Artificial Intelligence for ICT Innovation

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1 2016 ICT 산업전망컨퍼런스 Artificial Intelligence for ICT Innovation October 5, 2015 Sung-Bae Cho Dept. of Computer Science, Yonsei University

2 Subjective AI Hype Cycle Expert System Neural Network?

3 AI in Movies 2

4 Recent Concern about AI 3

5 AI in Reality Google Unmanned Vehicle Apple Siri IBM Watson 4

6 AI in Reality Google Deep Learning Classify cat images with 75% accuracy from 10M videos at Youtube EmoSPARK AI Cube Facebook Identify the face in a photo with 97.25% accuracy 5

7 What is AI? Study or technology to understand the substance of human intelligence, and realize it artificially Strong AI Study or technology to implement human intelligence Technology to make machine think like human Creativity / thought / emotion Weak AI Study or technology to solve a particular problem by imitating human intelligence Technology to solve a specific problem like human Large-scale data processing tirelessly and unbiasedly 6

8 Difficulty and Approaches of AI Difficulty What is clear, but How? Methodologies to develop intelligent systems Knowledge-based Approach: Decision making with stored knowledge Data-driven Approach: Decision making with knowledge extracted from data History of AI technology: Continuous fade in and out of new technology for 50+ years since the invention of computer Logic, optimization theory, probabilistic model, search theory, knowledge-based systems, expert systems, fuzzy logic, neural networks, genetic algorithm, chaos theory,... Key Technologies Search Production system Neural networks deep learning 7

9 Turing Test Conditions for machine to be intelligent (Alan Turing, 1950) Can machines think? Can machines behave intelligently? The imitation game: Operational definition of intelligence Is there a system that passes the Turing test? When is it possible? Does only human have intelligence? Functionalities required for computer Knowledge representation, Inference & planning, Adaptation & learning, Language processing 8

10 Integrative Intelligence Technology Separate endeavor on R&D for bottom-up approach (Artificial Life) and top-down approach (conventional AI) Require the cooperation between high-level intelligence of conventional AI and low-level intelligence of behavior-based AI Conventional AI: Lack flexibility and require enormous time Behavior-based AI: Difficult to solve complicated problems Require the collaboration between symbolic representation and connectionist representation Need of study on social ability, emotion, sensibility, etc. 9

11 Digital Convergence Multi-function Scheduler, camera, game, mp3 High-performance XScale 400Mhz 600Mhz Miniaturization 100g ~ 300g 10

12 AI for Mobile Phones AI Interface Service Mobile Device Difficulty in I/O - small screen, handwriting, thumb keyboard Lack of service fusion - simple collection of many high-techs User 11

13 Web Context Phone Conflict ontology AniDiary: Life-Summary in Cartoon Location Positioning Map Image DB GPS Call SMS Photo MP3 Device Weather Location Semantic Labeling Caller/ Calling Time Receiver s Phone Number SMS Contents Sending/Receiving Time Taken Time Access Number Listening Time Title, Genre In recharge?, Manner Mode Battery Level Weather Staying Time (statistics) Preprocessor Landmark Probability (Bayesian Net) Activity BNs Emotion BNs Environment BNs Event BNs 2 nd Inference Landmark Selection Cartoons Background Character Text Selection Effect (Exaggerate Moving] User Profile Job, Preference, Habit Age, Style Intermediate Result PIMS Address, Relationship, Memorial Day, Schedule High-level Result 12

14 An Example of Cartoons Generated Comic XML <CartoonDiary date=" " char_style="oriental"> <CartoonCut no="1" ch_main= Stand" bg_main= Subway2" comment= 사람 많네 ㅡ,.ㅡ"/> <CartoonCut no= 2" ch_main= Course" bg_main= Classroom2" comment= 아~ 그렇구나 /> <CartoonCut no= 3" ch_main= Walk" bg_main= Shopping mall"/> <CartoonCut no= 4" stress="true" ch_main= Moving with shopping bag" bg_main= department store"/> <CartoonCut no= 5" ch_main= coffee or tea" bg_main= in coffee shop" comment= 차 한잔의 여유"/> <CartoonCut no= 6" stress="true" ch_main= Sending SMS" bg_main= Inside Bus 1" comment= 버스 빨라졌네. ㅋ"/> <CartoonCut no= 7" ch_main= Sleeping" bg_main= Myroom2" comment="zzz..."/> </CartoonDiary> 13

15 Smart Phonebook Recommend the callees whom the user presumably would like to make contact with Based on the user s contexts Select proper services according to the user s social and personal contexts Social contexts: intimacy, relationships, relative activity, etc. 14

16 Implementation and Experiments Callee recommendation * Recommendation success rate for n candidates * Failing to recommend (21.7%) is mainly because of the first call that has no previous history Social context visualization Explain contact patterns and relationship 15

17 Conversational Artificial Secretary Here you are. 16

18 Prototype: Home Agent Control for Virtual Model Avatar (MS Agent) Virtual Model (EON) User Status User Input Emergency, The amount of information 17

19 Office Mate by Integrative AI 18

20 Limitation and Possibility of AI Reductionism Godel s incompleteness theorem New paradigm is needed Quantum computing, emergent computing, artificial life Behaviorism Worldwide market size of AI (IDC) Forecast about US$ 127 billion at 2015, and about US$ 165 billion at 2017 MacKenzie Outlook a ripple effect of automation of intellectual work through AI to reach US$ 5.2 ~ 6.7 trillion annually at

21 Direction of AI R&D One Hundred Year Study on Artificial Intelligence (AI100) 100-year effort to study critical issues in the design and use of AI systems, including their economic and social impact Allen Institute for Artificial Intelligence (AI2) contribute to humanity through high-impact AI research and engineering by constructing AI systems with reasoning, learning and reading capabilities 100 billion yen for 10 years for AI R&D in Tokyo establish a system to aim realization of the production revolution of advanced medical and factories Our AI R&D direction? Interdisciplinary fusion research: Human study + fusion study + computing technology Economic / social consideration: Job, human dignity Long-term steady investment & R&D 20

22 Summary AI technology contributes to intelligent services in various aspects Autonomous decision making Appropriate behavior generation Adaptation to environments Demanding new technology Integrative biological/engineering approach for combining intelligence components that have been developed independently Potential R&D topics Education: personalized coaching Transportation: optimized automatic vehicles Health care: personalized medical service Media: understanding multimedia by deep learning Finance: big data analytics for FinTech Game: miniature Turing test Internet: learn to read Web 21

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