Artificial Intelligence: Changing Paradigms

							            Artificial Intelligence:
            Changing Paradigms
                  Vivek Kumar Singh
                  Lecturer (Computer Science)
                  Banasthali Vidyapith,
                  P.O. Banasthali Vidyapith-304022
                  Rajasthan (India)
                  Email: svivek@banasthali.ac.in

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                  Disclaimer
  This Lecture is based on excerpts from varied
  sources. The views expressed are speaker’s own
  and in no way reflect the views of referred sources.




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  Outline of the Lecture
               The Beginning
               A Philosophical Encounter
                 - Turing Test and Searle’s arguments
                 - AI and Creativity
                 - Emotional Intelligence
                 - AI and Consciousness
               Symbolic and Connectionist AI
               New Dimensions of AI
               Recent Developments
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       The Beginning
               The term ‘AI’ was first coined in 1956 by
                Prof. John McCarthy at a conference in
                Dartmouth,U.K..
               Early work in AI
                  - Language Translation
                  - Problem Solving (GPS, 1957)
                  - Pattern Recognition


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    Turing Test
               Imitation Game (Proposed in 1951)




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Searle’s Chinese Room Argument
               Turing test is a behavioral test and not a true
                test of intelligence.




               The Chinese room passes the Turing test
                though it lacks understanding and
                intelligence.
               Strong and Weak AI
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Creativity
      Considered to be an essential component of
       human intelligence.
      Natural question is whether computers can
       think creatively.
      AARON – A Painter Programme – 20 Yr.
       Long project by Harold Cohen.




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 Emotional Intelligence
           Emotions are tied to everything we say and
            do.Incorporating emotions will improve
            interactions with users.
           Simulating Emotions in Computers:-
             - Internal
             - External (Simulating physical correlates)
                        - MIT’s KISMET




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Consciousness
           Consciousness is simply a byproduct of
            complex intelligent systems. Therefore, no
            need to try to isolate and recreate it, it will
            emerge automatically, as needed.
           If not a byproduct then whether its possible to
            computationally define and simulate it.
           Intelligence & Consciousness relationship.
           Critique – Subjective Phenomenal experience
            necessary for consciousness.
           MIT’s Cog Project
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            MIT’s COG Project




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Symbolic AI
           Branch of AI that attempts to explicitly
            represent knowledge in declarative form, i.e.,
            facts and rules.
           Successes:-
             - Expert Systems
             - Game playing programmes
           Problems:-
             - Common Sense Knowledge problem
             - Problems of implicit or procedural knowledge

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  Expert Systems
      Microworlds theory – a scaling theory.
      Mimic human performance within a restricted
       domain of knowledge.

   Game Playing Systems
      Uses brute force approach combined with
       high computational speed.




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Connectionist AI
           Neural Network Architectures.
           Most suited for tasks involving sensory, motor
            and procedural knowledge.

           Limitation:
            Human Brain ~ 100 Billion Neurons
            Typical ANN’s ~ 1000 Neurons




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New Dimensions of AI
           Building Child Machines rather than
            simulating adult minds and then let them
            learn.
           Robotics – artificial mind gets a body.
           Engineering and Run approach.
           Emphasis shifts to consumer/ commercial
            products.
           Artificial Life – synthetic perspective.
           Evolutionary Computing – applying biological
            principles to computing.

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Recent Developments
 Academic AI
    The MIT AI Lab
     Cog (Humanoid Robot), Database Management using Natural
     Language(InfoLab Group), Hal (Intelligent Room Project), Neural
     Circuitry (CBCL), Vision Interface project
      http://www.ai.mit.edu
    Carnegie Mellon University
     Human Computer Interaction, Intelligent Tutoring Systems, Speech
     Processing
     http://www.cmu.edu
    Stanford University
     Expert Systems, Robotics, Machine Learning, Natural Language
     Understanding, Image Understanding
     http://cs.stanford.edu/research/ai.html
    MIT Media Lab - Software Agents Group
     http://agents.media.mit.edu/groups/agents/


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Recent Developments (contd.)
 Corporate AI

    Microsoft Research
     Natural Language Processing, Machine Learning, Natural Language
     Computing, Speech Technology, Mindnet
     http://research.microsoft.com



    IBM Research
     Speech Processing, Machine Translation, Dialog Engines, Information
     Retrieval, Automatic Text Summarization, Natural Language Processing
     http://www.research.ibm.com




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Recent developments (contd..)
 Commercial AI
 Answerlogic – Question answering search engine
 http://www.answerlogic.com

 Artificial Life – Animated Chatterbot agents
 http://www.artificial-life.com

 Conversay – Voice interaction with Internet
 http://www.conversay.com

 Mindmaker – Intelligent Agents
 http://www.mindmaker.com

 Virtual Personalities – Chatterbots with real time animation
 http://www.vperson.com


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            Thank you




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