Artificial Intelligence for ICT Innovation
|
|
- Noah Flynn
- 8 years ago
- Views:
Transcription
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
Artificial Intelligence and Robotics @ Politecnico di Milano. Presented by Matteo Matteucci
1 Artificial Intelligence and Robotics @ Politecnico di Milano Presented by Matteo Matteucci What is Artificial Intelligence «The field of theory & development of computer systems able to perform tasks
More informationCSC384 Intro to Artificial Intelligence
CSC384 Intro to Artificial Intelligence What is Artificial Intelligence? What is Intelligence? Are these Intelligent? CSC384, University of Toronto 3 What is Intelligence? Webster says: The capacity to
More informationCHAPTER 15: IS ARTIFICIAL INTELLIGENCE REAL?
CHAPTER 15: IS ARTIFICIAL INTELLIGENCE REAL? Multiple Choice: 1. During Word World II, used Colossus, an electronic digital computer to crack German military codes. A. Alan Kay B. Grace Murray Hopper C.
More informationChapter 11. Managing Knowledge
Chapter 11 Managing Knowledge VIDEO CASES Video Case 1: How IBM s Watson Became a Jeopardy Champion. Video Case 2: Tour: Alfresco: Open Source Document Management System Video Case 3: L'Oréal: Knowledge
More informationCourse Outline Department of Computing Science Faculty of Science. COMP 3710-3 Applied Artificial Intelligence (3,1,0) Fall 2015
Course Outline Department of Computing Science Faculty of Science COMP 710 - Applied Artificial Intelligence (,1,0) Fall 2015 Instructor: Office: Phone/Voice Mail: E-Mail: Course Description : Students
More informationFall 2012 Q530. Programming for Cognitive Science
Fall 2012 Q530 Programming for Cognitive Science Aimed at little or no programming experience. Improve your confidence and skills at: Writing code. Reading code. Understand the abilities and limitations
More informationMachine Learning: Overview
Machine Learning: Overview Why Learning? Learning is a core of property of being intelligent. Hence Machine learning is a core subarea of Artificial Intelligence. There is a need for programs to behave
More informationPanel ADVCOMP/SEMAPRO. Luc Vouligny, moderator
Panel ADVCOMP/SEMAPRO Luc Vouligny, moderator Computing Challenges with Semantics and Ontology Models Cristovâo D P Sousa Universidade do Porto, Portugal Michel ClauB Technische Universität, Chemnitz,
More information01219211 Software Development Training Camp 1 (0-3) Prerequisite : 01204214 Program development skill enhancement camp, at least 48 person-hours.
(International Program) 01219141 Object-Oriented Modeling and Programming 3 (3-0) Object concepts, object-oriented design and analysis, object-oriented analysis relating to developing conceptual models
More informationUsing Artificial Intelligence to Manage Big Data for Litigation
FEBRUARY 3 5, 2015 / THE HILTON NEW YORK Using Artificial Intelligence to Manage Big Data for Litigation Understanding Artificial Intelligence to Make better decisions Improve the process Allay the fear
More informationAbout the Author. The Role of Artificial Intelligence in Software Engineering. Brief History of AI. Introduction 2/27/2013
About the Author The Role of Artificial Intelligence in Software Engineering By: Mark Harman Presented by: Jacob Lear Mark Harman is a Professor of Software Engineering at University College London Director
More informationEXECUTIVE SUPPORT SYSTEMS (ESS) STRATEGIC INFORMATION SYSTEM DESIGNED FOR UNSTRUCTURED DECISION MAKING THROUGH ADVANCED GRAPHICS AND COMMUNICATIONS *
EXECUTIVE SUPPORT SYSTEMS (ESS) STRATEGIC INFORMATION SYSTEM DESIGNED FOR UNSTRUCTURED DECISION MAKING THROUGH ADVANCED GRAPHICS AND COMMUNICATIONS * EXECUTIVE SUPPORT SYSTEMS DRILL DOWN: ability to move
More informationProfessor, D.Sc. (Tech.) Eugene Kovshov MSTU «STANKIN», Moscow, Russia
Professor, D.Sc. (Tech.) Eugene Kovshov MSTU «STANKIN», Moscow, Russia As of today, the issue of Big Data processing is still of high importance. Data flow is increasingly growing. Processing methods
More informationHow To Learn From The Revolution
The Revolution Learning from : Text, Feelings and Machine Learning IT Management, CBS Supply Chain Leaders Forum 3 September 2015 The Revolution Learning from : Text, Feelings and Machine Learning Outline
More informationMasters in Human Computer Interaction
Masters in Human Computer Interaction Programme Requirements Taught Element, and PG Diploma in Human Computer Interaction: 120 credits: IS5101 CS5001 CS5040 CS5041 CS5042 or CS5044 up to 30 credits from
More informationMasters in Advanced Computer Science
Masters in Advanced Computer Science Programme Requirements Taught Element, and PG Diploma in Advanced Computer Science: 120 credits: IS5101 CS5001 up to 30 credits from CS4100 - CS4450, subject to appropriate
More informationPage 1 of 5. (Modules, Subjects) SENG DSYS PSYS KMS ADB INS IAT
Page 1 of 5 A. Advanced Mathematics for CS A1. Line and surface integrals 2 2 A2. Scalar and vector potentials 2 2 A3. Orthogonal curvilinear coordinates 2 2 A4. Partial differential equations 2 2 4 A5.
More informationMasters in Artificial Intelligence
Masters in Artificial Intelligence Programme Requirements Taught Element, and PG Diploma in Artificial Intelligence: 120 credits: IS5101 CS5001 CS5010 CS5011 CS4402 or CS5012 in total, up to 30 credits
More information060010706- Artificial Intelligence 2014
Module-1 Introduction Short Answer Questions: 1. Define the term Artificial Intelligence (AI). 2. List the two general approaches used by AI researchers. 3. State the basic objective of bottom-up approach
More informationMasters in Networks and Distributed Systems
Masters in Networks and Distributed Systems Programme Requirements Taught Element, and PG Diploma in Networks and Distributed Systems: 120 credits: IS5101 CS5001 CS5021 CS4103 or CS5023 in total, up to
More informationMasters in Computing and Information Technology
Masters in Computing and Information Technology Programme Requirements Taught Element, and PG Diploma in Computing and Information Technology: 120 credits: IS5101 CS5001 or CS5002 CS5003 up to 30 credits
More informationThe Internet of Things
The Internet of Things Michael Bradley IoT Development Manager Nick O Leary Emerging Technologies Specialist The Internet of Things Billions of smart devices instrument our world today Interconnecting
More informationKNOWLEDGE-BASED IN MEDICAL DECISION SUPPORT SYSTEM BASED ON SUBJECTIVE INTELLIGENCE
JOURNAL OF MEDICAL INFORMATICS & TECHNOLOGIES Vol. 22/2013, ISSN 1642-6037 medical diagnosis, ontology, subjective intelligence, reasoning, fuzzy rules Hamido FUJITA 1 KNOWLEDGE-BASED IN MEDICAL DECISION
More informationCAD and Creativity. Contents
CAD and Creativity K C Hui Department of Automation and Computer- Aided Engineering Contents Various aspects of CAD CAD training in the university and the industry Conveying fundamental concepts in CAD
More informationWhat is Artificial Intelligence?
CSE 3401: Intro to Artificial Intelligence & Logic Programming Introduction Required Readings: Russell & Norvig Chapters 1 & 2. Lecture slides adapted from those of Fahiem Bacchus. 1 What is AI? What is
More informationProgramming Languages
Programming Languages Qing Yi Course web site: www.cs.utsa.edu/~qingyi/cs3723 cs3723 1 A little about myself Qing Yi Ph.D. Rice University, USA. Assistant Professor, Department of Computer Science Office:
More informationIntelligent Computing, Hyperconnected Cloud *, and Fujitsu
Fujitsu Laboratories of America Technology Symposium 2015 Intelligent Computing, Hyperconnected Cloud *, and Fujitsu Dr. Hideyuki Saso CEO and Representative Director Fujitsu Laboratories Ltd. June 24,
More informationSchool of Computer Science
School of Computer Science Computer Science - Honours Level - 2014/15 October 2014 General degree students wishing to enter 3000- level modules and non- graduating students wishing to enter 3000- level
More informationThe Relationship between Artificial Intelligence and Finance
Material 1 The Relationship between Artificial Intelligence and Finance University of Tokyo, Yutaka Matsuo Provisional Translation by the Secretariat Please refer to the original material in Japanese 1
More informationSMART MINDS + SMART CITIES
Your future in Applied Urban Science and Informatics SMART MINDS + SMART CITIES Your future in applied urban science and informatics. 1 6.2 1.9 million 143 million Your future in Applied Urban Science
More informationNetwork Machine Learning Research Group. Intended status: Informational October 19, 2015 Expires: April 21, 2016
Network Machine Learning Research Group S. Jiang Internet-Draft Huawei Technologies Co., Ltd Intended status: Informational October 19, 2015 Expires: April 21, 2016 Abstract Network Machine Learning draft-jiang-nmlrg-network-machine-learning-00
More informationAn Introduction to Health Informatics for a Global Information Based Society
An Introduction to Health Informatics for a Global Information Based Society A Course proposal for 2010 Healthcare Industry Skills Innovation Award Sponsored by the IBM Academic Initiative submitted by
More informationLearning is a very general term denoting the way in which agents:
What is learning? Learning is a very general term denoting the way in which agents: Acquire and organize knowledge (by building, modifying and organizing internal representations of some external reality);
More informationSURVEY REPORT DATA SCIENCE SOCIETY 2014
SURVEY REPORT DATA SCIENCE SOCIETY 2014 TABLE OF CONTENTS Contents About the Initiative 1 Report Summary 2 Participants Info 3 Participants Expertise 6 Suggested Discussion Topics 7 Selected Responses
More informationBig Data: Image & Video Analytics
Big Data: Image & Video Analytics How it could support Archiving & Indexing & Searching Dieter Haas, IBM Deutschland GmbH The Big Data Wave 60% of internet traffic is multimedia content (images and videos)
More informationDesktop Publishing. Specialized Application Software. 1 Chapter 4. 2 Introduction
1 Chapter 4 Specialized Application Software 2 Introduction Software that for years was only available for mainframe computers is now available for microcomputers. Specialized application software makes
More informationCloud Computing for Agent-based Traffic Management Systems
Cloud Computing for Agent-based Traffic Management Systems Manoj A Patil Asst.Prof. IT Dept. Khyamling A Parane Asst.Prof. CSE Dept. D. Rajesh Asst.Prof. IT Dept. ABSTRACT Increased traffic congestion
More informationManaging Knowledge. Chapter 11 8/12/2015
Chapter 11 Managing Knowledge VIDEO CASES Video Case 1: How IBM s Watson Became a Jeopardy Champion Video Case 2: Tour: Alfresco: Open Source Document Management System Instructional Video 1: Analyzing
More informationMultimedia Technology Bachelor of Science
Multimedia Technology Bachelor of Science 1. Program s Name Thai Name : ว ทยาศาสตรบ ณฑ ต สาขาว ชาเทคโนโลย ม ลต ม เด ย English Name : Bachelor of Science Program in Multimedia Technology 2. Degree Full
More informationTutorial: Big Data Algorithms and Applications Under Hadoop KUNPENG ZHANG SIDDHARTHA BHATTACHARYYA
Tutorial: Big Data Algorithms and Applications Under Hadoop KUNPENG ZHANG SIDDHARTHA BHATTACHARYYA http://kzhang6.people.uic.edu/tutorial/amcis2014.html August 7, 2014 Schedule I. Introduction to big data
More informationBSc in Information Technology Degree Programme. Syllabus
BSc in Information Technology Degree Programme Syllabus Semester 1 Title IT1012 Introduction to Computer Systems 30 - - 2 IT1022 Information Technology Concepts 30 - - 2 IT1033 Fundamentals of Programming
More informationEHR CURATION FOR MEDICAL MINING
EHR CURATION FOR MEDICAL MINING Ernestina Menasalvas Medical Mining Tutorial@KDD 2015 Sydney, AUSTRALIA 2 Ernestina Menasalvas "EHR Curation for Medical Mining" 08/2015 Agenda Motivation the potential
More informationSlide 7. Jashapara, Knowledge Management: An Integrated Approach, 2 nd Edition, Pearson Education Limited 2011. 7 Nisan 14 Pazartesi
WELCOME! WELCOME! Chapter 7 WELCOME! Chapter 7 WELCOME! Chapter 7 KNOWLEDGE MANAGEMENT TOOLS: WELCOME! Chapter 7 KNOWLEDGE MANAGEMENT TOOLS: Component Technologies LEARNING OBJECTIVES LEARNING OBJECTIVES
More informationMasters in Information Technology
Computer - Information Technology MSc & MPhil - 2015/6 - July 2015 Masters in Information Technology Programme Requirements Taught Element, and PG Diploma in Information Technology: 120 credits: IS5101
More informationCOMP 590: Artificial Intelligence
COMP 590: Artificial Intelligence Today Course overview What is AI? Examples of AI today Who is this course for? An introductory survey of AI techniques for students who have not previously had an exposure
More informationGfK 2016 Tech Trends 2016
1 Contents 1 2 3 Evolving behavior today s connected consumers Driving you forward 10 tech trends for 2016 Growth from knowledge turning research into smart business decisions 2 Evolving behavior today
More information2013 International Symposium on Green Manufacturing and Applications Honolulu, Hawaii
Green Robotics, Automation, and Machine Intelligence; a new Engineering Course in Sustainable Design Joseph T. Wunderlich, PhD College, PA, USA 2013 International Symposium on Green Manufacturing and Applications
More informationBIG DATA : BIG CULTURE THE GROWING POWER OF THE DATA AND ITS OUTLOOK FOR THE ECONOMY OF CULTURE
BIG DATA : BIG CULTURE THE GROWING POWER OF THE DATA AND ITS OUTLOOK FOR THE ECONOMY OF CULTURE November 2013 INTRODUCTION - - - - - - - Discovering I Tech tours Understanding I Business studies - - for
More informationMobile Marketing: Key Trends
The Mobile Media Authority The Mobile Market Authority Mobile Marketing: Key Trends The Mobile Media Authority Trusted intelligence for a mobile world Evan Neufeld VP + Sr. Analyst M:Metrics, Inc 2007
More informationManjula Ambur NASA Langley Research Center April 2014
Manjula Ambur NASA Langley Research Center April 2014 Outline What is Big Data Vision and Roadmap Key Capabilities Impetus for Watson Technologies Content Analytics Use Potential use cases What is Big
More informationWhat the Hell is Big Data?
Presentation What the Hell is Big Data? Bernard Marr www.ap-institute.com 1 Background 2 Navigating to Success 3 Navigation Today 4 The Global Data Revolution 5 The Intelligent Company Model Strategic
More informationTop 10 IT Trends that will shape 2014. David Chin Chair BICSI Southeast Asia
Top 10 IT Trends that will shape 2014 David Chin Chair BICSI Southeast Asia Gartner Hype Cycle: Emerging Technologies 2013 Convergence of cloud, social, mobile, devices, analytic-driven automation and
More informationHow To Understand The Power Of The Internet Of Things
Next Internet Evolution: Getting Big Data insights from the Internet of Things Internet of things are fast becoming broadly accepted in the world of computing and they should be. Advances in Cloud computing,
More informationDATA MINING TECHNIQUES AND APPLICATIONS
DATA MINING TECHNIQUES AND APPLICATIONS Mrs. Bharati M. Ramageri, Lecturer Modern Institute of Information Technology and Research, Department of Computer Application, Yamunanagar, Nigdi Pune, Maharashtra,
More informationScience: what is possible. Engineering: turn science into an everyday commodity (cheap, safe, reliable, resilient, )
: Big Data Analytics for Renewable Energy Mark J. Embrechts Dept. Industrial and Systems Engineering Rensselaer Polytechnic Institute, Troy, NY, USA What is Data Mining? Data Mining Big Data Analytics
More informationGlobal Technology Outlook 2011
Global Technology Outlook 2011 Global Technology Outlook 2011 Since 1982, The Global Technology Outlook had identified significant technology trends five to even 10 years before they have come to realization.
More informationAppendices master s degree programme Artificial Intelligence 2014-2015
Appendices master s degree programme Artificial Intelligence 2014-2015 Appendix I Teaching outcomes of the degree programme (art. 1.3) 1. The master demonstrates knowledge, understanding and the ability
More informationSix ways to accelerate Android mobile application development
Six ways to accelerate Android mobile application Creating an integrated solution for collaboration among teams Contents 1 Weaving the invisible thread of innovation 2 Android : vast opportunities and
More informationCOMP9321 Web Application Engineering
COMP9321 Web Application Engineering Semester 2, 2015 Dr. Amin Beheshti Service Oriented Computing Group, CSE, UNSW Australia Week 11 (Part II) http://webapps.cse.unsw.edu.au/webcms2/course/index.php?cid=2411
More informationMASTER OF MANAGEMENT (2011-2013)
MASTER OF MANAGEMENT (2011-2013) 1. Course Title: 2. Distinctive Focus: 3. Eligibility: 4. Mode of Selection: 5. No. of seats: 6. Duration: 7. Objectives: 8. Course Structure: 9. Course Details: 10. Summer
More informationCloud Computing and Big Data
Cloud Computing and Big Data. What s the Big Deal? Arlene Minkiewicz, Chief Scientist PRICE Systems, LLC arlene.minkiewicz@pricesystems.com 2013 PRICE Systems, LLC All Rights Reserved Decades of Cost Management
More informationNeural Networks for Machine Learning. Lecture 13a The ups and downs of backpropagation
Neural Networks for Machine Learning Lecture 13a The ups and downs of backpropagation Geoffrey Hinton Nitish Srivastava, Kevin Swersky Tijmen Tieleman Abdel-rahman Mohamed A brief history of backpropagation
More informationStudy Plan for the Master Degree In Industrial Engineering / Management. (Thesis Track)
Study Plan for the Master Degree In Industrial Engineering / Management (Thesis Track) Plan no. 2005 T A. GENERAL RULES AND CONDITIONS: 1. This plan conforms to the valid regulations of programs of graduate
More informationApplications of Artificial Intelligence. Omark Phatak
Applications of Artificial Intelligence Omark Phatak Applications of artificial intelligence (AI) are a convergence of cutting edge research in computer science and robotics. The goal is to create smart
More informationDATA MINING IN FINANCE
DATA MINING IN FINANCE Advances in Relational and Hybrid Methods by BORIS KOVALERCHUK Central Washington University, USA and EVGENII VITYAEV Institute of Mathematics Russian Academy of Sciences, Russia
More informationCharacterizing Knowledge Management Tools
Characterizing Knowledge Management Tools Half-day Tutorial Presented by Kurt W. Conrad conrad@sagebrushgroup sagebrushgroup.com Developed by Kurt W. Conrad, Brian (Bo) Newman, and Dr. Art Murray Based
More informationChapter 1 Basic Introduction to Computers. Discovering Computers 2012. Your Interactive Guide to the Digital World
Chapter 1 Basic Introduction to Computers Discovering Computers 2012 Your Interactive Guide to the Digital World Objectives Overview Explain why computer literacy is vital to success in today s world Define
More informationDeploy. Friction-free self-service BI solutions for everyone Scalable analytics on a modern architecture
Friction-free self-service BI solutions for everyone Scalable analytics on a modern architecture Apps and data source extensions with APIs Future white label, embed or integrate Power BI Deploy Intelligent
More informationApproaches to learning (ATL) across the IB continuum
Approaches to learning (ATL) across the IB continuum Through approaches to learning in IB programmes, students develop skills that have relevance across the curriculum that help them learn how to learn.
More informationRules and Business Rules
OCEB White Paper on Business Rules, Decisions, and PRR Version 1.1, December 2008 Paul Vincent, co-chair OMG PRR FTF TIBCO Software Abstract The Object Management Group s work on standards for business
More informationDATA SCIENCE ADVISING NOTES David Wild - updated May 2015
DATA SCIENCE ADVISING NOTES David Wild - updated May 2015 GENERAL NOTES Lots of information can be found on the website at http://datascience.soic.indiana.edu. Dr David Wild, Data Science Graduate Program
More informationData Mining and Soft Computing. Francisco Herrera
Francisco Herrera Research Group on Soft Computing and Information Intelligent Systems (SCI 2 S) Dept. of Computer Science and A.I. University of Granada, Spain Email: herrera@decsai.ugr.es http://sci2s.ugr.es
More informationRegulating AI and Robotics
Regulating AI and Robotics Steve Omohundro, Ph.D. PossibilityResearch.com SteveOmohundro.com SelfAwareSystems.com http://i791.photobucket.com/albums/yy193/rokib50/sculpture/lady-justice-frankfurt_zps970c5d8f.jpg
More informationGetting to Know Big Data
Getting to Know Big Data Dr. Putchong Uthayopas Department of Computer Engineering, Faculty of Engineering, Kasetsart University Email: putchong@ku.th Information Tsunami Rapid expansion of Smartphone
More informationAn Introduction to Data Mining
An Introduction to Intel Beijing wei.heng@intel.com January 17, 2014 Outline 1 DW Overview What is Notable Application of Conference, Software and Applications Major Process in 2 Major Tasks in Detail
More informationHow To Use Data Mining For Knowledge Management In Technology Enhanced Learning
Proceedings of the 6th WSEAS International Conference on Applications of Electrical Engineering, Istanbul, Turkey, May 27-29, 2007 115 Data Mining for Knowledge Management in Technology Enhanced Learning
More informationThursday, September 15, 2011
The Smartphone Revolution 2011 is the Year of Smartphones (Gartner) Gadgets Americans intend to buy in 2011 1) Smartphone 2) Laptop 3) Desktop PC 4) Mobile handset (other than Smartphone) 5) E-Book reader
More informationEffective Interface Design Using Face Detection for Augmented Reality Interaction of Smart Phone
Effective Interface Design Using Face Detection for Augmented Reality Interaction of Smart Phone Young Jae Lee Dept. of Multimedia, Jeonju University #45, Backma-Gil, Wansan-Gu,Jeonju, Jeonbul, 560-759,
More informationInformation and Media Literacy Accessing and managing information. Integrating and creating information. Evaluating and analyzing information.
Learning Skills for Information, Communication, and Media Literacy Information and Media Literacy Accessing and managing information. Integrating and creating information. Evaluating and analyzing information.
More informationBachelor of Games and Virtual Worlds (Programming) Subject and Course Summaries
First Semester Development 1A On completion of this subject students will be able to apply basic programming and problem solving skills in a 3 rd generation object-oriented programming language (such as
More informationIoT market analysis: Sizing the opportunity
March 2015 IoT market analysis: Sizing the opportunity Author Knud Lasse Lueth This report is aimed at IoT professionals who are looking for a detailed understanding of the Internet of Things market, segments,
More informationMICHIGAN TEST FOR TEACHER CERTIFICATION (MTTC) TEST OBJECTIVES FIELD 050: COMPUTER SCIENCE
MICHIGAN TEST FOR TEACHER CERTIFICATION (MTTC) TEST OBJECTIVES Subarea Educational Computing and Technology Literacy Computer Systems, Data, and Algorithms Program Design and Verification Programming Language
More informationInformation Technology Career Field Pathways and Course Structure
Information Technology Career Field Pathways and Course Structure Courses in Information Support and Services (N0) Computer Hardware 2 145025 Computer Software 145030 Networking 2 145035 Network Operating
More informationDoctor of Philosophy in Computer Science
Doctor of Philosophy in Computer Science Background/Rationale The program aims to develop computer scientists who are armed with methods, tools and techniques from both theoretical and systems aspects
More informationHorizontal IoT Application Development using Semantic Web Technologies
Horizontal IoT Application Development using Semantic Web Technologies Soumya Kanti Datta Research Engineer Communication Systems Department Email: Soumya-Kanti.Datta@eurecom.fr Roadmap Introduction Challenges
More informationSmarter Planet evolution
Smarter Planet evolution 13/03/2012 2012 IBM Corporation Ignacio Pérez González Enterprise Architect ignacio.perez@es.ibm.com @ignaciopr Mike May Technologies of the Change Capabilities Tendencies Vision
More informationI D C A N A L Y S T C O N N E C T I O N. C o g n i t i ve C o m m e r c e i n B2B M a rketing a n d S a l e s
I D C A N A L Y S T C O N N E C T I O N Dave Schubmehl Research Director, Cognitive Systems and Content Analytics Greg Girard Program Director, Omni-Channel Retail Analytics Strategies C o g n i t i ve
More informationSchool of Computer Science
School of Computer Science Head of School Professor S Linton Taught Programmes M.Sc. Advanced Computer Science Artificial Intelligence Computing and Information Technology Information Technology Human
More informationPersonalized User Journeys. By Kevin Jackson Global Sales Director Gravity R&D 12/15/14
Personalized User Journeys By Kevin Jackson Global Sales Director Gravity R&D 12/15/14 Table of Contents Omnichannel and Retail 2.0... 3 Moments of Truth (MOTs)... 4 ibeacons, MOTs, and Big Data... 5 Personalized
More informationMachine Learning. 01 - Introduction
Machine Learning 01 - Introduction Machine learning course One lecture (Wednesday, 9:30, 346) and one exercise (Monday, 17:15, 203). Oral exam, 20 minutes, 5 credit points. Some basic mathematical knowledge
More informationA Proposal for the use of Artificial Intelligence in Spend-Analytics
A Proposal for the use of Artificial Intelligence in Spend-Analytics Mark Bishop, Sebastian Danicic, John Howroyd and Andrew Martin Our core team Mark Bishop PhD studied Cybernetics and Computer Science
More informationFrom Big Data to Smart Data Thomas Hahn
Siemens Future Forum @ HANNOVER MESSE 2014 From Big to Smart Hannover Messe 2014 The Evolution of Big Digital data ~ 1960 warehousing ~1986 ~1993 Big data analytics Mining ~2015 Stream processing Digital
More informationThe analytics landscape: A personal view
The analytics landscape: A personal view Charles Elkan el December 20, 2011 What is analytics? Big data, business intelligence (BI), decision support (DSS), data warehousing, unstructured data, knowledge
More informationChapter Managing Knowledge in the Digital Firm
Chapter Managing Knowledge in the Digital Firm Essay Questions: 1. What is knowledge management? Briefly outline the knowledge management chain. 2. Identify the three major types of knowledge management
More information12/7/2015. Data Science Master s programs
Data Science Master s programs 1 1 Who are we? Willem-Jan van den Heuvel Tilburg University Ksenia Podoynitsyna Eindhoven University of Technology 2 2 Program What is Data Science? The Data Science Initiative
More informationHarmonizing Government Policies and Enterprise Strategies for IoT Business
Harmonizing Government Policies and Enterprise Strategies for IoT Business KEON CHUL PARK 1, JEMIN JUSTIN LEE 2, SANG HOO OH 1, BONG GYOU LEE 1 1 Graduate School of Information 2 Department of Technology
More informationBig data and its transformational effects
Big data and its transformational effects Professor Fai Cheng Head of Research & Technology September 2015 Working together for a safer world Topics Lloyd s Register Big Data Data driven world Data driven
More informationBIG DATA AND ANALYTICS
BIG DATA AND ANALYTICS Björn Bjurling, bgb@sics.se Daniel Gillblad, dgi@sics.se Anders Holst, aho@sics.se Swedish Institute of Computer Science AGENDA What is big data and analytics? and why one must bother
More informationStatistics for BIG data
Statistics for BIG data Statistics for Big Data: Are Statisticians Ready? Dennis Lin Department of Statistics The Pennsylvania State University John Jordan and Dennis K.J. Lin (ICSA-Bulletine 2014) Before
More informationMS1b Statistical Data Mining
MS1b Statistical Data Mining Yee Whye Teh Department of Statistics Oxford http://www.stats.ox.ac.uk/~teh/datamining.html Outline Administrivia and Introduction Course Structure Syllabus Introduction to
More information