24차 창조경제연구회 공개포럼

289
Contents 2015년 창조경제 24차 포럼 보고서 인공지능과 4차 산업혁명 1. 공고문················································································ 1 2. 연구회 소개········································································ 5 3. 발표자료··········································································· 11 4. 보고서·············································································· 87 5. 기고문············································································ 271 6. 기부금············································································ 285

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  • Contents2015 24 4

    1. 1

    2. 5

    3. 11

    4. 87

    5. 271

    6. 285

  • 1

    1.

  • 1.

    3

    24

    4 1 20 2020 700

    , 1/3 . . .

    4 . . 1) 2) 3), , IBM (Open -source) . 4) 5) . 6) .

    4 ()( ) , , . 4 . .

    : 2016. 3. 29() 14:00~16:30 : KT 1 ( 100) : () : http://onoffmix.com/event/63139

    14:00~14:05 (, )

    14:05~14:35 ()

    14:35~15:00 ()

    15:00~15:25 4

    15:25~16:10

    () ()

    () ()

    ( ) (IBM)

    16:10~16:25

    16:25~16:30 /

    28 25 Tel:02-577-8301 |Fax: 02-577-8302 | [email protected] | http://kcern.org

  • 5

    2.

  • 2.

    7

    2009

    .

    .

    . ,

    ,

    .

    .

    .

    .

    ,

    .

    .

    . .

    . 1.0

    , 2.0 . IT

    . 5

    .

    .

    .

    .

  • 4

    8

    .

    .

    . SNS

    .

    (Think

    Network) .

    .

    .

    , , , , ,

    . 1 KIST, ,

    , , 2 ,

    .

  • 2.

    9

  • 11

    3.

  • 3.

    13

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    14

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    15

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    83

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    85

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    86

  • 87

    4.

  • 4.

    89

    24

    4

    2016. 3. 29

  • 4

    90

    2016 24

    : 4

    : ()

    :

    :

    : 2016. 3. 29.

    :

    :

    :

    :

  • 4.

    91

    . 97

    1. 97

    2. 100

    3. 103

    4. 105

    5. 6 107

    6. 113

    . 117

    1. (AI, Artificial Intelligence)? 119

    2. 124

    3. 131

    . 145

    1. 145

    2. 167

    . 171

    1. O2O 171

    2. 177

  • 4

    92

    . 6 182

    1. 186

    2. 193

    3. 199

    4. 205

    5. 213

    6. 228

    . 240

    1. 240

    2. 249

    3. 257

    262

    265

  • 4.

    93

    Executive Summary

    1. 4

    , , , IoT

    (offline) (online) O2O(online 2 offline)

    2.

    ,

    3. O2O 50% 50$

    ,

    4. ,

    5.

    ,

    6. 1) 2) 3) 4) 5)

    6) 6

    1) : BM

    2) : M&A

    3) : ,

    4) : 3.0

    5) :

    6) :

  • 4

    94

    1980 3

    O2O 4

    - IoT, ,

    O2O

    1950 ?

    , 2) , 3)

    - IoT,

    , , ,

    M&A

    4 ,

    - , ,

    42 . ,

    - , IT

    ,

    IoT, , ,

    - 4 50

    1,000

    - ,

  • 4.

    95

    , 4 O2O

    - PSS, ,

    , ,

    4 6

    1) , 2) , 3) BM

    , 4) 50

    - 1) , 2)

    , 3) , 4)

    , 3 1) , 2)

    , 3)

    GPU ,

    3.0

    ,

    , ,

  • 4

    96

    ,

    ,

    ,

    Governance ,

    - Block Chain ,

    ,

    ( ,

    )

    ,

    - 10

  • 4.

    97

    .

    1.

    4

    2016 4 O2O(Online 2 Offline)

    (Cyber-Physical System)

    - O2O

    O2O ,

    - ,

    AI

    - 24 O2O

    - 4 O2O

    - , , ,

    ,

    - , 1930

    ,

  • 4

    98

    - ,

    - 3 , 100

    , 2015 10 (Fan Hui) 5

    -

    ,

    ,

    -

    -

    - ,

    -

    , 3

    - , ,

    O2O

  • 4.

    99

    -

    - O2O

    ,

    - ,

    TV, ,

    -

    - 2015 11 9, TensorFlow

    SaaS(Software as a Servies)

    - IBM Watson Siri

    SaaS IT

    4

    ,

  • 4

    100

    2.

    O2O

    ,

    ?

    1950 John McCarthy ,

    - 1980 5 , Alvey

    ,

    , , (

    )

    1) , GPU(Graphic Processing

    Unit) , 2) , 3)

    O2O

    -

    -

    O2O

    -

    , , ,

  • 4.

    101

    ( )

    ,

    -

    -

    1950 ,

    ,

    - (1958) 10 ,

    - (1967)

    -

    (Connectionism)

    Back Propagation

    -

    , (node) ,

    -

    -

  • 4

    102

    2010 GPU( )

    , IoT

    ( )

    (Neural Network)

    - ,

    (DNN, )

    -

    - CNN(Convolutional Network)

    RNN(Recurrent

    Neural Network) ,

    -

    1980 2010 GPU IoT &

    - 2009

    SVM(Support Vector Machine)

    - 10 3

    15

    - ,

    , , ,

    ,

  • 4.

    103

    3.

    2015 TensorFlow , MS

    -

    ,

    , , ,

    ,

    API

    (Torch) DL , (NVIDIA)

    (ML) (Big Sur)

    (Open-source)

    CNTK(Computation Network Toolkit)

    DMTK(Distributed Machine learning Tool Kit) ,

    IT

    WARP-CTC

    SW (CaffeOnSpark) 1,100

    ,

    (Veles)

    , , ,

    , ,

  • 4

    104

    , 42 , M

    MS

    ,

    IT

    ,

    M&A

    , 4

    ,

    -

    2014

    , (DeepFace)

    , IBM, MS ,

    - (Andrew Ng)

  • 4.

    105

    ,

    - 10

    - 2015 (ILSVRC)

    (7) 5 , 2015

    5

    - , ,

    , ,

    IT M&A ,

    ,

    - , ,

    4.

    O2O

    1.0 2.0

    ,

    3.0

    , 1 2

    , 4

  • 4

    106

    3

    ,

    - , ,

    ,

    , IoT,

    , ,

    IoT

    , (Online) (Offline)

    ,

    , ,

    1, 2

    -

    Before Service

    -

    B2C ,

  • 4.

    107

    (Unmet needs)

    -

    5. 6

    ,

    4

    , , ,

    6

    ,

    1) , 2) , 3) BM

    , 4)

    - Siri, Now, MS Cortana, M

    , IBM Watson Developer Cloud

    API

    - , IBM 400

    , 100

    - MS

  • 4

    108

    ,

    ,

    BM

    - Nest 114

    - ()

    -

    ,

    , 3 1) , 2)

    , 3)

    Long Tail

    1) , 2)

    , 3) , 4)

    ,

    , MS,

    Business Domain

    -

    - , ,

    , Business

    Domain

  • 4.

    109

    ,

    ,

    GitHub, Image-net, Statista, Google Public Data Explorer

    , ,

    , 3

    - ,

    MOOC

    - 2

    ,

    -

    3

    , (

    )

    - arXiv() ICLR

    - SCI

    1

  • 4

    110

    - () ,

    Challenge Shared Task

    - Challenge Shared Task ,

    - Challenge Shared Task

    , , ()

    -

    -

    ,

    - 3.0 ,

    -

    ,

  • 4.

    111

    Hogan Lovells

    - ,

    , ,

    - ,

    , ,

    - ,

    ,

    Opt In Opt Out ,

    2013 BSA

    24 3 , 1

    - ,

    ,

    - CC

    ,

    ,

  • 4

    112

    - ,

    1 3

    -

    -

    Big Brother

    - Big Brother ,

    Governance

    - Governance ,

    - Block Chain1)

    - Block Chain ,

    Block Chain

    Governance

    -

    ()

    1)

  • 4.

    113

    - 20 ,

    -

    ,

    3

    6.

    - ,

    ,

    , ,

    ,

    - ,

    , ,

  • 4

    114

    - , , ,

    -

    , ,

    - 1942 3

    - 2004 1

    - 2004

    - 2007

    - 2010

    - 2007 ,

    ,

    ( )

    ,

    ,

    ,

    , ,

  • 4.

    115

    -

    , ,

    -

    - , O2O

    - , ,

    ,

    -

    -

    -

    ,

    3

    , ,

    ,

    ,

    ,

    -

  • 4

    116

    , ,

    AI

    , 10

    -

    3 ,

  • 4.

    117

    .

    - 10 17

    -

    []

    1997 IBM (Deep Blue) 2011

    IBM (Watson) (Jeopardy)

    , 2012 (Hinton) (Deep learning)

    -

    - , A.I, , Her, ,

    -

  • 4

    118

    []

    - 5

    - , ,

    , ,

    CEO 5~10

    ,

    - ,

    -

    - ,

    -

    O2O

    - O2O , , , , ,

  • 4.

    119

    (Fintech), (Digital healthcare),

    - 4

    1. (AI, Artificial Intelligence)?

    - 4 , 1

    - 18

    - ,

    - 2

    - 3 PC ,

    4

    -

    O2O 4

    - O2O

    - (Atom) 80:20

    - (Bit)

    (Long tail)

  • 4

    120

    - PC

    , IoT() IoB()

    - ,

    -

    [] 4

    O2O ,

    O2O , O2O

    -

    O2O O2O

    -

    - O2O 1:1

  • 4.

    121

    - ,

    -

    -

    ,

    - , ,

    - O2O

    - O2O O2O

    - IoT, IoB, GPS

    - 30 1

    - O2O O2O

    [] O2O

    O2O

  • 4

    122

    - 3 (), (), () - , ()

    IoT IoB

    - 6

    6

    - O2O O2O

    O2O

    -

    - O2O

    -

    - O2O

    -

    -

    , , , , O2O , ,

    - , O2O

    - O2O ,

    - O2O 50

    , 1,000 2,000

    - ,

  • 4.

    123

    John

    McCarthy

    (1955)

    (The science and engineering of making intelligent machines)

    Charniak &

    McDermott

    (1985)

    (The study of mental faculties through the use of computational

    models)

    Kurzweil

    (1990)

    (The art of creating machines that perform functions requiring

    intelligence when performed by people)

    Rich &

    Knight

    (1991)

    (The study of how to make computers do things at which,

    at the moment, people are better)

    Schalkof

    (1991)

    (A field of study that seeks to explain and emulate intelligent

    behavior in terms of computational processes)

    Luger &

    Stubblefield

    (1993)

    (The branch of computer science that is concerned with the

    automation of intelligent behavior)

    Gartner

    ()

    , ,

    , ,

    (Artificial intelligence is technology that appears to emulate

    human performance typically by learning, coming to its own

    conclusions, appearing to understand complex content, engaging

    in natural dialogs with people, enhancing human cognitive

    performance(also known as cognitive computing) or replacing

    people on execution of non-routine tasks)

    - ETRI

    []

  • 4

    124

    Technavio

    (2014)

    ( )

    (A smart machine is a machine that is embedded with cognitive

    computing ability, which uses artificial intelligence and machine

    learning algorithms to sense, learn, reason, and interact with

    people in different ways)

    BCC

    Research

    (2014)

    (Smart machines are hardware or software systems that can

    accomplish their designate task even under conditions of

    uncertainty and variability)

    NIA , ,

    : ETRI(2015),

    2.

    2010 ,

    -

    ,

    - ,

    , ,

    ,

    1950

  • 4.

    125

    -

    -

    []

    : IDC&EMC, 2011,

    - 1) , GPU(Graphic Processing Unit) , 2)

    , 3)

    - GPU( )

    , NVIDIA

    - GPU(Graphic CPU) Cuda

    - 2015 12 Big Sur

  • 4

    126

    , Caffe, Torch

    - , MS DMTK

    - ,

    -

    - IoT IoB (Edge)

    -

    - 2009 ( 2.0)

  • 4.

    127

    [] 3

    - (Perception)

    (Cognition) (Manipulation)

    - ,

    -

    -

    -

    []

  • 4

    128

    - ,

    - ,

    -

    -

    ,

    1956 , , ,

    -

    - 1970 ,

    - 10 ,

    1997 IBM

    - 8 ,

    ,

    5 , (Alvey)

    ,

    - IBM

  • 4.

    129

    []

    : http://www.nickgillian.com/wiki/pmwiki/php/GRT/GettingStarted

    (Connectionism)

    Back Propagation

    - 1958 (Peceptron)

    - 1969

    -

    , (Node)

    ,

    - ,

    -

    (Neural Network)

    -

    (DNN, )

  • 4

    130

    -

    - ,

    , ,

    -

    []

    - Back Propagation

    -

  • 4.

    131

    CNN(Convolutional Network)

    RNN(Recurrent

    Neural Network) ,

    -

    -

    , (Convolution

    Weighted sum )

    3.

    []

    : (2015),

    2004 (CIFAR) 50

    (NCAP)

    , , , , ,

  • 4

    132

    -

    -

    - , , ,

    (Low-level feature)

    - , , ,

    - (Deep Neural Networks)

    -

    -

    ,

    - 2006 Hinton

    CNN(Convolutional Neural Networks)

    - ,

    - 2009

    SVM(Support Vector Machine)

    - 10 3

    15

    -

    -

    4 , , ,

    , , , ,

  • 4.

    133

    M&A

    ,

    2016

    -

    -

    -

    []

  • 4

    134

    []

    LUNIT (KOHEA)

    - 2

    []

  • 4.

    135

    (Cognitive

    computing)

    -

    (Machine learning)

    ()

    /

    -

    (Deep learning)

    -

    (Predictive application

    programming interfaces)

    API

    - API

    (Natural language

    processing)

    -

    Policy Net Value Net 2016 1

    (nature)

    []

    : (2016), AI is Here( )

    []

  • 4

    136

    IT SW , ,

    - IBM: Watson

    - GE: Predix

    - ETRI:

    , - Aircure: IPAA-compliant

    ,

    ,

    - Mansanto: Climate

    Insurance

    SW

    ,

    - Verdande Tech:

    DrillEdge

    , ,

    - TESLA, Audi, GM,

    - MOBILEYE: ADAS

    - Apple, Google

    ,

    ,

    - ABB: FRIDA

    - KUKA: LWR

    - Rethink Robotics: Baxter

    O2O

    - Sailthru: Delivers A 360

    , ,

    - Lending Club

    - Bloomberg: Trade book

    ,

    - Lex Machina: Legal

    Analytics

    - Kira: Quick Study

    (Image

    recognition)

    -

    (Speech recognition)

    (

    )

    : Tractica(2015), ETRI (2015)

    []

  • 4.

    137

    - Coursera: MOOC

    - KNEWTON

    - SmartZip

    - ROCKET FUEL

    - DSTILLERY

    Topology

    - NEC

    - Qualcomm

    : , ETRI (2015)2)

    3)

    []

    (Neural networks),

    (Gaussian mixture model), CRF(Conditional Random Field),

    (Hidden Markov model), (Boltzmann machine), SVM

    2000

    2) (2015), , 3) (2016)

  • 4

    138

    - ,

    - CNN

    ,

    -

    -

    - , (Perceptron)

    (Connection weight) (Weighted sum)

    (Classification)

    -

    ,

    - ,

    ,

    - ,

    -

    - ,

    - ,

  • 4.

    139

    , ,

    - (Over-fitting)

    - , ,

    -

    - ,

    ,

    4)

    (Pre-training)

    - (Error Back-

    propagation Algorithm), (Gradient-based)

    - ,

    (Desired output) E

    -

    - E W

    E(W)

    - E(W)

    ,

    (CNN, Convolutional Neural

    Networks)

    Convolution

    4) (2015) Deep learning and medical application

  • 4

    140

    -

    - , 2

    - ,

    CNN

    CNN

    - ,

    - CNN Convolution ,

    Max-pooling

    - , CNN

    , ,

    , , ,

    (RNN)

    -

    - ,

    - ,

    RNN

  • 4.

    141

    LSTM(Long Short-Term

    Memory)

    - LSTM

    - ,

    ,

    - ,

    [] LSTM

    LSTM LSTM

    LSTM , ,

    - , , ,

    CNN 2 ,

    - 2 ,

    - , CNN

    - Max-out ,

    NIN(Network-In-Network), (SPP, Spatial Pyramid Pooling)

    , (Inception)

  • 4

    142

    - Max-out ,

    SPP CNN

    - CNN

    -

    - GoogLeNet 22

    ( ) LeCun LeNet

    -

    -

    (Regularization techniques)

    2012 Hinton Dropout

    -

    ,

    - Bengio (Curriculum learning)

    - ,

    -

    ( ) CNN , CNN

  • 4.

    143

    -

    -

    - CNN (Feed-forward) ,

    ,

    - CNN

    ,

    CNN DBN(CDBN,

    Convolutional Deep Belief Networks), (Deconvolutional

    Networks)

    - CNN

    -

    (CNN ) CNN

    ,

    - CNN CNN

    - Farabet CNN

    - CNN

    - (Super-pixel) ,

    - (Multi-level cut)

    CNN

    R-CNN(Regions with CNN feature)

  • 4

    144

    -

    CNN

    - R-CNN CNN

  • 4.

    145

    .

    1.

    (1) AI

    AI

    2015

    - 2015 11 9, IT Google TensorFlow

    - TensorFlow ,

    - IT

    -

    - Eric Schmidt TensorFlow

    -

    - AI

  • 4

    146

    AI

    -

    - Greg Corrado

    - ,

    - ML(Machine Learning) - DL(Deep Learning)

    - / , / , /

    , /

    2015 11 10, (The Magic in the

    Machine) , (http://

    tensorflow.org/)

    - TensorFlow ,

    API 2.0 5)

    - 2.0

    , ,

    - , , , , ,

    , ,

    5) . (http://www.gnu.org/philosophy/license-list.html)

  • 4.

    147

    : DNN(Deep Neural Network)

    .

    99.9% .

    23% 8% .

    . GPS

    . ,

    , ,

    (Inceptionism) ,

    . 2015 6 18

    6)

    2015 12 2

    (Cloud Vision) API 7)

    - ,

    API , ,

    - API

    (Torch) DL

    - 2015 1 16 (Torch, http://torch.ch/)

    6) Google - Inceptionism: Going deeper into Neural Networks(18. Jun. 2015) https://photos.google.com/share/AF1QipPX0SCl7OzWilt9LnuQliattX4OUCj_8EP65_cTVnBmS1jnYgsGQAieQUc1VQWdgQ?key=aVBxWjhwSzg2RjJWLWRuVFBBZEN1d205bUdEMnhB

    7) Google Cloud Vision API changes the way applications understand images(2. Dec. 2015), http://googlecloudplatform.blogspot.kr/2015/12/Google-Cloud-Vision-API-changes-the-way-applications-understand-images.html

  • 4

    148

    (Deep learning) 8)

    - FAIR ,

    , ,

    (CNN, Convolutional Neural Network, ConvNet)

    - , /, , , NVIDA, AMD

    - ConvNets (NLP)

    (GPU) 9)

    (FAIR) (NVIDIA) (ML)

    (Open-source)

    , (Neural networks) (Training)

    , (Big Sur) 10)

    - (AI) (Open Rack)

    -

    (OCP, Open

    Compute Project)

    - (Kevin Lee) (Serkan Piantino)

    , OCP

    - OCP ,

    OCP (Free-air cooled)

    (HPC)

    - GPU M40 (NVIDIAs Tesla Accelerated

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    9) (http://arxiv.org/abs/1412.7580)10) Facebook to open-source AI hardware design(10. Dec. 2015),

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    17) Facebook - F8 2015: Updates on Connectivity Lab, Facebook AI Research and Oculus(26. Mar. 2015), http://newsroom.fb.com/news/2015/03/f8-day-two-2015/

  • 4.

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    (2016),

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  • 4.

    263

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    (2015), 2015 : , 2015.12.

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    , (2010),

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    Anderson, Susan Leigh, and Michael Anderson(2007), The Consequences for Human

    Beings of Creating Ethical Robots. In Human Implications of Human-Robot

    Interaction: Papers from the 2007 AAAI Workshop, edited by Ted Metzler, 1.

    Technical Report, WS-07-07. AAAI Press, Menlo Park, CA.

    Asaro, Peter(2015), "Regulating Robots: Approaches to Developing Robot Policy and

    Technology", presented at WeRobot 2015, University of Washington, April 10,

    2015.

    Bostrom, Nick and Yudkowsky, Eliezer(2011), "The Ethics of Artificial Intelligence",

    Cambridge Hanbook of Artificial Intelligence, William Ramsey and Keith

    Frankish(eds.), Cambridge University Press.

    BSA(2013), 2013 BSA global cloud computing scorecard

    Carl Shulman, Henrik Jonsson, Nick Tarleton(2009), "Machine Ethics and

    Superintelligence." AP-CAP 2009. Machine Intelligence Research

    Institutue(MIRI).

    Calo, Tyan(2015), "Robotics and the Lessons of Cyberlaw", California Law Review,

    Vol.103.

    Darling, Kate(2012), "Extending Legal Rights to Social Robots", Presented at We

    Robot Conference. April 2012

  • 4

    264

    Gianmarco Veruggio(2006), EURON Roboethics Roadmap, EURON Roboethics Atelier

    Genoa.

    Hogan Lovells(2014), "Data privacy regulation comes of age in asia"

    Karnow, Curtis E.A.(2013), "The Application of traditional tort theory to embodied

    machine intelligence, The Robotics and the Law Conference, Center for Internet

    and Society(Standford Law School), April. 2013.

    Knight, Kate(2014), "How Humans Respond to Robotics: Building Public Policy

    through Good Design", Center for Technology Innovation at Brookings, July

    2014.

    Lin, Patrick, Bekey, George&abney, Keith(eds.)(2011), Robot Ethics: The Ethical and

    Social Implications of Robotics, MIT Press.

    Solum, Lawrence B.(1992), "Legal Personhood for Artificial Intelligence", North

    Carolina Law Review, Vol.70.

    , http://www.law.go.kr/main.html

    , http://www.dongascience.com

    , http://www.irobotnews.com

    , www.sciencetimes.co.kr

    , , http://www.uni-stuttgart.de

    , http://www.giantt.co.kr

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    UNOG(The United Nations Office at Geneva), http://www.unog.ch (2015 Meeting of

    Experts on LAWS)

    http://www.aaai.org/Papers/Workshops/2007/WS-07-07/

  • 4.

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