%, followed by natural data accumulation. For example,
51 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
Figure 2-3: Percentage of AI application technologies in terms of patent filings across the world (as of 1H 2018)
24%
49% 13%
14%
Computer vision Natural language processing Speech processing Others
Source: WIPO, Deloitte Research
••Computer vision detection of objects in videos. Deep announced in 2015 that their speech Computer vision is a combination learning-based computer vision has recognition system can recognize of eyes and brain, involving images, exceeded human, as it is simply driven Chinese better than human with lower perception and understanding. It has by large amount of data rather than character error rate (CER). YITU's short surpassed human in its capabilities, human will. Machine vision performs speech dictation technology realized especially in facial recognition and understanding activities based on a CER of 3.71% in December 2018, image classification. Machines are data, in a way different from that of symbolizing a significant improvement more acute in perception than human beings. of speech recognition accuracy. human eyes, being able to gain more Speech recognition technology is ••Speech recognition information with higher accuracy improving in accuracy over time. Such Speech recognition was created of image recognition. In addition, machine-perception technology is by Bell Labs in the 1950s. Carnegie machines can stimulate human in relatively sophisticated, while machine- Mellon University launched a speaker- performing some creative activities. cognition semantic understanding is independent, large-vocabulary and Machines recorded an approximate limited by factors including training continuous-speech recognition system image recognition error rate of 2.9% in method, labelled data volume and in late 1980s. It is worth noting that ILSVRC 2016, much lower than 5.1% of computational complexity, therefore speech recognition systems that human beings, with good performance impeding the development of voice can recognize Chinese better than throughout object detection interaction. people came into being earlier than (recognition), object positioning and those that apply to English. Baidu
52 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
Figure 2-4: Maturity of speech and vision technologies
Technologies Maturity Application scenarios Representative companies
Security; Malong Technologies; Object and scene Autonomous driving; TuSimple; recognition technology Smart appliances; YITU; Drones DeepGlint
Photo editing software; SenseTime; Biometric recognition Security; CloudWalk Technology; technology Smart appliances MEGVII
Optical character Finance; DeepGlint； recognition technology Translation software CC Intelligence
Malong Technologies; Video object extraction IoT; Intellifusion; and analysis technology Security Hikvision
Tecent; Intelligent speakers; Baidu; Speech recognition Real-time translation Sogou; iFLYTEK
Mobile search; Mobvoi; Semantic analysis Intelligent vehicle information Unisound; systems iFLYTEK
Vehicle information systems; SinoVoice; Voice interaction Appliances; AISpeech Robots
Source: Publically available information, Deloitte Research
53 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
••AI-based education and related supporting technologies, find a decline in scientific papers to Compared with games which have extensive adoption of AI-based patent publications, indicating a stronger clear systems and complete data such education also requires integration interest of industries in the practical use as go, educational system is far more of quality educational resources of AI technologies. complex, involving various subjects and establishment of data pools by including pedagogy, psychology enterprises, algorithm advantages, Transportation has been the fastest and cognitive science. Intelligent large sample size, and market growing sector in the application of adaptive learning combines AI, data recognition of intelligent adaptive AI technologies from 2006 to 2019. mining, cognitive science, pedagogy, learning based on coordination among The application of AI in transportation psychology, behavioral science and the government, schools and teachers. only accounted for 20% of total patent computer science, allowing adaptive applications in 2006 while the figure learning system to simulate human Phase II: Technologies to be well reached one third as of 2019. In 2019, teachers to some extent and adjust above human average in the next autonomous driving and healthcare learning contents based on special two to over ten years are two hot AI technologies as they can teaching strategies in accordance AI capabilities are improving in separate dramatically improve social resource with students' learning objectives, technologies such as speech and visual distribution and change people’s life learning behaviors, preference recognition, and applied to numerous style. However due to technical barriers, and status, thereby to realize commercial areas rapidly. While they are not fully applied for commercial personalized education. AI-based with the rapid growth of AI in these uses and still on trial. adaptive education provides students commercial areas involving increasingly ••A long to go for fully autonomous with personalized tutoring and complex sectors and scopes, separate driving higher learning efficiency, imitating technology solutions can no longer meet Autonomous driving is ultimately experienced human teachers with the application needs of industries. aimed to realize truly autonomous good teaching methods. Machine Application technologies, including driving and enable passengers to do learning technology enables adaptive autonomous driving and intelligent other things with an eye on roads. But education to adjust students' learning healthcare, involve in several AI this requires advancements both in contents and paths on a real-time application technology sectors. hardware and software. In terms of basis, rather than organize unified hardware, LiDAR is likely to cost tens of learning according to syllabus or AI technologies has a long way to go in thousands of dollars leading to higher teachers' arrangement in a traditional commercial application from academic costs for a large scale deployment. way. research, patent application to industry As for software, engineers need to application. The initial focus of patent find an approach to equip AI with the The development of AI application in application is to develop technical ability to arrange and differentiate education is likely to address social solutions for industrial application, often various objects. Autonomous driving problems resulted from uneven with a lag of about ten years behind relies on the collaboration of AI, visual distribution of educational resources. scientific publications. Statistics from the computing, radar, monitoring devices Apart from AI application in education World Intellectual Property Organization and global positioning systems.
54 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
Figure 2-5: Distribution of autonomous driving technologies
Automotive Segment Representative Constraints Estimated technology technologies companies maturity
Bosch Continental Controls integration WayMo Finished vehicle Unmanned vehicle Baidu Tesla Nissan
OV O-film •• Rule: Lack of depth Video camera DENSO (deep dive into specific Ultrasonic radar Glarun Technology technologies in every Sensing Millimeter-wave radar Bosch scenario) LiDAR Continental •• Specialty: Lack of width Over ten years is required Veldyne (various scenarios in to reach L4-L5 IBEO large spans)
Google •• Training data: Low Baidu statistical confidence NavInfo Positioning High precision map of data; few mileage Beidou samples Galileo Glonass
Mobileye ADAS algorithm Zongmu Technology Underlying support Automotive chip NVIDIA CMOS sensor Sony Samsung
Source: Publicly available information, Deloitte Research
Measured by the clarity of rules and environmental model 360 awareness, forward or back.’ Besides, autonomous evaluation methods, the frequency of equipped with LiDAR, optical sensor and driving should not grow along with special cases and the scale of training millimeter-wave radar, etc. Secondly, technical advancement, but it requires data, autonomous driving has not cars must be equipped with high- laws and regulations, awareness or even yet reached or gone beyond human resolution maps with localization at high the overall supporting facilities such as capabilities as image recognition and accuracy of less than 10 cm. And thirdly, insurance and infrastructure built by speech processing have done, nor it can the market must make driving or yield governments. make judgement like human. rules that are perceived and accepted by cars and pedestrians. Meanwhile, As a result, autonomous cars have a ‘Before the fully autonomous driving cars must be deployed with sensing, long way to replace other cars, during market matures (L4-L5), the industry reasoning and decision-making abilities which the co-existence of autonomous must start with three capabilities. Firstly, similar to human as human are likely to cars and human drivers should be cars must have the sensing capability of violate traffic regulations, hesitate or go prioritized.
55 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
••Lack of practicable rules and data, AI healthcare is still at the mid- to diagnosis. Users may leave out standards for the application of stage and has a long way to go to fully or even incorrectly express their AI healthcare replace doctors. In intelligent diagnosis chief complaints via virtual medical Measured by the clarity of rules and as an example, there are certain assistants, leading to the discrepancy evaluation methods, the frequency of issues and challenges in medical of suggestions generated by virtual special cases and the scale of training liability concerning AI’s assistance assistants and users’ diseases.
Figure 2-6: Technologies involved in AI healthcare
Application Underlying Representative Constraints Estimated scenarios technologies companies maturity
•• Rule and specialty: High misdiagnosis rate, such as Infervision the average misdiagnosis Medical imaging Computer vision More than ten years Yidu Cloud rate due to imaging analysis reaching 27.8%
•• Lack of training data
Natural language Unisound Electronic medical processing CTME •• Low market acceptance Two to five years record (EMR) Speech recognition iFLYTEK
•• Various specialties; TINAVI Assisted diagnosis and •• Limited by market regulation, Robot SMAROBOT Two to five years treatment such as about 97 months SIASUN Robot is required from molecule discovery to FDA approval
Berry Genomics Disease risk prediction Machine learning Precision Genomic - In the near future BGI Genomics
MORE HEALTH Health management Computer vision Airdoc - In the near future iCarbonX
Cipher Gene •• Existing rules and specialties Drug discovery Machine learning 3D Medicines Ten years Ribo •• Limited by market regulation
Source: Publicly available information, Deloitte Research
56 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
In terms of rules and evaluation in the new edition of CFDA’s Medical Phase III: 2099 the age of strong AI? methods, the absence of medical Device Classification Catalogue in 2017, Strong AI is a type of artificial intelligence information standards presents for diagnosis software which provides equivalent to human intelligence in all challenges for the application of AI in diagnosis suggestions based on aspects, enabling robots to fully possess medical sector. AI is a tool focusing algorithms, it can apply for certification abilities as human have rather than on mathematics and logic, requiring of class II medical devices as it cannot being limited within a certain sector. higher accuracy and standardization directly provide diagnoses if only with Strong AI can think, plan, solve problems, of contents. As for marking lesions assistant diagnosis functions. For those do abstract thinking, understand in medical images, for example, even that can automatically identify lesions complex ideas, and learn fast and from doctors from the same department have and provide clear diagnosis tips, they lessons. Some think that strong AI will various marking methods. And regarding must apply for clinical trial certifications appear if it can mimic the human brain medical records, it is challenging to in line with requirements for class III and replicate all human brain neurons synchronize patients’ EMRs accurately medical devices. and synapses of the same magnitude. and names of various diseases vary with different doctors on a geographic basis. Measured by the scale of training data, a We are now in the stage of weak number of problems can be found with AI which helps reduce human’s Countries keep a sharp hold on the medical data. Despite of a large volume intellectual work, similar to advanced market access mechanism for new of medical data in China, data specifically bionics. Both AlphaGo and robots technologies due to complex diseases related to one certain category of capable of writing news releases or and higher frequency of special cases medical problems are of low volume novels are still weak AI, with limited as well as high relevance with people’s and quality. In medical imaging, for capabilities better human. Data and livelihood and life-threatening errors. instance, relevant data can be provided computing power are of undoubtedly Currently, regulators prohibit virtual for machine learning only after clinical great significance in the era of weak AI, assistant software from generating seasoned doctors mark the data, but pushing forward the commercial use diagnosis suggestions on any diseases, such quality and marked data resources of AI. And the two elements are still the only simple inquiry and advisory are limited. Enjoying a majority of most important in the times of strong services for users’ health issues allowed. imaging data and experienced doctors, AI. Besides, researches of tech giants Regulators in China tightly control 3A-grade hospitals are most capable of marked by Google and IBM on quantum the review and approval of diagnosis helping AI companies develop effective computing is a strong driver for human functions provided by AI technologies. models. to enter the age of strong AI. According to the classification rules
57 Global artificial intelligence industry whitepaper 2. Development of AI technologies Global artificial intelligence industry whitepaper 2. Development of AI technologies
Figure 2-7: Representative companies and research of strong AI
Representative companies Research orientation Milestones
Cognitive computing IBM Debater IBM Pan man-machine interaction Watson
Google Assistant Systems neuroscience methodology Google PathNet Pan man-machine interaction AutoML project
Microsoft Pan man-machine interaction Cortana
Writing AI OpenAI Deep reinforcement learning Spinning Up program
Source: Publicly available information, Deloitte Research
As stated in the Architects of Intelligence, many research teams from large tech Additionally, OpenAI, co-founded by based on the average estimate of players and small companies are making Tesla’s founder Elon Musk and partly researchers and entrepreneurs working their contributions to building strong supported by Amazon Web Services, is in AI today, including DeepMind CEO AI. Google’s DeepMind and Google doing a great deal of research aimed Demis Hassabis, Google AI Chief Jeff Research take specific measures, while at strong AI. OpenAI also creates two Dean and Stanford AI director Li Feifei, PathNet (a solution of training large special tasks: Gym and Universe to test the era of strong AI will come by 2099. general-purpose neural networks) the skills of strong AI that are under and evolutionary architecture search development. Discrepancies from these simple AutoML (a method of finding good estimates indicate that we have a long neural network structures for image way to go to achieve strong AI. However, classification).
58 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
59 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
3. China’s position in global AI sector
This AI wave is featured by the move of lab findings towards commercial application, mainly driven by the significant enhancement of computing power, a wide range of policy supports, highly frequent large investments and increasingly identified user demands. The AI industry is fast growing in China where exist over 4,000 AI companies in 2019, ranking the second in the world and enjoying certain advantages in data and application. However, there is still a certain gap between China with regions leading the world in several aspects including basic research, chip and talent.
Figure 3-1: Comparison of AI in China and regions leading the world
China Regions leading the world
•• Possess the large number of mobile internet users •• Users focus more on personal privacy in the world •• European governments introduced GDPR to •• China has introduced a national standard entitled Data separate the right of use and ownership of data in Information Security Technology - Personal policy terms while the U.S. may come hot on the Information Security Specifications, lower heels stringency than GDPR
•• Japan is an important producer of semiconductor •• China possesses almost half of the market value, materials, high-end equipment and special yet relying heavily on imports in high-end chips semiconductors Chip •• Lagging behind in semiconductor equipment, •• South Korea takes an absolute lead in high- Software materials and manufacturing bandwidth memory and dynamic random access memory (D-RAM)
•• A large gap with advanced world level Robot •• Japan still tops the world in robotics •• Lack of originality
•• 92 NLP companies •• 252 companies in the U.S.
NLP •• RMB12.236 billion raised •• RMB13.467 billion raised in the U.S.
•• 6,600 employees •• 20,200 employees in the U.S.
•• 146 companies •• 190 companies in the U.S. Technology Computer •• RMB15.83 billion raised •• RMB7.32 billion raised in the U.S. vision •• 1,510 employees •• 4,335 employees in the U.S.
Speech •• 36 companies •• 24 companies in the U.S. recognition •• RMB3.087 billion raised •• RMB1.931 billion raised in the U.S.
•• China is catching up in auto sensing tech, AI Autonomous hardware and software, connectivity V2X and •• The U.S. has a solid technical base driving autonomous driving testing
Application •• The application of AI technologies in education has •• China has just started the application of AI grown earlier abroad AI education technologies which is still in its infancy mainly focusing on ToC. •• AI-based educational products penetrate deeper in Europe and the U.S.
Source: Oxford’s Future of Humanity Institute, Tencent Research Institute, Deloitte Research
60 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
3.1 China has larger volumes of data population21 . The enormous quantity of privacy in the world, providing users and more diversified environment netizens means that the data Chinese with the claim of right on their personal for using data companies can access to are more data that users have the right to acquire AI technologies are evolving on the basis complex and multiple-dimensional and revise their personal data and of massive data. In the mobile Internet and serve as a solid foundation for the decide who can use them22 . China has era which has arrived, data generated algorithm upgrade of AI technologies also published a national standard from mobile devices are far more and the expansion of application entitled Information Security Technology important than PC Internet. scenarios. - Personal Information Security Specifications, but with lower stringency In terms of the volume of data, China In addition to data, governments’ than GDPR. For example, apart from has the largest number of netizens in regulations on private data also have employers, physiological state, mental the world, reaching 829 million at the a great impact on the potential for state, economic status and social status end of 2018 with the penetration rate of companies to use data. European are also included in the identity defined 59.6%. The number of mobile netizens governments have introduced General by the EU. exceeds 800 million for the first time, Data Protection Regulation (GDPR) accounting for 98.6% of the total netizen as the strictest policy to protect user
Figure 3-2: Size and proportion of Chinese mobile netizens
100 million people 97.5% 98.6% 9.0 95.0% 100.0% 90.1% 8.2 85.8% 90.0% 8.0 7.5 81.0% 7.0 80.0% 7.0 74.5% 6.2 70.0% 6.0 5.6 5.0 60.0% 5.0 4.2 50.0% 4.0 40.0% 3.0 30.0%
2.0 20.0%
1.0 10.0%
0.0 0.0% 2012 2013 2014 2015 2016 2017 2018
Size of mobile netizens Proportion of mobile netizens
Source: CNNIC, Deloitte Research
21. The 43th Statistical Report on Internet Development in China, CNNIC, http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201701/t20170122_66437.htm 22. Titans of Tech: Europe’s Flagship Companies, The Economist, April 2019
61 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
3.2 China is in the highest demand China’s semiconductor industry is on chip in the world yet relying thriving at a double-digit rate. AI chip heavily on imported high-end chips market sees active capital raising AI framework can be broadly divided activities and an increasing number into three layers. The infrastructure layer of M&As. A typical example is the includes core AI chip and big data, which global giant Xilinx’s acquisition of is the base for sensing and cognitive DeePhi Tech, a start-up specializing in computing power at the technical machine learning, deep compression, layer. The application layer is at the top, pruning and system-level optimization providing autonomous driving, intelligent for neural networks. Tech giants led robot, smart security and virtual by Alibaba, Baidu and Huawei have assistant services. As the core of the AI stepped into this battlefield. It is technical chain, AI chip is essential for AI worth noting that Huawei has started algorithm processing, especially for deep AI chip competition in smartphone neural networks. Today, the integrated sector. And Chinese mainland is eating circuit chips imported by China from into Taiwan’s semiconductor market the U.S. values over USD200 billion, far shares. Moreover, the growing Chinese higher than crude oil imports. mainland market will be a commercial channel for integrated circuit design In East Asia, Japan has long been industry and Chinese mainland the leader in semiconductor R&D companies will continue to invest in and material industries, marked Taiwan’s semiconductor industry. by semiconductor titans including However, Chinese semiconductor Toshiba, Sony and Renesas Electronics. producers have significantly improved South Korea and Taiwan have certain their competitiveness in recent years advantages in memory and foundry while the key parts are still largely services. South Korea is leading in imported from western countries with D-RAM and NAND flash memory with the self-sufficiency ratio lower than many top semiconductor companies 20%. Chinese government is greatly including Samsung and SK Hynix, largely concerned about this issue and released powered by governmental support. several favorable polices to support the The requirement of core technical growth of the semiconductor industry. competency in NAND memory market makes it challenging for new entrants to compete in the market. Taiwan has become the globally leading semiconductor foundry service provider where the foundry industry is dominated by two contract manufacturers: TSMC and UMC. Semiconductor foundry is an important pillar of information technology industry.
62 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
3.3 Chinese robot companies are In industrial robots, several local robot 3.4 The U.S. has solid strengths in growing fast with greater efforts companies, including Shenyang SIASUN, AI’s underlying technology while in developing key parts and EFORT, GSK, Harbin Boshi, STEP, ESTUN China is better in speech recognition technologies domestically and JEE, have grown fast. In the past technology Robot R&D and application is an years, domestic robot companies have Natural language processing (NLP): important index for measuring the initiated outbound M&As to acquire China is catching up with the US technological development level of overseas advanced technologies and NLP technology is able to change one country and the future economic expand foreign markets. ESTUN, EFFORT the way for human to interact with growth will be highly relevant with the and Wanfeng Technology have acquired machines. Massive dark data that are robot industry to a large extent. As an European and American companies. undiscovered in business data sector important part of building advanced Among three core robot components, cannot be applied by means of current manufacturing industry, robots, both controllers and servers are increasingly technologies, including unstructured industrial robots for production activities made in China but reducers are still data such as short message, files, emails, in the industry sector and service robots imported. There is a large gap of videos, speeches and pictures. NLP participating in human’s daily life, are of domestically made reducers in product technology will play an important role in great significance in seeking new growth performance and precision though in commerce. engines. With strong support of funds line with consistent design principles. and policies, China’s robot industry is Global service robots are on the rise. China is catching up with the US in terms growing rapidly and continues to top Despite of a late start, China is slightly of natural language processing (NLP). the world in terms of growth rate. The inferior to the global advanced level, Enterprises represented by Alibaba market exceeded USD8.74 billion in even leading in some key technologies. and Baidu has taken the lead in NLP. 201823 at the average growth rate of Tech giants including BATJ step in the In particular, Baidu's leading language 29.7% from 2013 to 2018. market backed by their strong technical and knowledge technologies are widely capabilities while traditional home applied in intelligent search, deep Q&A, Key robot components are still largely appliance companies, e.g. Haier, are dialogue system, intelligent writing, imported, including high-precision actively marching into home service machine translation and many other reducers, controllers and servo motors. robots, and research institutions, such fields. Japanese companies dominate more as Harbin Institute of Technology, are than half of the global high-precision converting research results through reducer market. In terms of software, cooperation with companies. China has certain skills in control algorithm and secondary development Special robot market is in its infancy, yet with a gap with foreign markets mainly covering vertical sectors like in stability, responsiveness and firefighting. Companies have certain accessibility. independence and made breakthroughs in key technologies such as high- Additionally, in terms of the application precision positioning and navigation and scenarios of robots: obstacle avoidance.
23. Report on the Development of China’s Robot Industry (2018) （《中国机器人产业发展报告（2018）》）, Chinese Institute of Electronics
63 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
China is superior in speech life has been surrounded by buildings’ technologies including auto sensing recognition access control, traffic cameras and technology, AI hardware and software, Speech recognition technology can banks’ security cameras. Ubiquitous V2X and autonomous driving testing. be widely applied in such scenarios cameras, integrated with facial Building on governmental support and as TVs, mobile phones, call centers recognition technology, magnify existing long established technical base, the U.S. and smart homes. In this aspect, the security effects and monitor everyone’s is widening the technical gap with China average recognition accuracy rate of behaviour. in sensor technology and AI hardware main platforms, including Baidu, iFLYTEK and software. But Chinese tech giants and Sogou, reaches over 97%. Alibaba’s From application layer perspective, and research institutes and universities speech AI technology is superior to there is little difference between are driving China to catch up in the two Google and is named by MIT as one China and the U.S. and even China is areas. of 10 Breakthrough Technologies expected to overtake the U.S. in facial 201924 . And this technology has been recognition technology. But there is a China is almost comparable to the penetrated in many scenarios, such large gap in basic algorithms between U.S. in connectivity technology and as express delivery, customer service the two countries. China has about autonomous driving testing. Huawei’s and train ticket purchase. During the 146 companies mostly engaged in the 5G technology will provide world-class 2018 11.11 Global Shopping Festival, application, including HIKVISION while communication support for connectivity Ali Xiaomi handled 98% of customer the U.S. has about 190 companies. V2X. And Huawei has cooperated with enquiries from the whole platform, China has 1,510 practitioners while the domestic and foreign carmakers in equivalent to one-day workload of U.S. has more than 4,00025 . testing. In autonomous driving testing, 700,000 human customer service staff. Beijing, Shanghai, Shenzhen and 3.5 China is catching up in Chongqing have issued self-driving Computer vision: A large gap in application vehicle testing licenses and provided basic algorithms Autonomous driving: Solid technical testing venues for tech giants (e.g. Computer vision has long been one base puts the U.S. ahead of China Baidu), who join hands with domestic of hot AI technologies. People’s daily Autonomous driving involves carmakers such as BAIC and BYD.
24. 10 Breakthrough Technologies 2018, MIT 25. China vs. U.S.: Battling to become world’s first AI superpower, Tencent Research Institute
64 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
Figure 3-3: China’s skill level in autonomous driving
•• The U.S. government provides strong support to achieve remarkable technical advantages.
Auto sensing technology •• China is accelerating to catch up: relevant technologies are being applied by carmakers, such as SAIC, Changan. And domestic universities, including Tongji University, Tsinghua University, participate in relevant technical research.
•• The U.S. is leading in hardware dominated mainly by NVIDIA, INTEL and IBM.
AI (hardware/software) •• Google predominates in software, relying more on basic technology while Baidu focuses more on optimize human work targeting Chinese market in Autonomous terms of basic technology. driving •• China has least difference with the U.S. in technology due to lack of consistent V2X standards. Connectivity technology V2X •• Communications is one strength of Chinese companies. Huawei is able to compete with Qualcomm in some areas and takes the lead in cooperation and car testing with several domestic and foreign OEMs.
•• China can stand up against the U.S. in the number of carmakers. Tech giants Autonomous driving (Baidu) plays an essential role who cooperates with several domestic and testing foreign car companies (BYD, Chery, BAIC, FOTON)
Source: Publicly available information, Deloitte Research
AI-based education: Foreign school, secondary school, high school (acquired ALEKS), ETS, ACT and NWEA countries are more mature while and many subjects in vocational are offering AI-driven self-adaptive China has a brighter prospect education. It has more application assessment and learning solutions; and despite in the early stage. scenarios focusing mainly on To B, intelligent adaptive learning players The application of AI technologies including testing agencies, schools and with efforts to cover five learning parts in education industry started earlier companies. Representative companies include large corporations such as in foreign countries where adaptive can be classified into three categories: IBM Watson Education, Adobe and technology has emerged early in the online education platforms transforming Dell, as well as specialized companies 1990s. AI-based education products into intelligent adaptive sector such as such as Prowler.io, Knewton, ALEKS are widely penetrated in Europe and Coursera, Khan Academy; intelligent and Carnegie Learning. Researches the U.S. for users at all ages through adaptive business units of education have proven the outstanding results nearly a decade of growth, involving groups such as Pearson, Wiley (acquired of AI technologies to improve learning early childhood education, primary Knewton), Elsevier, Cengage-McGraw Hill performance.
65 Global artificial intelligence industry whitepaper 3. China’s position in global AI sector
China has just started the application of learning systems are growing rapidly education company Yixue Education— AI technologies in recent years mainly thanks to China’s large population Squirrel AI, online education companies focusing on To C. But Chinese market base, education resources shortage transforming into intelligent adaptive has grown fast though in the early stage and priority on education. Education education and AI companies engaged as Yixue Education—Squirrel AI saw groups marked by New Oriental and TAL in intelligent adaptive education. With revenue exceeding RMB1billion in 2018 push into adaptive education through the unique advantage of going through and that of English Liulishuo reached investment and self-building. Moreover, the whole learning process, intelligent over RMB600 million. Various kinds there are three other categories of adaptive learning becomes the most of education related companies are companies including intelligent adaptive widely used technology in all learning stepping into AI technology as adaptive platforms, such as the Shanghai-based parts.
Figure 3-4: Comparison of AI-based education companies
Foreign Domestic
•• Mainly focus on To B •• Mainly focus on To C Business model •• Clients include testing agencies, schools, •• Clients include tutorial agencies companies
•• The U.S. and Europe are more mature and •• In the early stage of development achieve notable results Technical level •• Its core goal is at replacing the role of teachers •• Assist in teaching yet unable to fully replace in teaching teachers
•• Online education platforms transforming into •• Online education platforms transforming into intelligent adaptive sector (i.e. Zuoyebang, intelligent adaptive sector (i.e. Coursera, Khan Liulishuo,17zuoye) Academy) Representative •• Intelligent adaptive business units of education •• Intelligent adaptive business units of education company groups (i.e. New Oriental, TAL) groups (i.e. Pearson, Cengage Learning) •• Intelligent adaptive learning players (i.e. •• Intelligent adaptive learning players (i.e. Knewton, Squirrel AI) Aleks) •• AI companies (i.e. iFLYTEK)
•• China is seeing fast-growing intelligent adaptive •• Further enhance assistance to teaching learning systems that is expected to catch Prospect •• AI is to reshape learning experience and new- up thanks to China’s large population base, type education system is taking shape education resources shortage and priority on education
Source: Deloitte Research
66 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
67 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
4. AI reshapes every industry
The AI technology saw rapid start-ups need to find the right entry industries are facing disproportionate development during the past five to points and cultivate industry solutions in resource allocation. Despite the different ten years. Over time, the technology order to build moats. pain points, the above issues can be has gradually become known to the effectively addressed through data public and the pace of the Moore's Industries and sectors are facing collection, processing and analysis. Law is slowing down. The commercial different pain points. For instance, the Driven by data, AI can change the application of AI has become a key financial industry is facing cost pressure, industries. focus. Technology giants increasingly product and service homogeneity, and deploy vertical industry application, and frauds; the healthcare and education
68 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-1: Industry upgrades driven by the AI technology
Industry Pain point Some AI solutions
Financial •• financial institutions face application cost pressure •• develop intelligent customer service using technologies •• financial institutions are unable to offer customized such as voice recognition and semantic understanding to products and services to long-tail customers resolve users' problems and lower customer service cost •• single credit dimension, with financial risks such as bad •• develop intelligent investment advisory using big data and debts and frauds AI to provide personalized services for more customers •• build intelligent risk management system by combining AI and big data to enhance risk management capability based on comprehensive evaluation on multi-dimensional data
Healthcare •• resource allocation cannot keep up with demands as a •• intelligent imaging allows quick check of cancer related result of disproportionate healthcare resources diseases •• expensive medical expenses and long waiting time •• health management to change people's health habit from •• tension between doctors and patients, and misdiagnosis the source •• poor primary healthcare
Education •• disproportionate education resources •• leverages its image and voice recognition functions to •• teacher-centered rather than student-oriented teaching analyze problems, and develops customized solutions approach and effective feedback suitable for learners through deep •• one-to-one teaching targeting students' specific learning learning, adaptation and calculation problem is not realistic under the current mode of teaching
Autonomous •• frequent car accidents •• with sensors and visual technology, autonomous driving driving •• human attention span is limited frees the hands of humans; people adopt car-sharing and •• freight transportation cost is high electrified vehicles; logistics efficiency will be enhanced
Digital •• the urban population is expanding and the workload of •• leverage technologies including computer vision and government related public service is huge and complex machine learning to increase the proportion of self-service •• crimes and terrorist attacks are not predictable •• utilize big data to analyze the daily habit of criminal suspects and possible places where they may show up, and leverage computer vision technology to find and arrest criminals
Retail •• traditional market research methods can hardly reflect the •• leverage the machine learning technology to create user real consumer demands profiles and feed appropriate advertisement according to •• advertising targets and measure of the advertising impact users' preference are inaccurate •• leverage machine vision to capture customer behavior and •• consumers are increasingly demanding in terms of in-store analyze their real needs experience, payment convenience, and timely delivery •• leverage technologies including computer vision, voice/ semantic recognition and robotics to enhance consumer experience
Manu- •• product R&D and design processes are time-consuming •• leverage computer vision to identify defective items facturing and costly •• human workers are substituted by robots to perform work •• manual processes bring higher error rate and are difficult in dangerous sites to trace back •• high cost to achieve rapid mass customization with human labor •• lack of low-cost labor
Smart city •• the progress of urbanization is bringing different degrees •• traditional "smart cities" are developing into "super smart of impact on urban economy, resource utilization, living cities" covering six aspects to promote the integration of standard, time cost and sustainability; with increasing cities urbanization and population, urban managers around the world are facing increasingly difficult challenges
Source: Deloitte Research
69 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
In the financial industry, for example, development directions and motivation solutions and effective feedback suitable the AI technology has rapidly changed for the current healthcare sector. With for learners through deep learning, the key sectors in the traditional the continuous development and adaptation and calculation. financial industry. Amid continuous implementation of the AI technology changes of consumer behaviors and in healthcare, the existing complicated The performance of the above needs, the traditional financial services medical consultation process will be industries in the two dimensions industry players are facing remodeling greatly simplified and better solutions namely industry application and of different areas and processes. For will be provided to the people in market opportunities may be classified instance, with the constant changes of a number of aspects including into four quadrants. Transition stage consumer behaviors and preferences, optimization of healthcare resources means that the level of application of technology–driven precision marketing and improvements in healthcare AI in the relevant industry is relatively and feeds enable the provision of technologies. AI technology in healthcare high, but market opportunities are customized products and services, has basically covered the four key limited currently and the market scale enhancing customer stickiness through segments in the healthcare industry, is expected to expand further in the technology and allowing the inclusion including healthcare, medicine, health future. Germination stage indicates that of smaller businesses in the broader insurance, and hospital. the level of application in the industry ecosystem. In some areas, customer and market opportunities are not yet service representatives are gradually In recent years, the education mature, although AI has played certain replaced by AI robots to provide inquiry sector continued to demonstrate functions but is still at the initial stage services to customers. unprecedented revolutions through overall speaking. Growth stage means data reconstruction. Unlike traditional that the level of application in the In the healthcare sector, amid education approaches, AI-based industry is not sufficient, but application population aging, increase in the education uses data generated from will broaden in the future with more number of people with chronic health the five key learning processes, namely market opportunities. Developed stage problems, shortage of quality healthcare teaching, learning, practicing, assessing, means the AI technology has already resources and hike in public medical and testing. It leverages its image and had a profound impact on such areas expenses in society, the application voice recognition functions to analyze with high level of industry application of AI in healthcare has brought new problems, and develops customized and market opportunities.
70 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-2: Application of AI in different industries
High Transition Developed
Retail
Financial
Manufacturing Education Digital government
Communication, media and services Smart city Industry penetration Autonomous driving Energy Healthcare Public utilities Natural resources and materials Germination Growth
Low Market scale High
Source: Deloitte Research
4.1 Financial industry: AI enhances the business efficiency of financial long-tail customers barred by traditional the business efficiency of financial companies. financial services are covered, allowing businesses and reforms their more individuals or SMEs to enjoy internal operations Such efficiency enhancements are more convenient and efficient financial The financial industry is an important mainly reflected in three aspects. services and covering more customers application scenario of AI. The Firstly, under the traditional financial in terms of volume and range. Thirdly, application of AI in the financial industry model, there are often problems a wider range and variety of players has changed the rules of the financial such as information asymmetry, high are attracted to the ecosystem. By services industry. Traditional financial financial risk and high lending cost. The evaluating the consumer credit through institutions and technology companies application of innovative technology collection of massive consumption join hands to build a high-performance in the traditional financial business and credit data of consumers, financial and dynamic ecosystem on a broader improves the primary service structure risks such as bad debts are lowered. scale. Participants need to establish of the entire financial industry, thus Efficiency enhancements of the three extensive interaction with external lowering business cost and enhancing aspects above are mainly reflected parties to access the resources they service efficiency. Secondly, with in the three areas namely intelligent need respectively. Therefore, in the the emergence of various forms of investment advisory, intelligence FinTech ecosystem, a profound trust innovative FinTech companies, which customer service and intelligent risk and cooperation relationship will be are based on innovative technologies management, which are also the areas formed between financial institutions and provide customized products and with more profound application of the AI and technology companies, enhancing services per customer needs, more technology.
71 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Intelligent customer service In China Merchants Bank Credit Card enhances service efficiency Company, for example, intelligent Intelligent customer service refers to the customer service is leveraged to provide capability to answer simple questions more than 2 million times of online of users, and resolve users' questions human-machine interactions per day related to products or services through for customers, resolving 99% of users’ human-machine interaction. The level questions. Intelligent customer service of maturity of NLP is relatively low not only enhances customer service among other types of AI technologies, efficiency with 24-hour uninterrupted but it plays significant value in customer service to improve user experience, service. High training cost, difficulty but also reduces costs significantly. in aligning service outcome, and An increasing number of financial high turnover are issues with human companies are starting to adopt customer service representatives. Based intelligent customer service systems and on big data, cloud, and AI in particular, are making them the primary means intelligent customer service accelerates of customer service. Human customer the intelligentization of customer service representatives have shifted service of businesses. Knowledge maps from the main role to the supportive are leveraged to answer simple and role, and will even be completely repetitive questions, thus reducing replaced in the future with the advance the use of human customer service in the AI technology. representatives and enhancing the efficiency and outcome of customer Intelligent investment advisory service. Customer service robots have broadens range of service of the replaced 40%-50% of human customer long-tail customers service jobs and it is expected that 85% The application of AI robots in of the customer service tasks will rely on investment advisory liberalizes the ways AI by 202026 . of wealth management. The once costly and labor-intensive service is becoming The application of intelligent customer a product, and technology is extending service in the financial industry is mainly financial services to groups beyond the seen in the banking, insurance, and traditional wealthy class. For example, internet finance sectors. Traditional Lufax provides corporate or individual financial institutions such as banks and investors with comprehensive financial insurance companies tend to acquire asset transaction information and local solutions from IT service companies advisory related services. to ensure data security and mitigate potential leakage risk. Due to the Chinese residents have huge diversified needs of traditional financial investment assets, expected to reach institutions, customized solutions are RMB237 trillion by 2020, which will offered by IT service companies. In lay a foundation for the extensive the internet finance sector, intelligent development space of intelligent customer service mainly adopts the investment advisory in China. SaaS model, and it is mainly used by major internet finance companies.
26. Gartner
72 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Intelligent investment advisory as Quantopian was founded in Boston separated from products. Customers online tools can automatically analyze in 2011 to "inspire talented people will turn to the emerging, cost-effective the customer's financial profile and everywhere to write investment automated advisors. The number of leverage big data analysis to provide algorithms". Indeed, it means that wealth products sold via their own customized recommendations. It can the company leverages the internet advisory channels will further reduce. also manage investment portfolio to community platform to provide Traditional wealth managers will also see invest in quality products. Currently, scientists, developers and students weakened advantage of the economy there are two key types of models: with resources and basic frameworks of scale. More and more processes will and let them cooperate and use become automated and the number Trading procedures provided by financial data, education tools and of customers using virtual channels financial institutions such as banks. research data. With the thousands will be on the rise. New entrants will Some robot advisors only invest in of investment algorithms submitted, continue to use low-cost architectures. passive investment portfolios (such as Quantopian selects the best solutions It can be foreseen that the revenue ETFs) and do not allow modification based on risk, returns, potential and of traditional wealth managers will of investment strategies by clients. other factors. From the most basic way decrease in the future, and competition Other robot advisors allow clients of its operation, Quantopian is like a among traditional industry players in to take active part (such as selecting crowdsourcing investment company professional areas or service providers stocks) and charge service fees for in which algorithmic authors allow will intensify. modification of investment portfolios the platform to use the most effective and other services. For example, algorithms among their work and to Intelligent risk management "Machine Gene Investment" offered gain profit-sharing from designing mitigates financial risk by China Merchants Bank provides investment algorithms. In the current stage, personal investment advisory services. In 2016, consumption expenditures in China the average buy amount of accounts To financial institutions, these trends is growing rapidly, becoming the key reached RMB36,90027 . indicate that the middle-class market force driving China's economic growth. is being eroded. Retail banking will face With the increase in demand for loans, The other type of model is based competition as new market entrants the number of financial frauds is also on social media platforms, which may offer more commoditized on the rise. Built by combining AI and allow users to exchange investment wealth management products. In the big data technology, the intelligent options, strategies and market high-net-worth market, individual risk management system performs insights. Individuals may create wealth planners are playing a more comprehensive evaluation on data from investment portfolios and share with important role. In addition, retail multiple dimensions including users' other investors. One of which is retail banks may provide automated transaction behavior, credit status and algorithmic trading, which enables services to fulfil most of the needs social relationships to generate the final investors with limited technology of wealth management customers, evaluation results. knowledge to obtain effective but they need to adapt to customers’ investment algorithms and benefits, investment preference. Therefore, Financial institutions adopting intelligent and share only part of the profits wealth managers may need to modify risk management can be classified into from the investment returns with the their value proposition to maintain three types, namely the comprehensive algorithmic authors. For example, their operation. adopter, technology provider, and In the future, advisory service may be proprietary developer.
27. Reimagined (重构), Deloitte Research
73 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Comprehensive adopters generally Proprietary developers refer to financial In addition to the above three areas, refer to internet giants with both institutions that develop intelligent risk AI has rapidly changed the key areas development capability and financial management products by setting up of the traditional financial industry businesses, such as Ant Financial in-house technology teams to support in respect of internal operation of which launched Ant Shield and Sesame their own businesses, such as 360 financial companies. Amid continuous Credit, and NetEase Financial (网易 Finance which developed the Tian Ji (天 changes of consumer behaviors and 金融) which launched Beidou (北斗) 机) big data risk management system. needs, the traditional financial services risk management system. By offering Through intelligent risk management, industry players are facing remodeling intelligent risk management products, financial companies may significantly of different areas and processes. For these companies aim to obtain more relieve the problems faced by the instance, with the constant changes of user data for the provision of service as traditional financial industry such as consumer behaviors and preferences, a whole. frauds, credit risk management, and technology–driven precision marketing credit default by more effective means. and feeds enable the provision of Technology providers refer to Capital loss rate is a key metric of a customized products and services, technology companies providing risk financial company's risk management enhancing customer stickiness through management solutions to banks, capabilities. With intelligent risk technology and allowing the inclusion insurance companies and internet management, Alipay achieved an of smaller businesses in the broader finance institutions, such as Tongdun average capital loss rate of 0.001%, ecosystem. In some areas, customer Technology which offers anti-fraud, being highly competitive around the service representatives are gradually credit risk management and data globe. replaced by AI robots to provide inquiry verification services. services to customers.
74 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-3: How AI changes the whole operation process
Business Change Example Outcome
Front Service •• online intelligent •• ICBC's intelligent customer service "GINO" •• reduce labor cost office customer service provided over 100 million times of service in •• enhance service efficiency 2017 •• outlet customer service •• enhance customer experience robots
Marketing •• precision marketing •• Tencent Financial Cloud performs precise •• enhance advertising conversion user profiling and labelling by leveraging the rate and reduce marketing cost marketing big data accumulated in the Tencent ecosystem, and providing marketing feeds using self-developed prioritized advertising algorithms
Middle Product •• customized and •• China Merchants Bank's "Machine Gene •• precise product pricing office personalized products Investment" has 150,000 users, exceeding RMB •• boost long-tail customers to 10 billion •• intelligent investment expand business coverage advisory
Risk •• credit rating •• Ant Financial enabled Alipay to achieve a capital •• reduce risk claims management loss rate of lower than 0.001% by leveraging •• risk pricing •• reduce bad debt risk its intelligent risk brain which relied on massive •• dynamic monitoring data. It is leading globally. •• identify financial frauds quickly
Back Management •• internal risk •• Ping An Group performs remote intelligent •• enhance management efficiency office management management based on data modeling and and reduce management cost visual presentation •• intelligent office
Data •• data analysis •• Tencent and Beijing Municipal Bureau of •• enhance data security rating and Financial Work co-developed a Beijing-based reduce business risks •• active data security and financial security big data supervision platform protection to identify, monitor and provide early warnings on all types of financial risks in order to prevent and manage financial risks
Source: public materials, Deloitte Research
75 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
At present, intelligent financial The specific application areas of risk management and intelligent applications based on AI have been these companies mainly include investment advisory companies implemented on a trial basis in many intelligent risk management, accounted for more than half of those places. Currently, there are 139 intelligent investment advisory, companies, being the most popular intelligent financial companies in intelligent customer service, intelligent capital orientation. China, of which 44% have obtained investment research and intelligent round B/post-round B investments. marketing. Of which, intelligent
Figure 4-4: Distribution of different types of intelligent financial and investment companies
3% 5.9%
11.9%
34.7%
12.9%
5.9%
25.7%
Intelligent risk management Intelligent investment advisory Intelligent customer service Intelligent investment research
Intelligent marketing Intelligent claim settlement Intelligent payment
Source: iResearch, itjuzi.com, Deloitte Research
As one of the most developed cities there are 39 representative intelligent online lending, InsureTech, consumer in China's financial industry, Shanghai, financial companies focusing on 14 finance, intelligent payment, and the national artificial intelligent center, areas. The majority of the intelligent supply chain finance. put forward the idea of integrating financial companies are located in AI and finance earlier. In Shanghai, Pudong New Area, largely engaging in
76 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-5: Distribution of key intelligent financial companies in Shanghai
Baoshan District Putuo District Chongrong Financial Information quanerp—enterprise informationzation Service—stock forecast Chongming District buyfunds—AI financial solutions
Jiading Distict Jingan District Huilicai—wealth management app 51xtr—payroll services leapstack—intelligent insurance Minhang District Baoshan Chinascope—financial data Jiading Surong 360—social credit information District District I platform G H — F Yangpu District Ziwei Financial wealth management E A and investment platform Qingpu D B Jingshu Finance—Financial business District C services Pudong chancein—stock data services Changning District Minhang New Area profeto—intelligent finance Tigerobo—intelligent financial District Songjiang xinshucredit—Big data information search engine District Achain—public blockchain platform Fengxian eulerfinance—smart investment District Jinshan Pudong New Area District fantaiai—Financial technology services Jinshan District betawm—Data solutions Meidan Information—financial services Xuhui District icekredit—Big data afajr—Smart ivestment wuyintong—blockchain financial services iqunxing—Financial service platform
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: ASKCI Consulting, Deloitte Research
77 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
4.2 Education: AI application covers empowerment in education industry into an official stage of development, the whole education process cannot be accomplished at one with intelligent adaptive education New technologies will continue to stroke. Throughout AI's development enterprises including Cognitive Tutor, change the education industry. The and application process in education Knewton and RealizeIt being established emergence of the AI technology has industry, the main focus was on the in the US in the early 21st century, brought about the intelligentization planning and preliminary exploration and AI technologies are increasingly trend in the education industry, as of AI education at the beginning. In applied in education industry. Intelligent well as trends of mobility, product the 1950s, Allen Newell and Herbert adaptive learning is an AI educational homogeneity and online-offline A. Simon, both professors at Carnegie technology that simulates the one- integration. These trends will restructure Mellon University and pioneers of to-one teaching process between the relationship among players in the AI, promoted the development of AI teachers and students, empowering education industry ecosystem, improve in combination with mathematics, the learning system with individualized students' learning efficiency and engineering and economics. In the teaching capabilities. After 2010, redefine the education industry. 1970s, Jaime Carbonell created an China's intelligent adaptive education intelligent tutoring system and started to enterprises started to emerge, including From the perspective of industry teach with assistance from computers. New Oriental, TAL, Yixue Education, etc. development stages, AI education In 1993, the first Artificial Intelligence Since around 2016, TAL, New Oriental sector now is still in a development in Education (AiED) World Conference and many other well-known education stage and has not reached its was held in Edinburg, England. Over institutions as well as capitals have maturity. Though a hot concept, AI time, AI education has also entered begun investing in AI education.
Figure 4-6: The intelligentization trend in China's education industry
Deepened mobility Constant product improvement The trend of mobile device-based and upgrade learning will continue to grow. Many Diversified user needs lead to product new technologies will emerge. homogeneity to satisfy personalized needs of users
The age of intelligence
Indispensable AI technology Integration of online and offline Learning methods and means education will change further. Integration of Education companies constantly technology and education mainly expand and integrate product chains. relies on AI to understand and keep Offline and online education are likely up with the customers’ personalized to be integrated more closely, and needs from time to time. both will develop harmoniously with different focuses.
Source: Deloitte Research
78 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
AI will restructure the ecosystem of the with humans through interactive feedback on user data, then apply them education industry. AI is a technology interface and application scenarios. in five processes: teaching, learning, that intelligently processes massive Based on the AI technology, education assessing, testing and practicing, and data based on big data capturing and companies provide users with AI-based finally develop customized solutions and multi-dimensional recognition systems, education content, tools and relevant effective feedback. and achieves information interaction services. They collect, analyze and give
Figure 4-7: Illustration of the AI-based education structure in China
Students/Person receiving education
Teaching Learning Assessing Testing Practicing
AI education contents AI education tools AI education services
AI education platform
AI technical enabler
Personalized recommendation engine: personalized learning path and learning contents recommendation
Big data analysis system: learning data analysis and processing
Big data collection system: real-time collection of behavior data of each student
Source: Deloitte Research
Under the intelligentization trend, given its unique advantage of being able Besides, image recognition products intelligent adaptive learning has become to penetrate the whole learning process. and voice recognition products are also the most widely applied AI technology, It will gradually become the mainstream. applications of AI in education.
79 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-8: The application of AI in the five learning processes
Five learning Application of AI Major technologies Difficulties processes •• Collect preference data in advance, add •• Intelligent adaptive •• Low data frequency makes it feedback process learning system difficult to quantify •• Analyze raw data and feedback data to •• AI technology is not as optimize online teaching systems sophisticated as teachers Teaching
•• Deeply analyze learners’ learning patterns •• ntelligent adaptive •• Low data frequency makes it •• Provide targeted suggestions for learners learning system difficult to quantify on adjusting learning patterns based on •• Voice recognition •• Complicated learning patterns
Learning scientific methodologies lead to analysis difficulty
•• Apply recognition technologies to recognize •• Intelligent adaptive •• Machine recognition test results submitted by learners learning system accuracy is low •• Use deep learning to evaluate results •• Huge and complicated
Assessing according to preset standards testing data Technical difficulty
•• Predict based on learners’ behavior data •• Intelligent adaptive •• Large data volume •• Use testing data to make learning plans learning system •• Simple and explicit feedback •• Image recognition product data Testing •• Voice recognition product •• Low analysis difficulty
•• Use big data to design algorithm and analyze •• Intelligent adaptive •• Large data volume learner behaviors learning system •• The most direct feedback •• Design customized question portfolios to data strengthen weak points •• The lowest analysis difficulty •• Analyze question data to generate targeted Practicing evaluation report
Source: Deloitte Research
80 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Mainstream products in current AI learning solutions based on the development of adaptive learning education sector include intelligent students’ learning status, including systems since 2010 and significant adaptive learning system, intelligent knowledge reserve diagnosis, results have been achieved. Knewton’s assessment, intelligent dual-teacher competence assessment and content adaptive learning assisted Math courses classroom, and intelligent accompanying recommendation. For example, in have significantly improved the pass rate robots, etc. Top enterprises of intelligent the teaching and learning processes, of students at Arizona University and adaptive learning system in China learners vary with each other in learning reduced course withdrawal rate by 56%. include Yixue Education—Squirrel AI; status and competence. Leveraging Intelligent adaptive learning technologies intelligent assessment enterprises are the AI technology, intelligent adaptive and products develop differently in represented by iFLYTEK, Singsound, course systems can use big data and China and overseas. In the United Liulishuo, Pigai, etc.; intelligent dual- algorithms to develop a set of effective States and Europe, intelligent adaptive teacher classroom is led by TAL's and standardized courses according to companies are more developed, serving Intelligent Classroom and Yixue important and difficult teaching points mainly To B users, and are represented Education—Squirrel AI's AI + human such as knowledge point extraction by Knewton, ALEKS, RealizeIt and dual-teacher classroom. and learning method induction, offering DreamBox. Chinese intelligent adaptive the most suitable courses for learners companies are still in the initial stage Intelligent adaptive learning of different levels. Computing power and mainly serve To C users. However, systems improvement, massive data and adaptive learning is developing at a Intelligent adaptive learning systems the application of Bayesian network faster pace in China and is expected to can provide real-time and customized algorithm have greatly accelerated surpass the foreign countries.
Figure 4-9: Effectiveness of adaptive learning systems
+17% pass rate +45% completed the course -56% four weeks earlier withdrawal rate
Source: Knewton, Arizona University, Deloitte Research Note: the effectiveness of learning with Knewton’s adaptive learning assisted Math course introduced by Arizona University
81 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
The integration of the AI technology status and competence. Leveraging As speech assessment products and learning information management the AI technology, intelligent adaptive are dependent on data, education system is an integral part of intelligent course systems can use big data and companies with leading advantage in adaptive education products. By algorithms to develop a set of effective speech assessment will be stronger. applying cloud computing and the and standardized courses according to The accuracy of speech assessment deep learning function of AI, they important and difficult teaching points products is not only closely related can customize homework, testing such as knowledge point extraction and to algorithm, but also has close and courses and conduct scientific learning method induction, offering the ties with the validity and diversity assessment. AI technology has been most suitable courses for learners of of corpus in the database. With introduced into schools and some different levels. enough training data, algorithms education companies to track learning would be able to extract features status, record learning data, evaluate Intelligent assessment products more accurately and reasonably proficiency, manage learning progress A major branch of AI education, intelligent in the process of assessment. If all and connect parents with schools. By assessment is divided into voice and training data is provided by male using open big data, it can challenge essay assessment based on different users, then male users will get higher traditional teaching systems, make types of learning. Voice assessment is scores than female users. Moreover, teaching more targeted, quantify and represented by iFLYTEK, Singsound and enough training data also can help visualize learning progress, and improve Liulishuo, while essay assessment are extend speech assessment to other teaching and learning quality. Currently, represented by iFLYTEK and Pigai. Speech languages. Companies with large inadequate user coverage limits the recognition is an AI technology that has user base can obtain more diversified application of learning information been put into commercial application data, develop better products, attract management system in K12 sector. in the early stage. Currently, education more users, and achieve sustainable companies mainly apply it to conduct development, therefore, they could Besides, data openness is very speech assessment for oral language have bigger chance to succeed. important. With open big data, learners. Speech recognition technology The lack of ToB education companies education tech companies can use assess user’s oral language automatically creates huge demand for speech the AI technology to conduct analysis from multiple dimensions including assessment products. China has even and give feedback, which could help pronunciation, semantic meaning more urgent demand for speech companies and schools improve and expression. More importantly, assessment products due to the lack teaching plans and education quality. the application scenarios of speech of excellent foreign language teachers Moreover, companies can provide assessment technology has been and uneven oral language teaching technical support for offline education extended from shadow reading to open quality in second and third tier cities. entities with their technical strength and questions. For oral language learning, On the other hand, in Chinese schools, data reserve. Now, education companies speech assessment products have one teacher always has to teach more and IT companies mainly provide open two user groups: first, ToB education than 30 students. With limited practice data in vocational and K12 education institutions. They mainly use speech and guidance, students can’t learn oral sectors. assessment products in language testing language well as listening, speaking such as CET 4/6 oral testing, mandarin and writing. ToB market has huge At present, intelligent adaptive learning testing etc.; the other one is ToC users. demands, but companies focusing on products mainly play the assistive Since the time for class exercise is limited, this segment (including extracurricular role in teaching, while it is unable to speech assessment products have been education institutions, education completely replace teachers. In the embedded into many learning systems training centers and schools) are far teaching and learning processes, to help students practice oral language from enough. learners vary with each other in learning after class.
82 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
4.3 Digital government services: Building digital government with top- support for comprehensive intelligent favourable policies expedite down efforts. To build service-oriented government construction. Moreover, intelligent transformation governments, an e-government trend Hangzhou develops an integrated smart Similar to other sectors, governments gained popular nationwide since 2015. e-government management system to are expediting intelligent transformation As new technologies such as AI, big migrate urban management system, after witnessing significant achievements data, and cloud computing are putting urban planning system, and financial of AI in cost reduction and efficiency into commercial application, this trend service system on a one-stop service improvement. With the great support transforms into digitalization and platform. of urbanization strategies, China has intellectualization. The value of China’s achieved the highest urbanization digital government market is expected Since government departments are growth rate in the world. In 2018, the to exceed RMB340 billion by 2019, with somewhat disconnected and have urbanization rate of reached 60%, 15% of CAGR. different intelligent service demands, with around 730 million of urban intelligent service systems provided population. By 2050, China will have Government services: core elements by companies are always designed to larger urban population and make of digital government construction improve certain government services. urbanization rate exceed 80%. Large Government service is one of the most For example, to facilitate tax inspection urban population will generate massive important and the fastest growing area of local tax authorities, Ultrapower government affairs. Governments can in digital government construction. Local provides Chinese text analysis, use robotic process automation (RPA) governments are energetically building transforms text as structured data, and and AI to relieve administrative officials one-stop service platforms in order to searches related data via Internet to dig from repetitive tasks, enhance service provide intelligent government services. the relationships between companies efficiency, strengthen city development For example, Shenzhen Municipal Public and shareholders. quality, and improve urban living Security Bureau migrates offline service environment. Under the background windows to its online portal. Citizens Backed by AI technologies, government of AI empowerment, technologies can deal with household-related affairs services will be friendlier and more like face recognition and natural after “facial scanning”. It also develops an targeted. On one hand, citizens and language processing will help enhance integrated government information and companies can have easier access government service quality, improve resource sharing system for Shenzhen to public services, rather than simply working efficiency, bring convenience with 3.8 billion items of data (385 through online portals; on the other for enterprises and citizens, and realize categories of information and resources) hand, AI-based decision making will be intelligent decision making. from 29 government departments28 more effective and accurate and flexible. and public institutions to provide data
28. “To learn the benefits of government information resource sharing from Shenzhen’s experience” （《 从深圳政务信息资源共享实践成效充分认识政务 信息资源共享的基础性作用》）， Xinhuanet.com
83 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Leading public security service digital surveillance, develop smart police providers will get stronger services, accurately identify criminal AI is playing an increasingly important behaviors that are under planning role in urban security. Compared with and potential risks, and shift the focus the existing digital security, AI-based from post-investigation to proactive security system can provide real- prediction, warning and precaution. time and intelligent public security management. In China, smart city Security system solution providers are construction is gaining momentum. companies that provide all security As an important part of smart city system products and services, covering construction, public security will have pre-consultation, planning, product broader development space, as local provision, operation and maintenance governments are paying increasing and aftersales services. These attention to it. By 2020, the revenue companies are powerful, represented of security sector is expected to reach by Hikvision, Dahua Technology RMB800 billion with higher than 10% and Huawei. Hikvision and Dahua annual growth29 . There are two types of Technology are integrated solution AI-based security companies: product providers transformed from intelligent or service suppliers and security system hardware suppliers, they are expanding solution providers. markets with rich security technology experience. Huawei is a representative Product suppliers mainly refer to of platform providers. It builds security companies that provide certain products ecosystem with cloud technology and or services for the whole security experience. In 2017, Huawei established system. For example, Cloudwalk assists China Safe City Video Cloud Partner Guangdong Provincial Public Security Open Alliance with companies including Department to deploy face recognition Sense Time, YITUTECH etc. In 2018, system in key places such as subways the alliance developed solutions to and bus stations. When searching for apply safe city public security videos in suspects, it compares the appearance multiple areas. features of suspects with real-time surveillance video. The face recognition AI-based security market is still growing, system can help find, track and catch leading players are getting stronger. suspects, reduce manpower in post The competence of companies investigation, analysis and decision depends on technical ability and system making, and greatly improve working solution. As the requirements for efficiency. PERCENT helps the police market access increase, technologically to integrate internal and external data, backward companies will be knocked use big data and cognitive intelligence out and industry concentration will be technology to combine and analyze further improved. AI-based chips are multi-modal data, carry out data-based increasingly important for intelligent
29. 13th (2016-2020) Five Year Development Plan for Chinese Security Industry (《中国安防行业“十三五”（ 2016-2020 年）发展规划》) , China Association of Work Safety
84 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
security services. By 2020, the number 2020. As estimated, AI-based medical as well as the Yangtze River Delta. They of sensing devices in IoT will reach 50 industry will account for one fifth of the are focusing on disease screening and billion30 . If companies send massive total AI market. In 2016, the value of prediction, medical imaging diagnosis, data collected by them to the cloud, the China’s AI-based medical industry was medical records and documental broadband will be under huge pressure. RMB9.661 billion, with 37.9% of growth. information analysis, as well as new drug Edge computing will bring great In 2017, this number exceeded RMB13 research. In 2018, companies engaged benefits for the security sector including billion, increasing by 40.7%. And it is in disease screening and prediction got reducing the time from data to decision expected to hit RMB31 billion by 2019. the most financing. Except large state- making and cutting transmission and owned enterprises, tech giants such as storage costs. Therefore, security Baidu, Alibaba, Tencent and iFlytek also service providers will gradually expand In terms of market demand, due to actively invest in these start-ups. from downstream to upstream and the shortage and uneven allocation enhance the application of intelligent of medical resources, the market is in In the past several years, Shanghai technologies. urgent need of more open and efficient has become a fertile land for “AI + medical solutions. In terms of technology healthcare” for its inherent advantages. 4.4 Healthcare: AI-based development, with significant progress First, platform advantage. With applications are getting mature in computing vision, natural language large medical service demands and In face of numerous social problems, understanding and data mining, outstanding scientific research capability, such as aging population, growing the implement of AI-based medical Shanghai accumulates systematic and chronic disease patients, quality medical applications gain more technology complete medical data, which lays a resource shortage and higher public support. As for policies, developing solid foundation for providing AI-based medical costs, AI-based medical services healthcare industry based on Internet medical services. Second, international will bring the healthcare industry with and AI technologies is always the focus market access and favourable new hope and momentum. With the of our national policymakers. In April entrepreneurship environment. application of more AI technologies in 2018, the State Council clearly showed Shanghai gathers mainstream medical healthcare industry, tedious medical its support for healthcare-related AI information companies and Internet treatment procedures will be simplified, technologies through the Opinions on companies, attracts abundant capital medical resource allocation will be promoting the development of “Internet and talents, and has formed advantages optimized and medical technologies be + healthcare”. These policies are positive in medical imaging, minimally invasive improved. signals for the development of AI-based surgery and drug research. Third, healthcare industry.Chinese AI-based Shanghai makes a good start in According to the Development Planning medical companies are late comers but promoting industry-university-research- for a New Generation of Artificial maintain fast growth. In recent years, application integration and cultivates Intelligence released by the Stata such start-ups constantly increase and many excellent electronic and intelligent Council, China clarifies the goal of get huge capital injection. China has medical equipment companies, which increasing the size of major AI-based 144 smart medical companies, most of will benefit AI research, platform building industries to over RMB150 billion by them are based in Beijing, Guangzhou and data sharing.
30. IDC
85 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-10: distribution of Shanghai’s key AI-based medical companies
Baoshan District Huangpu District Weikan Intelligence—intelligent medical Chongming District GT Apeiron Therapeutic—anti-tumour imaging analysis drug R&d SP Medical-Intelligent medical devices and software Songjiang District DEEP VOXEL INC.—medical imaging Yangpu District Bangbang Robotics-recure robotics Baoshan DR.brain—medical imaging Jiading District ayoka—smart work-out District I Changning District G H F ivisionhealth—digital technology E A Minhang District Qingpu D B BaseBit—healthcare big data District C VoxelCloud—medical imaging Pudong Mirage3D—medical beauty New Area — Qingpu Distict Minhang Ech-med.com medical equipment District changrentech—health management Songjiang xinws—heart health management District Fengxian Jingan District District dr—elephant-mobile health solutions Fengxian District Jinshan Skinrun—intelligent beauty data Sucabot—surgery robot District
Xuhui District Pudong New Area Meecaa—smart medical equipment Pailong Biology—biotechnology COBIO—medical diagnosis xinmob—wearable device Accutar Biotech—targeted therapy Intellchildcare—lung & heart stethoscope Hiwein—Health management SYNYI AI—medical text analysis le9health—Medical big data
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: IT juzi, Deloitte Research
86 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
With the rapid development of AI data and complex training framework, healthcare industry. In China, talents technologies in healthcare industry, however, not too many companies can proficient in both medicine and traditional medical concepts, meet the above two requirements. technology are in severe shortage. As technologies, talents and regulation are Many of them have not developed for regulation, the healthcare industry facing with challenges. Since traditional algorithms to make joint diagnosis is closely related with life safety, patient diagnosis approaches are deep-rooted, on complicated diseases. Besides, information should be confidential and the acceptance level of doctors and the healthcare industry also face the safe and be protected by relevant laws patients on new technologies is crucial problem of technology and product and regulations. for intelligent medical service providers. homogenization. Talent shortage is Intelligent healthcare requires massive another restraining factor for AI-based
Figure 4-11: smart healthcare industry chain
Smart healthcare industry chain
EMR Medical Health Assisted Disease risk Drug Hospital Hospital Unisound imaging manage- diagnosis prediction discovery manage- manage- Hwinner Infervision ment and Berry Cipher Gene ment ment iFlytek Yiducloud More treatment Genomics 3D-Med Medbanks platform iFlytek health Tinavi Precision Riibo Real Data Infervision Airdoc Smartbot Genomic LiinkDooc iCarbonX Siasun robot BGI SYNYI AI
Structured Process Identify Phone DNA Drug Support Technology and feature food robot sequence research medical platforms classifiable extraction through Navigation analysis and data mining that use AI patient value based images and robot Disease screening, and medical technologies information on images helps form prevention side effect decision to assist in advance balanced analysis prediction making with medical dietary and machine research habits tracking learning
Computing Speech NLP Robot Machine learning vision
Source: Deloitte Research
87 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
So far, AI-based medical technologies imaging: first, image identification. In the one. Watson for Oncology is a cognitive have basically covered four areas: sensing phase, AI can be used to analyze computing system developed by IBM medical treatment, pharmaceuticals, images and get meaningful information. to assist tumour treatment. It has been medical insurance and hospitals. The Second, deep learning. In the learning embedded into Yihui multi-discipline first batch of AI-based medical products and analysis phase, AI can use massive diagnosis cloud platform to support have been applied in three scenarios: imaging and diagnosis data to form a collaborative diagnosis and treatment. intelligent diagnosis and treatment, deep understanding of neural network Watson cognitive calculation technology hospital management and health and then develop diagnosis capability. provides sufficient clinical evidence management. for the discussion between doctors, iFlytek and Tencent have entered into besides, it also help transmit patient Intelligent health management. the intelligent medical imaging sector. data, build knowledge base and offer It means applying AI technologies in For example, Tencent rolls out a new follow-up services, forming a closed specific health management scenarios product Miying, which applies imaging management loop. such as using medical sensors to identification, deep learning and other monitor health conditions. Currently, leading AI technologies to help doctors As China’s leading AI + healthcare such applications mainly include risk identify early esophagus cancer. With up application, Tencent Miying is important identification, virtual nurse, mental to 90% of accuracy, it can help patients for Tencent to build the new generation health, online diagnosis, health identify lesion as soon as possible. of AI-based medical imaging opening intervention and precision medicine- Moreover, Jianpei Tech, Yiducloud, and innovation platform. Now, Tencent based health management. With the Zying, RayPlus, Deepinformatics and Miying can screen for many diseases, development of AI technologies, big data other Chinese companies also apply AI including early esophagus cancer, lung has been widely applied in personal in medical imaging to improve medical cancer, diabetes, retinopathy, breast medical record, POCT equipment, services. cancer, colorectal cancer and cervical intelligent health devices and mobile cancer. The newly published AI-based phone apps. Health management aims Intelligent diagnosis and treatment. colorectal cancer screening system can to prevent diseases and maintain health It means applying AI technologies identify adenoma, non-adenoma and through individualized management, to assist diagnosis and treatment. adenocarcinoma, provide real-time which is going to be the mainstream Computers “learn” from medical experts video enteroscopy examination for the of preventive medicine. For instance, and doctors, imitate the thinking and first time, and identify adenocarcinoma Cognitive Care (Hangzhou) develops inference of doctors and then develop with 97.20% of accuracy. The AI- virtual doctor with medical information, reliable diagnosis and treatment based diagnosis platform can help clinical medicine knowledge and virtual solutions. Intelligent diagnosis and doctors diagnose and predict over technologies to provide follow-up treatment is the most important 700 kinds of diseases, covering 90% of services for discharged patients. application of AI technologies in highly-frequent diseases in outpatient healthcare industry. departments. The system accumulates about 500,000 medical terms, over 1 Intelligent medical imaging. It refers So far, several intelligent diagnosis million term relation rules, more than 10 to applying AI technologies in the programs have been implemented million pieces of health tips, and around diagnosis of medical imaging. AI can in China, IBM’s Watson intelligent 80 million items of high-quality medical be applied in two phases of medical diagnosis platform is the most typical knowledge.
88 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
4.5 Autonomous driving: leading Autonomous diving is still at the As autonomous driving needs strong force in auto industry reforms testing phase, but it will have huge industrial infrastructure and technology In the era of artificial intelligence, auto market potential in the future. Due to support, China’s autonomous driving related smart mobility ecosystem is technology and regulatory limitations, car companies mainly gather in Beijing, being redefining. Three major elements autonomous diving cars have not been Guangdong, Jiangsu, Zhejiang and of mobility (people, car and road) have widely used. Many traditional carmakers Shanghai. Industry cluster effect will get their own decisions and behaviors and Internet companies such as SAIC, more prominent with the development just like human beings. The whole NIO, DiDi, Baidu, BAIC and BMW have of autonomous driving and the Yangtze mobility ecosystem will experience completed the first phase of testing River Delta and the Pearl River Delta dramatic changes. Strong calculation (closed road testing), but only several will remain the growth poles. Moreover, capability and massive valuable data pass the second phase of testing (open local policies also have important impact are the nucleus of multi-dimensional road testing), therefore, the autonomous on the distribution of autonomous collaborative mobility ecosystem. As driving market won’t have too much driving car companies. China’s first the application of AI technologies changes in the short term. China is batch of autonomous driving pilot cities, in transportation sector becomes expected to roll out autonomous driving Beijing, Shanghai, Fuzhou, Chongqing, intelligent, electrified and sharable, an cars by 2020. At that time, the sales Changsha, Changchun, Hangzhou, intelligent transportation industry chain of autonomous driving cars will reach Guangzhou and Shenzhen, have built centered on autonomous diving will be 60,000 units, and this figure will reach 4 roads for autonomous driving car gradually formed. million units by 2035. testing.
Figure 4-12: geographic distribution of Chinese autonomous driving companies
13%
6% 34%
8%
15%
23%
Beijing Guangdong Shanghai Zhejiang Jiangsu Others
Source: Deloitte Research
89 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
From a geographical view, Shanghai is Jiading District, Shanghai has chosen Many domestic autonomous driving leading the reform in the auto industry. a section of low-risk road (5.6km-long) start-ups such as NIO, Weltmeister, In March 2018, Shanghai officially to test intelligent and connected cars Singulato and Youxia have built R&D granted China’s first batch of license publically. Traditional automaker SAIC centers in Shanghai. Meanwhile, plates to auto makers for open road and autonomous driving start-up NIO international auto brands including Tesla testing. Shanghai will allow the testing have gained the first batch of license and Google’s Waymo also set up plants of intelligent and connected cars as well plates. BMW is the first foreign auto and R&D bases in Shanghai. as autonomous driving cars on roads. brand gaining permission in Shanghai.
Figure 4-13: distribution of major Shanghai-based autonomous driving car companies
Baoshan District Chongming District Yangpu District Shanghai Rongshen—intelligent mobility Roadefend—driving security 51autoshop.com—car sales outlet Geotech—intelligent mobility big data Jiading District Songhong—vehicle R&D Hesai Tech—laser radar Jingan District Baoshan Shanghai Internet of Things Co., Ltd.—IoT Ichezheng.com—driving data Jiading District District I G H Minhang District F Xuhui District E A WM-motor—New energy Qingpu D B Mappertek.com—automatic Hozonauto—electrical vehicle District C positioning and navigation Pudong Banma—Internet vehicle Minhang New Area Ebanma.com—automotive solutions District Changning District Songjiang YOGO Robotics—Business service District Fengxian Daokeme—Car Hailing community Pudong New Area District Zongmu—auxiliary driving Jinshan Hingetech—intelligent vehicle system Hongkou District District NASN Auto Electronics—intelligent driving Stonemeter—automobile electronic Raxtone Software—IoV system Motovis—autonomous driving Nullmax—autonomous driving
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: ITJUZI.com, Deloitte Research
90 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
From the perspective of user demand, and environment-friendly. Traditional initiated cross-border cooperation car has been considered as an auto makers are making technology with relevant departments and auto important transportation tool, however, breakthroughs. Mainstream car makers, manufacturers, to achieve reasonable as car ownership increases, negative no matter technology companies resource sharing and allocation. To build impact such as traffic accidents, traffic or manufacturers, have reached a multi-dimensional collaborative mobility jams and pollution has gradually consensus on cross-border cooperation: ecosystem in the era of smart mobility, emerged. We need new technologies data and connection will be the key strong computing power and massive and approaches to make transportation words in the era of smart mobility. valuable data are necessary. safer, more comfortable, economic Some technology companies have
Figure 4-14: grading of autonomous driving technologies
rading of autonomous Name Definition Driving operations driving technologies
NHTSA SAE
L0 L0 Manual driving People drive cars safely Driver
L1 L1 Auxiliary driving Vehicles complete only one operation related with Driver and vehicle steering wheel and speed, drivers are responsible for other driving operations
L2 L2 Partly autonomous driving Vehicles complete several operations related with Vehicle steering wheel and speed, drivers are responsible for other driving operations
L3 L3 Conditional autonomous Vehicles complete most driving operations, drivers Vehicle driving need to stay focused and be prepared for unexpected situations
L4 L4 Highly autonomous driving Vehicles complete all driving operations, drivers don’t Vehicle need to stay focused in certain roads and environment
L5 Fully autonomous driving Vehicles complete all driving operations, drivers don’t Vehicle need to stay focused
Source: SAE, NHTSA, Deloitte Research
Vehicles began to have intelligent more comfortable and safer. The real abroad, are at Level 2 or Level 3. AI- functions since 2000. GPS and sensors intelligent auto trend starts from the based systems and algorithms have provide data and application support second decade of the 21st century. become mature, however, the testing of for autonomous driving. Since the Following Google’s efforts in AI autonomous driving technologies is still rolling out of GPS, many tech and auto technologies, many AI-based functions at the experiment stage. If autonomous companies have begun to accumulate were developed to assist drivers, such as driving cars cause traffic accidents personal mobility data. AI use massive lane changing and parking. on roads, trust crisis would burst out data to learn driving skills. Sensor between auto companies and users. enables vehicles to sense and judge From the perspective of technology Currently, unmanned freight transport the surroundings. For example, ABS, development, most intelligent driving and shared autonomous driving car are safety bag and ESC make vehicle technologies, no matter at home or the latest AI-based applications.
91 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-15: autonomous driving industry chain
Autonomous driving industry chain
Auto intelligence Auto chip Auto communications
Baidu UISEE DeePhi Tech Westwell IoV High-precision map JD IDRIVERPLUS Cambricon Intellifusion Sense Time Alibaba Horizon Baidu map BDStar Navigation MEGVII Tencent Robotics NavInfo Amap.com
OEM Auto control
Braking system Steering Throttle Brake
BAIC BAIC Singulato Central Cloud Intelligent Vehicle Singulato Baidu JD GAC SAIC Auto sensing NIO BYD Camera Laser radar Millimeter wave radar Ultrasonic radar
Perception Technology Beetech Benewake Qfeeltech Heyi technology HawkEye technology
Source: public information, Deloitte Research
Unmanned freight transportation. and JD announced the completion of integration, long-distance sensing, In logistics sector, autonomous driving testing on L4 unmanned heavy trucks in refined modelling & controlling and can be applied in long-distance truck China and Silicon Valley respectively. multi-object optimization and decision transportation, delivery on closed roads making. Commercialized unmanned and intra-city transportation. It can help Trucks have many problems, including heavy truck driving technology can increase the number of trucks on roads, large blind area, lack of flexibility, poor reduce driver demands, cut down reduce accident death rate caused by stability and loose structure. AI-based energy consumption and emission and drivers and cut transportation costs. unmanned freight transportation can help mitigate global warming. However, Industry giants and start-ups have help resolve these problems based nothing is perfect. Due to high power started to research the former two on technologies such as multi-sensor consumption, battery may cost a lot in application scenarios. Recently, Suning online positioning, multi-sensor long distance transport.
92 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Unmanned car-sharing. It’s an be a core competence. The business percent, and that of machine learning important application of autonomous model that traditional automakers related applications would exceed 42 driving technology. According to the selling car ownership to individuals percent. Report on China’s Car-sharing Mobility will be replaced by emerging business Market 2018, China’s utilization rate of models. In this context, the retail industry private cars is only 5%, together with have been begun to leverage AI to some traffic control measures, young 4.6 Retail: Industry convergence drive transformation. Embracing the urban consumers will increasingly tend driven by AI trends of technological development, to choose car sharing. According to the Benefited from the digital major domestic offline retailers has data released by the Ministry of Public transformation of retail industry, AI has been increasing their investment in AI. Security in 2017, 215 million of people penetrated into all the links on the retail Investment in building AI capabilities who hold driving licenses don’t have value chain. As major retailers enter by retailers in 2018 stood at around cars, with 33 million new driving licenses into the game, e-commerce giants and RMB900 million, taking up 3.15 percent being granted every year. high-tech companies are stepping up of their total investment, and is expected efforts in expanding their presence in to exceed RMB17.8 billion by 2022, As for the commercial potential of the market, driving the convergence accounting for 25 percent of total autonomous driving, AI effectively of AI applications in retail industry. investment. E-commerce giants are also reduces the transportation costs of Deep learning and computer vision utilizing AI to speed up integration of people and goods. AI ushers us into have developed as pillar technologies online and offline businesses. the era of car sharing. Cars become for smart retail. Deep learning is shared transportation tools from private mainly applied in data analytics and In Shanghai, China's largest consuming properties, and car owners become modelling to optimize industry chain, city, the application of AI in retail industry users of car sharing platforms. As young while computer vision can be used would likely drive more efficient growth urban consumers increasingly tend for consumer behavior analysis and of the industry. Shanghai has the to choose on-usage mobility services, commodity identification. As of now, largest share of AI in retail, and retail rather than purchase their own cars, the computer vision-assisted goods technology companies in its Pudong current consumption model centered detection, self-service checkout, etc. New Area account for a quarter of all on car ownership will be fundamentally have been commercialized. its retail companies. Among which, changed. For traditional auto makers, Shanghai Lazhasi Information Science such change will gradually disrupt the Deployment of AI in retail industry is Technology Co., Ltd., parent company business models of traditional auto growing rapid across the world. As of the food delivery brand Ele.me, is makers. To response the shock brought forecasted by Gartner, 85 percent of located in Putuo District, Shanghai. Tech by autonomous driving, traditional auto consumer interactions will be managed giants represented by Alibaba and retail makers including Ford have transformed automatically through AI by 2020. Data champions represented by Yonghui all from car sellers to auto service of Global Market Insights shows an choose Shanghai as a key pilot plot for platforms. over 40 percent of CAGR for global AI their development of new retail and applications in retail industry during retail technologies. The reason is that For Internet giants holding with 2018-2024, with a market size reaching Shanghai, as China's most expensive city user data, the emerging intelligent USD8 billion by 2024. Of which, CAGR by consumption per capita, has a strong transportation market is their future of AP market would likely exceed 45 consumption demand and a higher level battle field. AI will disrupt the business percent, mainly driven by China and of opening up that drive higher degree models of traditional mobility service India markets. From the perspective of of acceptance for new retail models providers, and the capability of using technologies, CAGR of visual recognition/ among its consumers. data to integrate platform resources will search related applications would be 45
93 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-16: Distribution of key smart retailers in Shanghai
Chongming District Baoshan District Yangpu District Kaola mobi—community daily-life services Puqiu System—Retail big data Yes!Go—Unmanned retail LVX Leovation—Smart retail solutions
Minhang District Jiangan District Ocheng—Intelligent marketing Baoshan datamip—data analysis Jiading izhaohu—elderly care service District haomaiyi—AR District I G H Ginger technology—automation F E A vending Changning District Qingpu D B District C YMG365.com—Cross-broader Pudong e-commerce Xuhui District Minhang New Area iXiaoguo-Smart business services District Songjiang Qingpu District District Fengxian Pudong District WBox—Smart site selection District Chaoji daogou—Digital retail operation Jinshan Zuoling Youli—Daily-life O2O District Songjiang District Zhifengchao—Home furnishing
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District Source: ITJUZI.com, Deloitte Research
The applications of AI in retail are built applications such as site selection, Accelerated online and offline AI based on consumer, goods, store in-store shopping experience and integration. AI offers more methods for and supply chain, with different focus unmanned stores are designed to market players to manage consumer for different scenarios. Consumer- maximize performance of store relationships digitally, which will speed based applications, including demand investment; supply chain-based up online and offline integration, and forecasting, personalized marketing, applications like smart pricing, intelligent enable them to better satisfy consumers' purchasing experience and intelligent distribution and storage mainly seeks to individual needs at customer side as well customer service, aim to continuously enhance efficiency. as further optimize their cost and fees attract effective consumer engagement; structure to increase income and reduce goods-based applications mainly As AI quickens its penetration into each cost at business side. facilitate payment, stock count, sales link of retail industry, topics of concern promotion, pricing and other features regarding AI in retail industry in the utilizing smart shelves; store-based future will include:
94 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Massive fragmented experiments massive experiments with startups to Deep-dive of industry applications for application scenarios. Diversified find the best entry point. by startups. Though with significant development of AI in all links of retail investment in AI by tech giants, their industry brings fragmentation of Enhanced cooperation between retailers competition for ecosystem has not application scenarios, which now enter and startups. To compete with tech closed the door for startups. However, into a period of massive experiments. giants in retail market with extensive advantages are limited for startups to Some applications are developing in an application of big data and AI, traditional compete with tech giants, and they early stage, such as unmanned retail retailers need to be more proactive in cannot build a moat around themselves and in-store robots, and have no proof establishing partnerships with startups. merely by export of technologies. Thus, of business to clearly and effectively more and more startups would dive enhance customer experience and deep into the industry, working to offer reduce costs. With unclear application solutions and build clear profit models scenarios, retailers would also conduct for industry clients.
Figure 4-17: Smart retail industry chain
User portrait Online shopping Intelligent customer experience service Attracting • PERCENT consumer • SENSORS Data • Malong Technologies • ABitAI engagement • DT Dream • Infimind
Smart shelves
Goods • ImageDT management
Store site selection Smart store Unmanned retail • Behe Technology • Cloudwalk • DeepBlue Redefine stores • Geohey • Keruyun • F5 • ML • Tuzi City
Demand forecast Smart logistics
Smart supply • Cardinal Operations • ouhualin • inData chain • Linx Robot • Lanxin Technologies
Source: Deloitte Research
95 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
User portrait. Who are the users? Smart site selection. China's retail Intelligent customer service system. What products or services do they industry has gone from offline to online, AI-based customer service systems need? At what prices? These are the and returned from online to the basics starts semantic comprehension and issues most concerned by retailers. of omni-channel development to serve question recognition when customer The interactions of vendors with customers. The demand for offline retail asks a question, conducts big data customers generate massive data, and is reviving, indicating continuous growth search for the question identified, then through continuous accumulation of of needs from vendors to open new analyzes the meaning of customer's users' consumption data and machine stores. AI site selection, by integrating question and looks into the knowledge learning, vendors could dive deep various data including legacy sales map to find matched answers and make into the preferences and demands of data, population economic data and decisions. AI customer service answers consumers, and tag each customer with distance of competitors, could enhance to customers' questions throughout dozens or even hundreds of labels, such the granularity of models and analysis 24 hours of the whole day to enhance as purchase power, consumer credit, of data relevance for site selection to customer satisfaction, and to reduce brand preference, behavior pattern a new level. Site analysis delimits the labor cost for vendors and set people and social relations, so as to develop scope of business circle, and studies free from dull and intensive tasks to corresponding user portraits and real-time pedestrian volume around the focus on work of higher value. Beebot, knowledge maps. User portraits are the pre-selected site as well as changes of Alibaba Cloud's intelligent customer basis for precision marketing and large- people flow within the area, in order to service robot, can handle knowledge scale personalized recommendations evaluate whether customer flow of the enquiries and answer questions based and services. Alibaba's intelligent store could be met. Site comparison on its knowledge base. Combined with recommendation system made allows users to pre-select 3-5 store multi-round dialogue configuration 45.3 billion AI-based personalized sites and compare their head office of tools, Beebot can integrate businesses recommendations for users during chain stores, sectors, customer flow into dialogues, such as order inquiry, the Double 11 festival last year. at different hours, etc. to calculate logistics tracking, self-service return Research shows that, sales conversion and analyze the best site for the store. of goods, etc. Beebot can serve six rates of personalized pages are 20 GeoHey leverages geographical big million customers per day, with up to percent higher than that of traditional data to offer retailers with site selection 95 percent of resolution rate and 36 pages. PERCENT's user portraits for new stores and withdrawal site industry knowledge bases, providing allow vendors to modify user group selection, utilizing machine learning to multi-language services 24/7. ABitAI's indicators and weighting, and to choose calculate weighted score for an area or a Robota leverages autonomous suitable user groups for marketing. site based on the features of members machine learning and human-machine In the marketing project for a large of the location, as well as attributes collaboration, based on dialogue model department store, it successfully helped of pedestrians, competitor stores, of user intentions and combining with improve performance of promotion symbiosis resources for businesses, industry knowledge maps, to improve activities, reduce the cost of getting transportation accessibility, etc. and conversion of pre-sales shopping guide new customers by over 70 percent on develop a sales forecast model to and re-purchase. Robota will run within average, increase conversion rate by predict performance of the store. online and offline scenarios, offering more than 70%. Payment as an essential pre-sales guide robot and after-sales link of consumption contains massive service robot for online scenario, as well user data. Converged payment analyzes as intelligent hardware robot, offline users' payment preferences, habits, shopping guide robot, smart shelves, frequency, etc. to provide references for etc. for offline scenario. vendor to enhance customer loyalty and guide the pace of sales promotion.
96 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
4.7 Manufacturing: Huge reduce up to 20 percent of processing As seen from the regional distribution potentials for application of smart cost for manufacturers, and up to 70 of AI application in manufacturing, manufacturing percent of such reduction comes from Shanghai is growing as a key area Combined with related technologies, higher productivity. By 2030, the world for the development and application AI could help improve the efficiency will see GDP growth of USD15.7 trillion of emerging smart manufacturing of each link of the manufacturing driven by AI, of which China would take industries. Up to now, Shanghai has process by collecting various production up USD7 trillion; and by 2035, AI will basically established a development data via Industrial Internet of Things likely drive an increase of productivity by system for smart manufacturing. In and processing such data utilizing 27 percent, boosting a manufacturing key sectors including automotive, deep learning algorithms to offer GDP of up to USD27 trillion. high-end equipment, aerospace, recommendations or even self- ship and marine engineering as well optimization. However, compared As guided by state policies, China's as electronic information, Shanghai with financial, business and healthcare manufacturing industry is speeding has identified 14 national and 60 industries, the potential for AI up its intelligent transformation. The municipal smart factories, developed application in manufacturing has been Made in China 2025 plan published in 66 smart manufacturing standards, and substantially underestimated. SAP's 2015 lists smart manufacturing as one recognized 30 smart manufacturing analysis of top 300 AI investment of the five key programs guided by the system solutions providers in two projects in China during 2015-2018 government. In 2017, China accelerated batches. With the development of shows that 23.4 percent of the the implementation of pilots for smart "one center and one belt" smart investment falls in business and retail manufacturing, and special subsidies manufacturing industry cluster, sector and 18.3 percent in autonomous provided for smart manufacturing by Shanghai is gradually building up a driving, while AI investment related the government were also increasing world-class port industrial center and to manufacturing stands below one rapidly. In 2018, China implemented a suburban industrial belt (covering percent, and manufacturing is the 99 new pilot projects for smart Pudong, Minhang, Jiading, Baoshan, sector with the most potentials for AI manufacturing, of which 18 located in Songjiang and other districts) for smart application scenarios. Research finds the Yangtze River Delta region and 10 in manufacturing. that the deployment of AI could help the Beijing-Tianjin-Hebei region.
97 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-18: Distribution of key smart manufacturing enterprises in Shanghai
Jiading District Chongming District Yangpu District ROXZ—Power transmission and Zhida Technology—Smart charging distribution Anke Technology—New energy Re-Fire Technology—Fuel cells efficiency RENLE—Industrial control Luster Teraband—Visual imaging Putuo District Baoshan Shiele Intelligent Technology— Baoshan District Jiading District Intelligent building District I Ensnmax—Gas detection G H Shunhao Stock—Environmental Interlway—Industrial robot F packaging materials E A Qingpu D B District C Minhang District Pudong Xuhui District New Area Celi Engineering—Smart Minhang Basewin Intelligent—Smart equipment District burning Songjiang Argus—Prevention&treatment dyes Shanghai Ningyuan—Deep District hole machine tool R&D Fengxian District Jingan District Jinshan Chingmu—Infrared location tracking Changning District District FOTRIC—Thermal imaging equipment China Mingsheng Xinguang—New energy — Estepup Environmnetal Technology Pudong New Area Fengxian District Industrial three wastes UIROBOT—Industrial automation Huidu Environmental— Transcom—Silicon solar power Recyclable packaging materials Spreadtrum Conmmunications— Jinshan District Gehope Environmental— Mobile phone chips Austri Wind Power—Wind power safety Atmospheric protection
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: ITJUZI.com, Deloitte Research
98 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-19: Shares of smart manufacturing segments
100%
90%
80% 37.00%
54% 70%
60% 3.00%
13.00% 50% 0.12% 40% 15.00% 21.00% 30% 9%
20% 5% 14.00%
10% 17.00% 12.00% 0% 2016 2025E
Industrial robots Manufacturing IoT Manufacturing cloud (public) Manufacturing big data & business analytics Manufacturing AI Smart factory application/solution
Source: Markets and Markets Insights, Deloitte Research
99 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Manufacturing will become the blue sea for AI applications. The market size for applications of AI and related scenarios in manufacturing was around USD120 billion globally in 2016, and is expected to exceed USD720 billion by 2025, with a CAGR of more than 25 percent.
Figure 4-20: Smart manufacturing industry chain
Generative product Smart products design • Huawei • Vivo Products • AUTODESK • Oppo • Xiao I Robot • Rhinoceros • Xiaomi
Product QA Random sorting • Aqrose • Neptune • Riseye • COBOT Technology • Raystrong • Mech-Mind • Alsontech • Govion • NeuroBot Production & manufacturing
Production resources Production process Predictive production allocation optimization operation & • Haier • AInnvoation maintenance • CASICloud • SIASUN • WYSEngine
Material demand /sales Warehouse self- forecast optimization Supply • JD.com • Geek+ chain • Quicktron
Source: Public information, Deloitte Research
100 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Scenarios of AI application in phones in 2018, indicating huge market Take handling system as an example. manufacturing mainly include three potentials for smart products. The system assigns handling tasks categories. First, intelligent products Product quality control: Machine based on production demands, and R&D and empowerment of products vision recognition can be utilized to the robots will complete point-to-point with intelligence; second, leveraging AI to conduct fast scan on the quality of goods handling automatically. Robots improve product quality and productivity products, enhancing efficiency of transporting goods within a factory or in manufacturing and management quality control. With the ability to keep warehouse would detect obstacles and process; third, intelligent development of learning, the performance will be adjust moving routes to find the best supply chain. continuously improving over time. Auto routes. Machine learning algorithms parts companies have started to make would use logistics data, such as data of Smart products: Integrate and use of vision systems with machine materials in and out, stocks, turnover of commercialize AI technological learning algorithms to identify defective parts, etc., to facilitate self-optimization achievements to produce next- parts, including detecting defects and operation of warehouses. For generation smart products such that are not covered in the data sets example, algorithms may suggest as smart phones, industrial robots, used for training algorithms. AI vision to relocate parts with low demands service robots, autonomous driving technology company Bosaidong can further away, and place parts with high vehicles and drones. These products detect defects on the exterior of auto demands in surrounding areas with are the carriers of AI, with the ability electroplated parts with a high precision quick access. With focus on logistics to perceive and make judges through of 0.1mm; Aqrose applies AI and 3D robots and smart logistics solutions, combination hardware with various vision technologies in industrial quality Geek+ develops robotic sorting systems, software, and can interact in real time control and sorting, and completed an handling systems and sorting systems, with users and the environment. Take A-round funding raising of USD8 million leveraging robotic products and AI smart phone as an example. In addition in January 2018; Govion uses AI vision technology to offer smart logistics to the AI chip that enables it to run in quality control of screens, and has automation solutions. Robotic handling and respond faster, smart phone's completed an A-round funding raising of system utilizes moving robots to handle AI applications including smart voice RMB50 million; Raystrong focuses on the shelves/trays for automatic handling, assistant, biometric identification and quality control of textile fabrics. facilitating smart transformation with image processing also bring multi- enhanced flexibility of production, and dimensional smart experience for the Warehouse self-optimization: achieving automatic route planning user. Top four domestic phone makers, Smart carrier robots has significantly and loading/off-loading of shelves/trays i.e. Vivo, Xiaomi, Huawei and Oppo, have enhanced sorting efficiencies in for unmanned, smart handling within all launched their AI-featured flagship warehouses and reduced labor costs. factories and workshops.
101 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
4.8 Smart city: AI-based urban space, environmental destruction As one of the technologies to support infrastructure innovation system caused by repeated construction, the construction of smart cities, AI Different AI application scenarios potential danger from aging pipelines can be applied in urban infrastructure are integrated in a city. With the and lack of accurate operation and system to address a series of city application of AI and other cutting-edge maintenance data. As an effective development challenges and create technologies, urban infrastructure solution to pipeline-space conflict, utility healthy, low-carbon, safe and convenient are upgrading, fully supporting the tunnel is still in need of improvement city life. The application of AI can construction of intelligent cities. While in systematic planning and reasonable be piloted in key projects and then urbanization is accelerating, cities are charging mechanism. Logistics is expanded to cover all areas to establish facing many development challenges subject to high risks due to heavy an AI-based urban infrastructure such as dense population, energy reliance on manual sorting and innovation system. structure relying on limited energy types, distribution. Therefore, it is necessary low efficiency of resource distribution, to integrate technologies including big Shanghai is taking active initiatives risky transportation and logistics, low data, cloud computing and IoT with to establish a global leadership in AI garbage recovery rate and poor air urban infrastructure construction development, with great investment quality. These problems have stimulated to create innovative approaches to in the development of comprehensive the development of AI industry. logistics resources distribution. Such projects including Xuhui West Bound initiatives are expected to facilitate AI Tower, Zhangjiang AI Island, Maqiao As increasing urban population brings the application of information and Artificial Intelligence Innovation challenges for urban space and intelligent technologies in logistics Experimental Zone, Beiyang AI Town, resources distribution as well as safety and the establishment of standards Jiading Next-generation Data and and life quality, dense urban population and systems in the industry. China is AI Research Center and Dongjing AI is a compelling problem. China adopts lagging behind in waste sorting and Industrial Base. These projects can an energy structure relying heavily on recycling, compared with developed provide complementary advantages traditional energies such as coal and countries, exposed to various obstacles in AI innovation resources and natural gas. In response to the Paris to hazard-free treatment, recycling industrial base. For example, Maqiao Agreement on climate change, China and reduction of urban life wastes. Artificial Intelligence Innovation has vowed to put a peak on its growing These obstacles include waste recycling Experimental Zone, which consists carbon dioxide emissions by the year disorder, ineffective waste sorting and of industrial innovation development 2030. The world is paying increasing collection, rough garbage disposal and zone and comprehensive practice attention to climate improvement closed management system. Extensive zone, will establish extensive AI through energy structure changes. and long-lasting air pollution in China application scenarios to support urban The traditional independent network is threatening people's health and management, social governance and of resources distribution has caused may bring serious economic loss and livelihood service, etc., helping Shanghai vast problems concerning urban pressure to healthcare system. Air establish a leadership in AI development. infrastructure construction including quality control has become a matter of unreasonable use of underground concern for the society.
102 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
Figure 4-21: Distribution of comprehensive zones in Shanghai
Xuhui District Chongming District Pudong New Area West Bound AI Tower Zhangjiang AI Island Beiyang AI Town
Minhang District Jiading District Maqiao Artificial Intelligence Next-generation Data and AI Research Innovation Experimental Zone Center Baoshan Jiading District
District I G H Songjiang District F Dongjing AI Industrial Base E A Qingpu D B District C Pudong Minhang New Area District Songjiang District Fengxian District Jinshan District
A Huangpu District B Luwan District C Xuhui District D Changning District E Jing’an District F Putuo District G Zhabei District H Hongkou District I Yangpu District
Source: ASKCI Consulting, Deloitte Research
103 Global artificial intelligence industry whitepaper | 4. AI reshapes every industry
The urban infrastructure system When it comes to implementation, waste treatment to reduce greenhouse that applies AI mainly includes urban in terms of AI’ technological path gas emissions in the city and improve green space, transportation, logistics, in transportation, a new-type road the utilization of recyclable resources circulation, energy and other innovative classification system can be used in the with facilities and technologies including systems. comprehensive zones in the near term pneumatic automation system and to change the density of road networks waste sorting center. Green space system (intelligent and road sections. Besides, vehicle- water treatment-based park): infrastructure cooperative technology In the near term, urban comprehensive Green space system refers to an urban and smart parking technology can be zones can build intelligent waste sorting intelligent water management system also used to build smart scenarios for and anaerobic digestion of organic built for real-time response to the sharing mobility and self-driving taxi waste power generation systems and impacts of global climate changes on the system in a small range. And it can be pneumatic conveying system and kitchen urban water environment and ultimately expanded to the whole city in the future. waste disposal system for dry and wet achieve the goal of water saving and wastes, and integrate with intelligent recycling, environmental adaptability and Logistics (automated flow): The waste information monitoring and safe use. logistics system with automated flow management network for better control process aims to lower costs and and operation. In the medium to long During the implementation, sponge raise efficiency and safety. It applies run, incentives can be introduced in the city and rain garden technologies automated and intelligent technologies production and pre-sorting of wastes to should be deployed first in the urban to address the issue of “last mile” control sources and expand to the whole comprehensive zones combined with delivery, enhance logistics and delivery city. urban smart comprehensive corridors efficiency, lower costs and significantly to build a more mature operating and improve street and traffic environment. Sustainable construction (energy management models of the sponge city. system): Building a sustainable energy Additionally, the green space system can The case of Netherlands’ urban system aims to improve efficiency, be integrated with sewage and waste underground pipeline network can flexibility and reproducibility and disposal system and energy system to be used as a reference to specific achieve resources saving and recycling fulfill the principle of circular economy. practices. In the near future, pipes for by leveraging technologies including And it can be further expanded to the underground logistics systems can be distributed energy, waste water heat whole city to ensure that the city is able reserved in the urban comprehensive recovery pump, combined cooling to navigate the water environment crisis zones for installing wireless charging heating and power, microgrid and energy led by global warming through various infrastructure. And a small range of storage technology. measures. test run is implemented based on mature supporting technologies. In the In the near term, urban comprehensive Transportation system (user- medium to long term, the city can work zones combine waste water heat friendly mobility): In the future smart with established logistics companies recovery pump and waste incineration city, the needs of human and city will to design a robot distribution system power generation technologies to create be taken as a starting point to actively and build on existing technologies to an energy chain that is aligned with the respond to the development of future AI develop technologies that can extend principle of circular economy. Renewable technologies, build various application the networks of underground logistics energy, including solar energy and wind scenarios for smart transportation and system to the whole city. energy, can be provided for the starting create a more effective, dynamic and zone first and distributed energy for sustainable smart mobility system. Circulation system (solid waste integrated functional areas. And the use treatment): It is aimed at achieving of renewable energy can be extended to recycling, reducing and harmless solid the whole city in the medium to long run.
104 Global artificial intelligence industry whitepaper Deloitte China Contacts
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