HOW IS KOREA SHOCKED BY ALPHAGO?

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1 Movements to Intelligent Information in Korea HOW IS KOREA SHOCKED BY ALPHAGO? Shin Seokhwan / Vice President

2 Is Go(Weiqi/Baduk) different from Chess? IBM's Deep Blue beat world chess champion Garry Kasparov in 1997 Till 2014, Go programs could not beat a professional Go player without handicaps

3 Big match in Seoul, Korea Vs. 33 years old 21 years in professional 18-time world champion 4 th in the world rank Developed by Google DeepMind Beat all Go programs Beat Fan Hui in Oct

4 The result was incredible! 1st 2nd 3rd 4th 5th X X X Win X black white black white black Win Win Win X Win

5 How did AlphaGo learn Go? D Silver et al. Nature 529, (2016) doi: /nature16961 Supervised Learning Reinforce Learning The probabilities The position 160,000 game records 1,280,000 self-matches Amateur 3 Dan Professional 9 Dan(?)

6 Human predicts the future of AI A Space Odyssey (1968/2001) Matrix (1999/2199) I,Robot (2004/2035) EX Machina (2015/2020?) Terminator (1984/2029) AI (2001/2090) HER (2013/2025) 6

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8 Big Data and AI Market Application Markets [M USD] 40,000 30,000 Big Data and AI Market Trends [IDC, EU, Market Reports, 2013] 20,000 Smart Robot / Wearable Services 10, 빅데이터 Big Data 인공지능 AI Big Data market will grow at a 27% compound annual growth rate (CAGR) to $32.4 billion through 2017 Global Industry Analysts forecast the big data based Artificial Intelligence market to exceed 27 billion by 2015 Virtual Agent / Decision Support Self-driving Car / Smart Factory

9 AI Market Expectation? Growing exponentially over the coming years Apple, Google, Microsoft and Facebook invest in the AI 1980s 1990s 2000s 2010s H/W, System OS, S/W Service Platform Artificial Intelligence? Personal Assistant and QA Services MS Cortana Apple Siri Amazon echo Google Now MIT Jibo Docomo SC

10 Big Value from Big Data? Size? 1,000,000,000 Tera = 1,000,000 Peta = 1,000 Exta = 1 Zetta 1.2ZB 1.8ZB 2.5ZB 7.9ZB 35ZB mins 750B HD Movies 163M Years Watching for One Person Volume 3M/sec s 20hrs Movies /min 50M Tweets /day 3V? Velocity Variety DBMS Sensor Log Text Office Image Audio Video

11 The Facts of Big Data? Big Data Technology : Complex and large data sets that it becomes difficult to process using traditional technologies Why is it so difficult to process? 3V x F.A.C.T!! (Fragment x Ambiguity x Context x Trustability)

12 What is Artificial Intelligence? The science and engineering of making intelligent machines. (John McCarthy) The study and design of intelligent agent system that perceives its environment and takes actions that maximize its chances of success. (Stuart Russell) The study how to create computers and computer software that are capable of intelligent behavior. (Wikipedia) Planning (decision making) Learning Reasoning Knowledge Representation Learning Reasonin g Planning Voice / Images Perception NLP / Sensors Actuators Action Display / TTS Environment

13 What is Artificial Intelligence? Strong AI Artificial general intelligence. Computers can be made to think on a level at least equal to humans, that they can be conscious and experience emotions. Weak AI Non-sentient computer intelligence or AI that is focused on one narrow task. All real-world systems labeled "artificial intelligence" of any sort are weak AI at most. Systems that think like humans Systems that act like humans Systems that think rationally Systems that act rationally

14 Knowledge Representations Natural Language Employees working for a company are humans; the company and the employees are legal entities. The company is able to make a reservation for an employee s trip. The trip is available by plane or train that travels in cities within Korea or the U.S.. The companies and destinations for business trip are located in the cities. Saltlux reserved OZ510 with a round trip of Seoul and New York for Hong, Kildong. Rule Language (Rule) If someone is flying, he must be on trip. (Rule) If someone s trip is reserved in a company, he is an employee of the company. (+ Rule) For short trip in the same country, an employee should take a train. (Deduction) Hong kil-dong whose flight is in reservation is an employee of Saltlux. (Deduction) OZ510 is a flight for the U.S. and Korea.

15 Intelligent Information in Korea Smart Factory Intelligent Information Intelligent Information AI SW Big Data IoT Cloud Military Humanoid Self-driving Car Drone HPC ICT Devices Machine Translation Interpretation Agents

16 (Ex) Two Big Projects from Government Image/Action Recognition and Analysis Abnormal actions Image recognition Action pattern analysis Knowledge-based Agent Voice Recognition Natural Language Processing Knowledge Base Machine Learning Reasoning

17 Knowledge Learning and Reasoning for QA Who is this person? He/she was born in Gyungsang-do between remarried father, a soldier and mother, a teacher. He/she has an elder sister and lost his/her mother on independence day. WiseQA Learning and Augmentation WhoIs(?x) type(x) = :- person, hasmother(?x,?mother), job(x.father) = soldier, job(?mother, teacher), job(x.mother) = teacher, becomes(?x, 60), remarriage(x.father, home(?x, Gyungsang-do), hasfposition(?x, X.mother), 2nd), hasfather(?x,?father), diedon(x.mother) = ind-day, job(?father, soldier), birthplace(x) remarriage(?father, = Gyungsang-do,?mother) isfirstchild(x).. = No, Ara Ko, Jeaho Kim, Jun Han G.H. Park(90%) Ara Ko(10%) Jaeho Kim(5%) Search (graphmatching) Reasoning Semantic Temporal Geospatial Uncertain Korea headof President job Jaeok Park daughter job Soldier Core Knowledge job job Junghee Park father birthplace Deagu Honam Kim divorce monk wife husband Geunhae Park teacher birthday Youngsu Yook mother memberof Okchon School Yookyoung chairman diedon Saenuridang Middle School

18 For TC, Threat or Opportunity? Linguistic Cognition Story Writing

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20 Occupation TREAT by Computer Rank Carl Benedikt Frey and Michael A. Osborne, September 17, 2013 Computerisable Probability (0~1) Recreation Therapists Occupations Training and Development Managers Industrial Production Managers Chefs and Head Cooks Funeral Service Managers, Directors, Biological Technicians Interpreters and Translators Judges, Magistrate Judges, and Magistrates Installation, Maintenance, and Repair Workers Camera Operators Tire Repairers and Changers Barbers Technical Writers Transportation Inspectors Telemarketers

21 Roles of Human in TC Emotion Emotional Contents Semantic Meta Data Content Strategy Content Style / Standards Facts Data Engineering Technology Knowledge Design New Information / Contents Intuition