Future Watch: China's Digital Landscape and Rising Disruptors - Module 2.6 Artificial Intelligence

OTSIKKO
ALAOTSIKKO, KUUKAUSI VUOSI
CHINA’S DIGITAL LANDSCAPE AND RISING DISRUPTORS
MODULE 2.6
ARTIFICIAL INTELLIGENCE

AUTHORS
Dr. Edward Tse
Founder and CEO
Team Finland Future Watch Report, August 20172
Mr. Bill Russo
Managing Director and Auto Practice Lead
Mr. Alan Chan
Senior Consultant

Artificial Intelligence
TOPICS
1. WHAT IS AI? WHY NOW?
2. CHINA’S AI STATUS AND INNOVATORS
3. FUTURE OPPORTUNITIES AND IMPLICATIONS FOR TEAM FINLAND

How to define “intelligence”?
Can machines be “intelligent”?
WHAT IS AI? (1/2)
Source: Literature research, Gao Feng analysis
Artificial General Intelligence (Strong AI)
 Human-level intelligence across the board
 A machines that can perform any
intellectual task that human can
 Ability to reason, plan, solve problems,
think abstractly, comprehend complex
ideas, learn quickly, and learn from
experience
Artificial Super Intelligence (ASI)
 “An intellect that is much smarter than
the best human brains in practically every
field, including scientific creativity, general
wisdom and social skills.”
 Independent world view and values
Artificial Narrow Intelligence (Weak AI)
 Specializes in narrow applications only
First definition of AI
 By John McCarthy, Professor, Dartmouth College,
1956
 “Every aspect of learning or any other feature of
intelligence can in principle be so precisely described
that a machine can be made to simulate it”
Modern definition
 The science and engineering of "intelligent agents“ -
any device that perceives its environment and takes
actions that maximize its chance of success at some
goal
Path to Artificial Super Intelligence
Defining AI
Singularity? What AI can/can’t do?

WHAT IS AI? (2/2)
Source: Waitbutwhy, Rapidminer, Literature research, Gao Feng analysis
 Any technique which enables
computers to mimic human
behavior
Machine Learning
 Subset of AI techniques which use
statistical methods to enable
machines to recognize patterns
and improve with experiences
Deep Learning
 Subset of ML which uses
complex neural networks to
make the computation of multi-
layer neural networks feasible
Understanding the key terminologiesThree key layers of AI
Applications
 Industrial robots, chat bots, fintech, smart
healthcare, autonomous driving, smart home
appliances, etc.
Core Technologies
 Computer vision, speech recognition, natural
language processing, machine learning, deep
learning, etc.
Infrastructure
 Data, sensors, biometrics, graphics processor
chips, cloud computing
What does it mean to your industry?

AI IS DISRUPTING INDUSTRY BY INDUSTRY
Source: Gao Feng analysis
Go game
Texas Hold’em Poker
Automotive
Healthcare FinTech
Many more…
“AI will transform industries just as electricity
transformed almost everything 100 years ago”
Andrew Ng,
Former chief
scientist at Baidu,
founder of Coursera
and Google Brain
AI is not a futuristic
concept and many
practical AI applications
are already available
today, such as Facebook
newsfeed, Google search
results, Amazon product
recommendations,
LinkedIn Ads, iPhone siri,
photo-editing/tagging…
etc.

AI HAS A LONG HISTORY OF BEING “THE NEXT BIG THING”…
Augmented Reality (AR)
Source: Literature review, Gao Feng analysis
1950 1956 1974 19931980 1987 Time
Birth
Inflated
Hype
AI winter I
New Hopes
AI winter II
Explosive
Growth
Popularity
Timeline of AI Development
 1950s-1960s: First AI boom - the
age of reasoning, prototype AI
developed
 1970s: AI winter I
 1980s-1990s: Second AI boom: the
age of Knowledge representation
(appearance of expert systems
capable of reproducing human
decision-making)
 1990s: AI winter II
 1997: Deep Blue beats Gary
Kasparov
 2006: University of Toronto
develops Deep Learning
 2011: IBM’s Watson won Jeopardy
 2016: Go software based on Deep
Learning beats world’s champions

... BUT THIS TIME IS DIFFERENT
Source: Wired, Gao Feng analysis
1. Cost-effective High Performance Computing
 Graphics Processing Units (GPUs) (and Tensor Processing
Units): Discovery of using GPUs (originally used for generating
computer graphics in video games) to build and run parallel
neural networks, the primary architecture of AI software
2. Better Algorithms
 Breakthrough developments
in Artificial Neural Networks
(ANN) – to model the
network of nerve cells in a
human brain on a computer
3. Abundance of Data
 Massive databases, self-
tracking, web cookies, online
footprints, terabytes of storage,
decades of search results,
Wikipedia, etc. as raw materials
to train learning machines

YET, THERE ARE MIXED VIEWS TOWARDS THE FUTURE OF AI
"The development of full
artificial intelligence could
spell the end of the human
race."
-- Stephen Hawking
“I think we should be very
careful about AI. If I had to
guess at what our biggest
existential threat is, it’s
probably that.”
-- Elon Musk
“There could be a race of killer
robots in the far future, but I
don’t work on not turning AI
evil today for the same reason
I don't worry about the
problem of overpopulation on
the planet Mars”
-- Andrew Ng
“All new technologies present
the possibility for misuse. AI is
no different. And even
technologies that are a clear net
positive for humanity have
negative side effects that should
be understood and dealt with
thoughtfully.”
-- Astro Teller
“It seems probable that once the
machine thinking method had
started, it would not take long
to outstrip our feeble powers…
They would be able to converse
with each other to sharpen their
wits. At some stage therefore,
we should have to expect the
machines to take control.”
-- Alan Turing
Neither hyped nor alarmed, we should carefully examine the new economic opportunities and the threats brought
by AI; the development of AI must address the risk of potential misuse and widening inequalities

TOPICS

CHINA WILL BECOME A MAJOR DRIVING FORCE OF THE NEXT AI
REVOLUTION
Source: 36Kr, iiMedia, Gao Feng analysis
10.2
6.3
3.7
2.1
1.1
63%
69%
94%
108%
0
5
10
15
20
25
30
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
202220212018 2019
77%
2020
YoY Growth Rate Market Size
China AI Market Size
2018E-2022E, USD BnUSD Bn %
83
132
136
160
173
228
233
366
709
2,905
Switzerland
Spain
France
UK
China
US
Germany
Israel
Canada
India
Total Number of AI companies
Unit: Thousands, 2016

CHINA HAS THREE UNIQUE ADVANTAGES TO BECOME A GLOBAL LEADER
IN AI
 AI-related policies: 13th Five-year
Plan (March 2015), Internet Plus,
Made in China 2025 (May 2016),
Robotics industry Development
Plan (April 2016), Three-year
Guidance for Internet Plus AI Plan
(May 2016)
 March 2017 – China’s highest
national meeting included AI in the
Government Work Report for the
first time
 Vast data gold mine from over
730M of online population
 Tencent’s WeChat has almost
940 million users worldwide
and Alibaba Group has more
than 420 million active buyers
on Taobao
 Chinese patent applications in
the AI segment grew to 8,410
between 2010 and 2014, a
186% increase from the
previous 5-year period between
2005 and 2009
 China has a large pool of young
mathematics, science and
engineering graduates
 Abundance of funding
Big data Innovation Ecosystem Government Push

CHINA HAS LEAPFROGGING DEVELOPMENT IN TERMS OF AI RESEARCH
AND DEVELOPMENT
Source: 36Kr, SCImago Journal Rank 2015, Vertex, Washington Post, Wuzhen Institute, Gao Feng analysis
Global AI citation ranking
By number of AI publications cited
2015
637 692
388
424
444 200
237
267199
1,487
504
UKChina
2,124
Spain
588
India
643
US
1,116
Self-citations
Other citations
Journal articles cited at least once, mentioning
“deep learning” or deep neural network”
2015
The no. of academic research papers published in
China in the field of deep learning exceeded the US
China is ranked first for absolute AI citations and
third based on publication influence

AI DEVELOPMENT IN CHINA IS CURRENTLY FOCUSING ON A FEW MAJOR
PRACTICAL APPLICATIONS
Source: 36Kr, Gao Feng analysis
Others
6%
Data services
3%
Vertical applications
3%E-commerce
3%Fintech
4%
Smart Education 4%
Personal Assistant 4%
Smart Home 5%
Machine Learning
6%
Smart Driving
6%
Smart Health
7%
Natural Language Processing
11%
Service Robotics
20%
Computer Vision
21%
Distribution of China AI Start-ups, 2017 Investment received in China by segment
Accumulated sum, 2017 Jan, RMB Bn
0.6
0.7
0.8
1.6
2.0
2.8
Smart
Driving
Smart
Security
Smart
Home
Computer
Vision
RoboticsNatural
Language
Processing
China’s AI start-ups are focusing
on a few key applications
China’s AI–related investments are also very focused
on a few areas of specialization

AS A DIGITAL-SAVVY SOCIETY, THERE IS A RELATIVE HIGH CONSUMER
AWARENESS OF AI IN CHINA
Source: iiMedia Consumer Survey, Gao Feng analysis
47% "So-so"
"Never heard of AI"
"Know little"
6%
20%
"Know AI well"
24%
"Know AI very well"
5%
“How well do you know AI?” “Where do you get to know AI?”
4%
7%
13%
29%
41%
75%Online media
Traditional media
Literatures
Cultural products
Others
Institutional reports
Majority of Chinese consumers are aware of AI
Chinese consumers learn about the concepts of AI
mostly from online sources

CHINESE CONSUMERS ARE OPTIMISTIC ABOUT THE FUTURE OF AI AND
ARE AWARE OF THE NEED TO NURTURE AND ATTRACT MORE AI TALENTS
Source: iiMedia Consumer Survey, Gao Feng analysis
“Do you think AI has more advantages or
disadvantages?”
59% "More advantages"
"No advantages"
"Equal" 2%2%
"More disadvantages"
31%
"No disadvantages"
18%
Chinese consumers are in general very optimistic
about the future of AI
47% "Necessary"
"Not that necessary"
"No need" 2%2%
"Very necessary"
31%
"No clear view"
18%
“Is it necessary to provide more education on AI?”
Chinese consumers are aware of the AI talent gap

CHINA’S AI MARKET LANDSCAPE
Source: iiMedia Research, Gao Feng analysis
Sensors
Chips
Industry Data Data Services
Biometrics Cloud Computing
Infrastructure
Layer
Core
Technology
Layer
Machine Learning Natural Language Processing Computer Vision
Application
layer
Industrial Robots Service Robots Smart Health Care Internet Finance
Personal Assistant Smart Security Smart Home Wearables
Precise Marketing Autonomous vehicle Logistics Vertical applications
NOT EXHAUSTIVE

THERE IS AN EXPANDING POOL OF AI TALENTS IN CHINA
Lu Qi
Group President and
COO, Baidu
Former Microsoft EVP
In general, Chinese AI scholars are more focused on the pragmatic applications and
use cases of AI while their counterparts in the US focus on fundamental research
Zhang Tong
Executive Director,
Tencent AI lab
Former head of Baidu
Big Data Lab
Wang Gang
Chief Scientist,
Alibaba AI Lab
Wang Jun
Founder, iCarbonX
Former CEO, Beijing
Genomics Institute
Li Hang
Huawei Noah Ark Lab
Zhao Feng
CTO and VP for
advanced R&D and
smart home
Haier
Sun Jian
Chief Scientist, Megvii
Former Partner Research
Manager, Microsoft
Yang Qiang
Chair Professor, Dept Head
of Computer Science &
Engineering, HKUST
Wang Haifeng
Head of AI
Group, Baidu
Zhou Jingren
Chief Scientist and
Vice President of
Alibaba Cloud
Ye Jieping
President, Didi
Research
Yu Kai
Founder & CEO,
Horizon Robotics
NOT EXHAUSTIVE

CHINESE TECH GIANTS ARE MAKING BIG BETS TO TAKE LEAD IN THE AI RACE
 Baidu Brain, an AI
platform with over 60
different AI-enabled
services
 DuerOS: natural
language-based,
conversational-based
human computing
platform, penetrating
over 100 home
appliance brands
 Apollo: open platform
for self-driving car
solutions
 Deep Interest Network:
Advanced personalized
recommendation engine
 DT PAI (Platform of Artificial
Intelligence) launched in
August 2015
 Ali Xiaomi: a virtual
personal secretary for
shopping and O2O services
 Alibaba City Brain: leverage
Ali Cloud big data and deep-
learning technologies to
build 'city brains' in
cooperation with Hangzhou
and Macau governments
 Tencent AI lab: 50 world-
class AI scientists,
researchers and experts
 WeChat-HKUST Joint Lab
for pioneering research
based on WeChat data
 ‘Fine Art’ AI: developed
by 13 Tencent
engineers, defeated high-
ranking Japanese Go
player Ryo Ichiriki this
year
 Launched DiDi Labs
primarily focusing on AI-
based security, advanced
service dispatch algorithm,
intelligent driving
technologies
 Huawei Noah’s Ark
Laboratory and Berkeley
Research (BAIR) formed
partnership on
development of machine
learning, AI and data
mining
CASE EXAMPLES

MOBVOI IS A LEADING AI START-UP FOCUSING ON VOICE RECOGNITION
AND NATURAL LANGUAGE PROCESSING IN CHINESE CONTEXT
CASE EXAMPLE
 Company mission: To define the next generation of human-
machine interaction (HMI) through advanced AI technologies
Ticwatch
(Smart Watch)
Ticmirror
(In-vehicle
Robot)
Tichome
(AI Speaker)
Chinese language
recognition
Accurate
vertical search
engine
Real-time
proactive
search
Semantic
analysis
Text-to-speech
technology
Services
(Applications)
Software
(AI Technology)
Hardware
(Products)
…
POI
recommendation
Real-time
traffic alert
Movie ticket
booking
Restaurant
reservation
Food delivery
Health
monitor
Use cases Key enablers User experiences
Source: Mobvoi official website, Crunchbase, Gao Feng analysis
Business model
Company Facts
 Founded in October 2012
 Raised USD 252M from
ZhenFund, Sequoia Capital,
SIG China, Google, and
Volkswagen Group
 Founded by Li Zhifei Li,
former research scientist at
Google and a world-class
natural language processing
expert
 In Apr. 2017, Volkswagen
Group China and Mobvoi
announced a strategic
partnership and a 50:50 JV
to develop AI applications for
future connected cars

TOUTIAO IS A NEW UNICORN PROVIDING CURATED NEWS AND CONTENT
Source: Toutiao, Financial Times, Literature research, Gao Feng analysis
Competitive advantages in
content generation, distribution and monetization
Toutiao’s exponential growth
Basic facts:
 By analyzing the features of content, users and users’
interaction with content, Toutiao’s AI-powered
algorithm models generate a tailored feed list of
content for each individual user
 Now valued at USD 20Bn (from USD 500M in 2014)
 Launched in August 2012 based in Beijing
 Founder: Zhang Yiming
 100M daily active users in 2017Q1
 Average daily usage time: 76 mins
 Hired Ma Wei-Ying, former assistant managing
director of Microsoft Research Asia, to lead its AI Lab
 User-generated and professional-generated
content in various media forms: text, short
videos, Q&As
 Provide incubator and media lab services for
curated content makers
 AI-generated content live feed
 Understand user’s emotions and behavioral
characteristics through machine learning,
analyze and predict user’s profile
 Personalized news content – “Thousand
people, thousand interfaces”
 Technology barrier: Leverage big data to
accumulate user understanding overtime
11
46
335
107
141
507
2016H22015H2
Total length of read (Billion mins)
Total no. of read (Billion)
No. of articles (Million)
Content
Generation
Content
Distribution
Content
Monetization
 Business model: Personalized newsfeed ads,
re-direct traffic to E-commerce sites
 Earned USD 869M in 2016 from in-app ads
with the goal to reach USD 10Bn by 2020
CASE EXAMPLE

MEGVII (FACE++) IS A FAST-GROWING COMPUTER VISION START-UP THAT
HAVE PENETRATED INTO A WIDE RANGE OF USE CASES
Source: Megvii official website, Gao Feng analysis
Company Background
 Founded in 2011, Megvii is a computer vision firm that aims to power human with AI. It has developed leading technologies in
facial recognition, body recognition, and object recognition
 Megvii raised USD 147M in 4 rounds from 6 investors, including Sinovation Ventures, Qiming Venture Partners, and Foxteq Holdings
 Megvii focuses on commercializing its facial recognition technology in Internet finance, banking, ride hailing sectors, and also its
body and object recognition technologies in intelligent real state and intelligent security areas
 Ranked 11th in the “50 Smartest Companies of 2017” of MIT Technology Review
CASE EXAMPLE
Face Comparing
Face Attributes
Emotion recognition
Face Detection
Face Landmarks
Gaze estimation
Face Searching
Beauty score
Body Detection Gesture Recognition
Body Attributes
Body Outlining
Key technologies Key customers (examples)
 User authentication
 Smile to Pay
 Driver verification for
ride hailing service
 Photo beautification with automatic
makeup and beauty effect
 User authentication for self
banking services

IFLYTEK IS A LONG-ESTABLISHED AI COMPANY SPECIALIZED IN SPEECH
AND LANGUAGE PROCESSING TECHNOLOGIES
*As of August 17 2017
Source: iFLYTEK official website, 36Kr, Gao Feng analysis
Company Background
 Founded in 1999, iFLYTEK is the leader in intelligent speech and language processing technologies in China
 Listed in Shenzhen Stock Exchange in 2008, and now with a market cap of ~USD 12B*
 Achieved international advanced technologies in many areas including speech recognition, speech synthesis,
natural language processing, oral language evaluation, voiceprint recognition, and handwriting recognition
 Ranked sixth in the “50 Smartest Companies of 2017” of MIT Technology Review and first among all Chinese
companies in the list including Alibaba and Baidu
easy trans
600
CASE EXAMPLE
Smart Education Smart Home Smart City
Smart Vehicle Smart Health
Care
Key application industriesKey products Key customers
Voice
Assistant
iFLYTEK
input
One-stop HMI
solution platform
Bilingual education
products

THERE IS A MYRIAD OF EMERGING CHINESE AI START-UPS FOCUSING ON
HEALTHCARE, ROBOTICS, AUTONOMOUS DRIVING AND OTHERS
Source: Company official websites, Crunchbase, Gao Feng analysis
 Founded in 2015 and raised USD 200M in 2 rounds from
3 investors, including Tencent and China Bridge Capital
 In Feb.2017, iCarbonX was selected by Fortune as one
of the “50 Companies Leading the AI Revolution”
 Founded in 2014 and received USD 410M series B
funding in Aug. 2017 with a valuation of USD 1.1B
 Computer vision and deep learning solution provider
 Ranked fifth in China Money Network's China AI Top 10
Ranking in 2017
 Founded in 2015, focusing on commercialized
autonomous truck technology solution
 Facilities in both Beijing and San Diego
 Received USD 20M investment from NVIDIA and Sina
 Founded by Wu Gansha, former chief engineer at Intel
Labs China, in 2016
 Building commercialized solutions for self-driving
technologies, products and services
 Turing Robot is the most intelligent robot brain tailored
for the Chinese language context
 Building the most leading AI robot operating system in
China and globally
 Founded in 2007 and raised USD 45M in 3 rounds from
3 investors, including Legend Star and TusPark Ventures
 AISpeech has 7 national qualifications, 25 patents, and
23 software copyrights
Digital health ecosystem Speech recognition and analysis
Deep learning AI robotics
Autonomous Driving Autonomous Driving
To compete with tech giants, AI start-ups must tailor their technologies and solutions to
focus on specific use cases and build big data capabilities as competitive advantages
CASE EXAMPLES

TOPICS

FINLAND HAS PUT AI AS ONE OF THE TOP NATIONAL STRATEGIC PRIORITIES
Prime Minister
Juha Sipilä
 Making Finland the world
leader in artificial intelligence
 Called for a common national
vision to make effective use of
AI in society
 Using AI to boost wellbeing
will require not only new
competences but also novel
approaches, forward-thinking
decisions and frameworks,
and an adaptive labor market
Minister of Economic Affairs
Mika Lintilä
 To make Finland the best in the
world in applying AI and
renewing ways of working
 Established an AI-focused
steering group in May 2017,
program ready by September
 “Finnish companies and Finnish
society have an excellent basis
to turn the challenges and
opportunities brought about
by AI into accelerators of
sustainable growth”
Director General National Agency
for Education
Olli-Pekka Heinonen
 Important to take AI into
account in education
 AI applications could for
example be used to create more
efficient ways to identify and
help students at risk of dropping
out

 IBM opened The IBM Watson Health
Center in Helsinki, Finland
 A hub for the collaborative future
development of data-driven cognitive
and artificial intelligence applications
and solutions for Finnish healthcare
THERE IS AN INCREASING AMOUNT OF AI START-UPS AND AI-ORIENTED
INITIATIVES IN FINLAND
Source: Literature research, Tekes, Gao Feng analysis
Claned
 Leverage AI and education
psychology to enhance
personal learning
 Personalizes learning to
each individual optimizing
study motivation and
improving learning results
Curious AI
 Founded 2015 as a
spin-off from Aalto's
Deep Learning
Research Group
 Specialized in the
fundamental research
on unsupervised AI
Zen Robotics
 Specialized in AI-
controlled robotic
systems
 Next Generation
Recycling – leader
in robotic waste
separation
IBM and Tekes
Blueprint Genetics
 Addresses the main
bottleneck of genetic testing
through next-generation
sequencing (NGS) powered
by AI
 Received EURO 14M in July
2017
"I am positive that Watson cognitive
capabilities will further boost innovation in
Finland and put us at the forefront of game-
changing health transformation, at the
European level and in the global
marketplace.“
- Pekka Soini, Director General of Tekes
CASE EXAMPLES

TO MAXIMIZIE ITS FULL POTENTIAL IN AI, FINLAND HAS EXISTING
COMPETITIVE ADVANTAGES TO LEVERAGE AS WELL AS GAPS TO CLOSE
Competitive advantages of AI in Finland
 High level of technology-related
education and skills
 Strong collaboration between
companies and universities (VTT)
 Innovation ecosystem that allows a
trial-and-error
 Legacy in applied and fundamental AI
research – with legends such as Teuvo
Kohonen and Erkki Oja
Gaps to close
 Talent gaps – technical and business
leaders who understand both sides
 Getting ready for AI – businesses to
begin data acquisition and investigate
the future benefits of AI in driving
productivity and reducing costs
 National strategy – to set national
priorities and leverage AI as a
economic multiplier to accelerate AI
transformation

FINLAND SHOULD TAKE IMMEDIATE ACTIONS TO CAPTURE THE
EXPOLSIVE OPPORTUNITIES IN AI
Potential actions
Education
 Offer AI-specific curriculum at the top local universities and STEM education in high schools
 Hold public events for mass to understand and discuss the basic concepts, benefits and risks of AI
 Openly engage with consumers and understand needs and pain points that can be potentially
addressed by AI technologies
R&D
 Call for more novel applications and research on AI
 Set up AI-specific funds and incubators to accelerate the development of Finnish AI ecosystem
Businesses
 Leverage Finland’s traditional industries including the clean energy, forestry, industrial machinery
and processes, medical and ICT, and empower their AI transformation
 Provide continuing education on AI-related courses for all kinds of workforces
 To explore new applications of AI and identify potential use cases and profit potentials
Global ecosystem collaboration
 Establish cross-border linkages to encourage global knowledge transfer and benchmark global best
practices; set up overseas AI labs to attract high-skilled talents
 More detailed national strategy on AI and government funding for quality AI research and start-ups

Future Watch: China's Digital Landscape and Rising Disruptors - Module 2.6 Artificial Intelligence

Future Watch: China's Digital Landscape and Rising Disruptors - Module 2.6 Artificial Intelligence

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Future Watch: China's Digital Landscape and Rising Disruptors - Module 2.6 Artificial Intelligence