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Brain Amplifier for Holistic Knowledge Management using New Generation of AI. Dr. Eunika MERCIER-LAURENT VP AFIA MODEME UMR 5055- Research Center IAE Université Lyon 3, France. ECCAI ASTI. AI was born from dreams It is still what we need to innovate.
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Brain Amplifier for Holistic Knowledge Management using New Generation of AI Dr. Eunika MERCIER-LAURENT VP AFIA MODEME UMR 5055- Research Center IAE Université Lyon 3, France ECCAI ASTI
AI was born from dreams It is still what we need to innovate • ~3000BCfirst known expert system • 13th C Ramón Lull invented the Zairja, the first device that systematically tried to generate ideas by mechanical means • 17th first computer Pascal and Leibnitz • 1921robot (Karel Capek) • 1945 ENIAC Electronic Numerical Integrator and Calculator • 1945 – 1956 cybernetics, neural nets – learning (Hoebbs) • 1950 Turing test to measure machine intelligence • 1956 Logic theorist first AI pg A. Newell, H. Simon and JC Shaw • 1956 AI was born, the founders was supposed to understand human intelligence and ready to put it into machine • Checkers-playing pg, GPS, NL (Chomsky), perceptron, Dendral, automatic translation… • 1970 machine learning, Prolog • 1975 XCON first commercial expert system, speech recognition • 1980 first commercial tools, beginning of industrial expert systems, fuzzy logic, genetic algorithms • 1985 constraint programming • 1990 CBR, conceptual knowledge modeling, ontology… More on http://www.crl.ucsd.edu/~elman/Courses/cog202/Papers/ai-history.html and on http://emlkmi.free.fr/tiki-index.php?page=HistoireIa Eunika Mercier-Laurent
AI in France • Prof. Jacques Pitrat, Paris 6 • Natural language processing: Prolog Marseille 1970, automatic translation, NL interface to DB • INRIA NL fuzzy information retrieval from DB (80) workstation for collaborative work with AI inside (81) • Groupe Bull : • Research Center 1981 (NL to DB, KOOL, Prolog) • ECRC 1984 (constraint prog, Prolog machine, deductive DB • CEDIAG 1985 : KOOL, Charme, KADS, EDEN, applications • Global approach (91), Organizational Memory, ontology 1994 • ECCAI 82, AFIA 89, IJCAI 93,141 research teams, 37 AI comp Ilog, Cosytec, Kaidara… • Conferences RFIA (since1980) & Plate-forme (since 1999) including applications • AI in national and European Programs Eunika Mercier-Laurent
CEDIAG main applications ALPIN Expert system for Medical insurance with natural language module for automatic processing of medical reports; NOEMIE Configuration system for Bull computers Diagnosis and help desk for customer support, KRONES configuration support system and diagnosis for bottle-washing engines Danish Customs’ decision support system for interpretation of ECC regulations. A similar system was later developed for Argentina Customs. ARAMIS-GM French national Guards Missions planning system (resource allocation, crisis situation management). The first hybrid system was composed of database natural language retrieval, expert system and constraint programming techniques. RAMSES Security of the Winter Olympic games Albertville 1992, in which we have reused our experience from ARAMIS-GM development. SACHEM, decision support system for blast furnaces, the largest European AI application for Sollac (Groupe Arcelor). Knowledge acquisition from telemetric data for Formule1 racing cars, reusing prior experience. Computer network diagnosis, Optimized keys designing, Scheduling, time-tables for colleges, universities and engineering schools, Planning and resources allocation for orange picking and optimizing juice production…. Eunika Mercier-Laurent
What we learnt ? Knowledge is relative to human Human is complex Human have to deal with complex systems Eunika Mercier-Laurent
Context of AI since 1996 • Name : AI or computational intelligence ? • AI promised to much ? • AI inside is not AI ? Decision support systems for technical and medical diagnosis, help desk, maintenance, scheduling, optimization, risk analysis, process control, traffic control design, advisory systems, software.. Solutions are mainly software, we can do better Eunika Mercier-Laurent
Opportunity for AI • Internet : Information overload, lot of data e-services, e-business, e-learning, e-government, m-ware, content design and search …without AI, • Knowledge Management is about Knowledge ! (k transfert, sharing, finding, learning, innovation) lack of feedback from AI applications and ..reinventing the wheel • Mondialization : complex problem to solve, cultures, access to collective K, RT translation ICT : What is missing ? I AI = different thinking Eunika Mercier-Laurent
AI Today Integration of existing techniques (but nothing really new since 20 years) • Knowledge Discovery from multimedia documents • Semantic web (ontology, NLP, MAS, ANN) • Collective intelligence for MAS • Artificial life (understanding brain is to difficult ?) • Hybrid solutions (soft) for complex problems (text mining, automatic indexing and retrieval..) • Intuitive HMI • Computer graphics, VR, immersion, simulation • Co-design Classic and AI Eunika Mercier-Laurent
New generation of AI (symbolic and robotics) Eunika Mercier-Laurent
Future of AI Welcome to my dreams Eunika Mercier-Laurent
C3PO and R2D2 from Star Wars Some inspirations • Leonardo da Vinci, Jules Verne, Isaac Asimow, Lew Bobrow, Stanislaw Lem… • AI, Minority report, Star Wars • More human robot ? Johny 5 from Short Circuit • More powerful human ? Extension of biological capability as Jake Foley… Eunika Mercier-Laurent
Five Generations of Management Styles Adapted from Innovation Strategy for The Knowledge Economy Debra M. Amidon 1997 BH 1st Technologyas the Asset 2nd Projectas the Asset 3rd Enterpriseas the Asset 4thCustomeras the Asset 5thKnowledgeas the Asset CoreStrategy • R&D in Isolation • Link toBusiness • Technology/BusinessIntegration • IntegrationWith CustomerR&D • CollaborativeInnovationSystem ChangeFactors • UnpredictableSerendipity • Inter-dependence • Systematic R&DManagement • AcceleratedDiscontinuousGlobal Change • KaleidoscopicDynamics Performance • R&D asOverhead • Cost-Sharing • BalancingRisk/Reward • ‘ProductivityParadox’ • IntellectualCapacity/Impact Structure • Hierarchical;Functionally-Driven • Matrix • DistributedCoordination • Multi-Dimensional‘Communities ofPractice’ • SymbioticNetworks People • We/TheyCompetition • ProactiveCooperation • StructuredCollaboration • Focus onValues andCapability • KnowledgeCultivators Process • MinimalCommunication • Project-to-Project Basis • PurposefulR&D/Portfolio • Feedback Loopsand ‘informationpersistence’ • Cross-BoundaryLearning andKnowledge Flow Technology • Embryonic • Data-Based • Information-Based • IT as aCompetitiveWeapon • IntelligentKnowledgeProcessors Customer Retention Customer Success Eunika Mercier-Laurent Customer Satisfaction
Technology replaced person-to-person interactions with person-to-machine… Technology requires the synergy of individuals, machines and social organizations and depends profoundly both on an understanding of nature - on science - and on the capability to design. Virtually every human activity - agriculture, commerce, education, health care, warfare, industry and more - depends directly or indirectly on our interactions as individuals with society and machines. George Bugliarello Eunika Mercier-Laurent
My vision In my vision, connected human knowledge cultivators work in perfect synergy with the artificial knowledge processors. They learn from each other. Computers help people by performing the tasks difficult or impossible for human to do… in the world where the biological, social and machine components are well balanced, are sustainable indefinitely without destroying the environment, and enhance the human condition. Eunika Mercier-Laurent
Spirit ElectroluxAutomower What kind of machines ? Aibo Eunika Mercier-Laurent
Dreams Problems & Needs (market) Power of (imagination & intelligence)) methods techniques solutions Products and services Innovate for what ? Eunika Mercier-Laurent
Problems and needs Today problems are complex challenge : find balanced solution Needs • Safety of persons and systems (cryptography, identity management, intrusion detection, security at home, security of Information Systems) • Health, k of our body and k about how to care it, human « spare parts » • Sustainability • Agriculture (ancestral knowledge rediscovering instead of inventing new pesticides and artificial fertilizers) RICH • Intelligent services on line FAQ… • social (loneliness, handicapped, unemployed), • H & C Learning (3W access to K), interactive, with RV, collaborative learning by playing… • Imagination training, interactive games, influence on (bad) comportment ? • Intelligent car • intelligent house ? management of vital functions, recognition of visitors, spare of water and energy, household appliances, equipment for handicaps.. Eunika Mercier-Laurent
Holistic Knowledge Management An integrated system of initiatives, methods and tools designed to create the optimal flow of knowledge within and throughout an extended enterprise to ensure stakeholders success Debra M. AMIDON ENTOVATION International Eunika MERCIER-LAURENT 3D of KM : Technology, Economy, Social/Culture Eunika Mercier-Laurent
Multi-Lateral Agencies, International Societal Organizations Society 5 Countries, Consortia, Regional Entities Nations/Regions 4 Companies, Universities, Government Agencies Enterprise 3 Functions, Teams, Associations Disciplines, SIG’s, Community of Practice Groups 2 Employees, Suppliers, Customers, Stakeholders, Alliance, Partners Individual 1 Holistic Perspective Eunika Mercier-Laurent
3 levels of needs • Individual – machine as an amplifier of human capacity and intelligence • Organizational • Society Eunika Mercier-Laurent
Individual level • Intelligent assistant able to • Find relevant information and knowledge on demand and push • Understand documents/emails, make un abstract • Manage my documents, files, emails using my logic • NL dialog and capability of RT translation • Optimize tasks (travel, shopping, event..) • access and intelligent navigation in the world knowledge bases (scientific, music, sport,) • Recognize visitors, automatic vacuum cleaner, advice… • Tell me a joke when I am sad.. Eunika Mercier-Laurent
Entreprise/Organizational level The same capacity as for individual + • Effective management of innovation process Computers are considered as a source of K • Sharing the learned knowledge relevant to a given point-of-view with relevant people • Effective management of intellectual capital, “who knows what, who needs to know what, and how to learn what is needed” • Support for “business intelligence”: finding and checking relevant information Eunika Mercier-Laurent
Entreprise/Organizational level • Patent browsing for similarity determination • Automated tools for pattern discovery and knowledge acquisition both at the individual and collective levels • Tool for building collective experience of the company • Decision support for all professionals : diagnostic, configuration, problem solving, process control… • Management of global security Eunika Mercier-Laurent
Society • Intelligent e-services (administration, tourism, RT education, call centers…) • Intelligent connections between enterprises, university and investors 3P • Entertainment closer to the life (intelligent games, travel guides and tips, VR visit of monuments with interaction (touch, smell…) • Intelligent banking services • Bank of knowledge and experience (health…) • Services for older people • Health services Eunika Mercier-Laurent
Challenges for AI • Better understanding of our brain capacity • Better use of computer capacity (K thinking approach) • More collective, multi-domain and multi-cultural intelligence (1+1=11) instead of competition • Intuitive software • HM natural communication • RT translation Eunika Mercier-Laurent
Challenges for AI • The Convergence of bio- info- and nano-techniques (human spare parts) ? • Extension of biological capabilities ? • Global Innovation Support Systems • New ways for communication • Better conservation and use of past knowledge and experience • Contribution to the Sustainable Knowledge Society • More of fun Eunika Mercier-Laurent
Share our dreams, lets work our imagination andInnovate our future together… 谢谢!