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Brain Amplifier for Holistic Knowledge Management using New Generation of AI

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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 – PowerPoint PPT presentation

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Title: Brain Amplifier for Holistic Knowledge Management using New Generation of AI


1
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
2
AI was born from dreams It is
still what we need to innovate
  • 3000BC first 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
  • 1921 robot (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/cog
202/Papers/ai-history.html and on
http//emlkmi.free.fr/tiki-index.php?pageHistoire
Ia
3
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

4
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.

5
What we learnt ?
Knowledge is relative to human Human is complex
Human have to deal with complex systems
6
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

7
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

8
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

9
New generation of AI (symbolic and robotics)
10
Future of AI
Welcome to my dreams
11
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

12
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
4th Customeras the Asset
5th Knowledgeas the Asset
CoreStrategy
  • RD in Isolation
  • Link toBusiness
  • Technology/BusinessIntegration
  • IntegrationWith CustomerRD
  • CollaborativeInnovationSystem

ChangeFactors
  • UnpredictableSerendipity
  • Inter-dependence
  • Systematic RDManagement
  • AcceleratedDiscontinuousGlobal Change
  • KaleidoscopicDynamics

Performance
  • RD asOverhead
  • Cost-Sharing
  • BalancingRisk/Reward
  • ProductivityParadox
  • IntellectualCapacity/Impact

Structure
  • HierarchicalFunctionally-Driven
  • Matrix
  • DistributedCoordination
  • Multi-DimensionalCommunities ofPractice
  • SymbioticNetworks

People
  • We/TheyCompetition
  • ProactiveCooperation
  • StructuredCollaboration
  • Focus onValues andCapability
  • KnowledgeCultivators

Process
  • MinimalCommunication
  • Project-to-Project Basis
  • PurposefulRD/Portfolio
  • Feedback Loopsand informationpersistence
  • Cross-BoundaryLearning andKnowledge Flow

Technology
  • Embryonic
  • Data-Based
  • Information-Based
  • IT as aCompetitiveWeapon
  • IntelligentKnowledgeProcessors

Customer Retention
Customer Success
Customer Satisfaction
13
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
14
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.

15
What kind of machines ?
Aibo
16
Innovate for what ?
17
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..

18
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

19
Holistic Perspective
20
3 levels of needs
  • Individual machine as an amplifier of human
    capacity and intelligence
  • Organizational
  • Society

21
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..

22
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

23
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

24
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

25
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 (1111) instead of competition
  • Intuitive software
  • HM natural communication
  • RT translation

26
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

27
Share our dreams, lets work our imagination
andInnovate our future together
??!
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