The document discusses several topics related to artificial intelligence and robotics. It describes how the global market for robots and AI is expected to reach $152.7 billion by 2020. It also discusses advances in machine learning, cloud computing, big data, and cognitive computing that are driving growth in AI. Finally, it notes both the opportunities and challenges of integrating AI and robotics technologies across various industries like healthcare, transportation, and manufacturing.

1. July 2016
한상기

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3.  The total global market for robots and artificial intelligence will reach $152.7
billion by 2020 -- “Robot Revolution – Global Robot & AI Primer” by Bank of America Merrill Lynch
Global Research (Dec. 16, 205)
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[출처: Postscapes and Harbor Research] [출처: McKinsey Global Institute]

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6.  딜 숫자는 줄고 펀딩 규모는 늘었음
 산업 IoT, 헬스케어 IoT는 증가, 웨어러블은 냉담해짐
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8.  Advance of Powerful and Cheap Hardwares
 Machine Learning and Deep Learning Technologies
 Cloud Computing and the Availability of Big Data
 Digital Interconnection of People
 The Beginning of Cognitive Computing and The
Research on Neuro-morphic Computing
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9.  The future of IoT is cognitive, the cognitive of IoT: think, learn, understand
 Digital is not a destination, it’s a foundation
 New era of Cognitive Computing -- Data is visible now, advent of cognitive
computing
 Watson – 32 functions, 52 technologies, cloud platform, 36 countries,
80,000 programmers
 Watson IoT business
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[출처: Wired]
[출처: MIT Technology Review]

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“DeepFace” to
detect whether two
faces in unfamiliar
photos are of the
same person with
97.25% accuracy,
regardless of
lighting conditions
or angles.
[출처: TechCrunch]
[출처: Fortune]

12.  Image Recognition Market worth 29.98 Billion USD
by 2020 – MarketsandMarkets
 시각은 인간이 가진 감각기관 중 가장 편리하면서도
반복적으로 사용하는 정보입력기관
 이미지 검색은 이미지 이해를 통해서 고도화 - 구글
 이미지를 통한 관계, 취향, 행동 분석 – 페이스북
 자율 주행차의 기본 기능
 시각 장애인을 위한 사회적 기능
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[출처: Network World]

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16.  Apple Siri, Google Assistant, MS Cortana, Amazon Echo
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[출처: 각 회사 웹사이트]

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[출처: Google]
[Uber and Facebook]

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[출처: Context Aware
Computing for
The Internet of Things:
A Survey]

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[출처: Wired, 2013. 8]

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[출처: Google]
[출처: The Guardian]

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31.  Creating (and maintaining) maps for
self-driving cars is difficult work
 Driving requires many complex
social interactions
 Bad weather makes everything
trickier
 We may have to design regulations
before we know how safe self-
driving cars really are
 Cybersecurity will likely be an issue
— though a surmountable one
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• If a construction worker uses hand gestures to tell a car to either go or to
stop, no autonomouscar today can reliably make the right decision.
• When the sun is immediatelybehind a traffic light, most cameras won’t
be able to recognize the color of the signal through the glare.
• If we see a truck with a “Makes Wide Turns” sign, we know how to adjust
our driving accordingly. If we see children distracted by the ice cream
truck across the street, we know to slow down, as they may dash toward
it. Today’s computers aren’t nearly as skilled at interpreting complex
situations like these.

32.  In the manufacturing industry,
we’re seeing connected devices
open up new ways of data sharing
that were not previously possible.
Now, small sensors on pieces of
complex machinery can emit data
about performance status that can
then be used to adjust scheduled
maintenance. With this data, teams
can predict maintenance failures,
proactively prevent them and
ultimately reduce down time.
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33.  2015년 2014년에 비해 83% 증가
 Linking sensors to machinery : Samsara
 Laying down technical infrastructure and cloud services: Sigfox, Arrayent,
 Helping companies spin the data into useful insights on the backend : Sight
Machine, Uptake Technologies
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One of the largest deals in
2015 was to IoT networking
company SigFox, which held
a Q1’15 $115M Series C that
included a host of corporate
backers including Intel
Capital, Samsung Ventures,
SK Telecom Ventures,
Telefonica Ventures, Air
Liquide, Engie, and Eutelsat
Communications.

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36.  Navigant 리서치에 의하면, 글로벌 스마트 도시 기술 시
장은 2012년 61억 불에서 2020년 202억 불로 성장 예상
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37.  The AI market for healthcare applications is expected to achieve rapid
adoption globally, with a CAGR of 42% to reach $6.6 billion in 2021 until 2021
-- Frost & Sullivan’s Transformational Health program
◦ Provide physicians and researchers with clinically relevant, real-time, quality
information sourced from data stored in electronic health records (EHRs) for
immediate needs
◦ By 2020, chronic conditions, such as cancer and diabetes, are expected to be
diagnosed in minutes using cognitive systems
◦ By 2025, AI systems are expected to be implemented in 90% of the U.S. and 60% of the
global hospitals and insurance companies
◦ AI systems will deliver easily accessible, cheaper and quality care to 70% of patients.
 일본 의사 10명 중 7명은 향후 20년 이내에 인공지능(AI)이 환자의 진료를
담당할 것이라고 예상했다 - 니케이신문
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Distinguished leaders in healthcare already working with
IBM Watson include Memorial Sloan Kettering Cancer
Center, the Mayo Clinic, New York Genome Center,
Cleveland Clinic, and The University of Texas MD Anderson
Cancer Center
for $2.6 billion

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“Chris actively used his 5Star for six days last
week and could contact help if needed during
that time. He spent time at the farmer’s market,
his daughter’s home and the coffee shop. He
did a great job of charging the device regularly,
never letting the battery power fall to a low
level.”
“Mary Clare actively used her 5Star for three
days last week and could reach an operator if
needed during that time. However, she didn't
actively use her device for four full days. She
may need a reminder that it is important to
carry her device at all times, guaranteeing that
support is available when needed.”
“Edward made four total calls to GreatCall last
week, including an important one to notify 911.”

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[출처: Let’s Talk Payments]

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Advanced Analytics
Wealth Management for the massses
Fraud Detection

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JIBO

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[출처: Kate Darling, MIT]

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“Establish a good working
relationship between the
people working on AI and the
people who are thinking about
safety issues”
[출처: MIT Technology Review,
the Guardian, Backchannel.com]

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[출처: TechCrunch]
[출처: MIT Technology Review] [출처: Bloomberg]

51.  Support research into mitigating algorithmic
discrimination, building systems that support fairness
and accountability, and developing strong data ethics
frameworks
 Encourage market participants to design the best
algorithmic systems, including transparency and
accountability mechanisms such as the ability for
subjects to correct inaccurate data and appeal
algorithmic-based decisions.
 Promote academic research and industry development
of algorithmic auditing and external testing of big data
systems to ensure that people are being treated fairly.
 Broaden participation in computer science and data
science, including opportunities to improve basic
fluencies and capabilities of all Americans.
 Consider the roles of the government and private sector
in setting the rules of the road for how data is used.
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[Source: McKinsey Global Institute]
[Source: Altimeter]
• Different OEMs: devices or equipment that are not made by the
same manufacturercan cannot integrate
• Different OSs: inability to run on the same operating systems
• Different versions or times of purchase: devices that weren’t
made or purchased at the same time
• Different/incommunicable types of connectors or connectivity
frameworks (e.g. devices)
• Different/inconsistent communication protocol standards (i.e.
rules)
• Lack of programmability needed to connect in the first place

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56.  The FTC also recommended that IoT companies should
reasonably limit their collection and retention of
PII. These practices, known as data minimization, can
help mitigate privacy-related risks. The FTC
recommended that:
◦ IoT companies should examine their data practices and business
needs and develop policies and practices that impose reasonable
limits on the collection and retention of PII; and
◦ to the extent there is a need to collect and store PII, IoT
companies should consider whether they can do so while
maintaining the PII in a de-identified form.
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58.  “an insurance company might want to know its customers’
moods — so it can raise their fees if they show signs of
becoming depressed or sick”
– Clive Thomson, author of “Smarter Than You Think:
How Technology Is Changing Our Minds for the Better
 “Tracking how our bodies are responding throughout the day
could allow you to tailor your life according to what’s
happening to your body throughout the day. It could allow
nutritionists to carefully build meal plans for clients, or for
doctors to come up with more efficient medical treatments.”
-- Prerna Gupta @ Smule
 Employers might want to know when their staff members are
bored at work or in the meeting
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61.  The FTC also recommended that IoT companies should
reasonably limit their collection and retention of
PII. These practices, known as data minimization, can
help mitigate privacy-related risks. The FTC
recommended that:
◦ IoT companies should examine their data practices and business
needs and develop policies and practices that impose reasonable
limits on the collection and retention of PII; and
◦ to the extent there is a need to collect and store PII, IoT
companies should consider whether they can do so while
maintaining the PII in a de-identified form.
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[출처: The Guardian]

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[Carry by dispatch.ai]
[출처: MIT Tech Review]

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[출처: Newsweek] [출처: gizmag.com]
[출처: 저작권보호센터]

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“Kiva’s robots have already helped Amazon cut operating expenses by a
massive 20%. If Kiva robots are dispatched to the rest of the 110 Amazon
warehouses, the tech giant could save almost $2.5 billion” -- Deutsche Bank

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75.  AI 시스템이 자연인과 법인에 이어 행위 주체와 함
께 권리 주체가 될 수 있는가?
 로봇과의 섹스 등 사용자들의 행동에 대한 사회적
담론은 어떻게 해야 하는가?
 로봇과 인간이 공존하는 사회 시스템은 어떻게 진화
할 것이며, 로봇끼리 이루는 사회는 어디까지 허용
할 것인가?
 로봇의 자기 복제나 자체 제작의 허용 여부
 ‘Big Red Button’의 의무화
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