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Concepts of Immersive Intelligence


Workshop for FCVW May 2010

Workshop for FCVW May 2010

Published in Technology
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    No notes for slide
  • Clouds at 2: 3:
  • slowly spinning cube that appears huge
  • several complex abstract objects, maybe using Susanne’s creations
  • persons in a conference room viewing a projection screen, taking notes, etc.
  • sub-atomic particles to normal objects to the Earth to galaxies
  • explosion in slow motion to geological formations in rapid motion in June 2004 in the Grand CanyonAlso explosion at
  • beating heart or bottle dropping/breaking on floor… to a 9/11 scene
  • Artistic Delivery of Data + Threshold of Interaction= >>> (greater) Engagement.


  • 1. Concepts and Practices of Immersive Intelligence
    Dr. Richard Hackathorn
    Bolder Technology, Inc.
    Federal Consortium for Virtual Worlds 2010
  • 2. ThinkBalm Innovation Community
    Erica and Sam Driver,
    Immersive Intelligence Colleagues
    Meet-and-Greet event in Aug 2009
    Open community under Creative Commons
    Register here! Join us for coffee on Tuesdays
    NOTE: Slides at under Blog
    How we got started…
  • 3. Immersive Intelligence: What and Why?
    Elevator pitch in 30 seconds!
    Realistic business-oriented assessment
    Emerging technology; unproven use case
    When and how . . . for what expected benefit
    Motivated to jump in-world and contribute!
    Workshop Objectives
  • 4. Why? So, What?
    Sharing A Vision
    Places to Visit & Things to Learn
    Putting It Together
    What’s Next?
  • 5. Not your grandmother’s pie chart!
    What are we trying to accomplish?
    Hard Problems
    Complex Systems
    Big Data
    A. Why? So, What?
  • 6. Not your grandma’s pie chart!
    © Getty Images. Used with Permission
  • 7. What Problems Are We Solving?
    We Are Here!
  • 8. No quick answers
    No ‘right’ answers
    Conflicting priorities
    Many valid opinions and perspectives
    Leveraging the Wisdom of the Crowd
    Managed Muddling
    What are Hard Problems?
  • 9. Non-intuitive behavior
    Often full of surprises
    Tipping points
    When you least expect them
    Feedback Loops
    Exponential Behavior
    Will hit the wall… with certainty
    Small World effects
    Phase transitions from one state
    What are Complex Systems?
  • 10. History of Complex Systems
    Science Of
  • 11. Stable System
    Chaotic System
    Will Wright at GameTech 2010
    Complex Systems are Chaotic
  • 12. Clocks versus Clouds
    regular, orderly,
    and predictable
    highly irregular, disorderly,
    and more or less unpredictable
    Karl Popper
  • 13. Focusing on technology (MPP, MapReduce, Hadoop)
    What is Big Data?
    The Economist, Feb 25, 2010
  • 14. Volume – Yes, but…
    More than we can store!
    Can we ever touch each bit?
    Data in motion  new types of analysis
    What is important to capture? Context?
    Many types of data! …like network graphs
    Analytics are a necessity!
    Can not touch all the atomic level data!
    What is Big Data?
    The Economist, Feb 25, 2010
  • 15. Imagine virtual space
    Imagine virtual objects
    Imagine virtual teams
    Imagine scaling size
    Imagine scaling time
    Imagine scaling probability
    B. Sharing A Vision
  • 16. Imagine Virtual Space
    Vast canvas spanning kilometers
    Persistent and always on
  • 17. …with rich features, such as texture, lightning, shadow, shininess, etc
    Imagine Virtual Objects
  • 18. Sharing experiences & common perspectives
    Understanding the root cause of problems
    Generating & prioritizing alternative solutions
    Executing on action plans
    Imagine Virtual Teams
  • 19. From the very small to the very large
    Imagine Scaling Size
  • 20. From the very fast to the very slow
    Imagine Scaling Time
  • 21. From the certain to the highly improbable (and unimaginable)
    Imagine Scaling Probability
  • 22. Immersive Intelligence Park on Second Earth 6
    Chakryn Forest by Bettina Tizzy and others
    beautiful and complex => data forest
    Real-time weather display on NOAA Meteora
    Data feed from NWS, updated every 5 min
    DadenDatascape by David Burden
    Ben Lindquist of Green Phosphor
    Tools to graph data in several virtual worlds
    Data Sculptures by Ann Cudworthat Beach Ride
    C. Places To Visit & Things To Learn
  • 23. Death and Taxes by Eric Hackathorn
    Chromutate by Opensource Obscure
    Fanciful objects with playful behaviors
    Mars Victoria Crater on NASA Explorer Island
    Largest sculpted build
    Wind Simulator by comet Morigi
    Creative use of particles
    Asteroid strike on Mars by the Exploratorium
    Large-scale complex simulation; getting the physics correct
    Svarga ecosystem as the “God Game”
    C. Places To Visit & Things To Learn
  • 24. NOAA Real-Time Weather
  • 25. Exciting and insightful way of visualizing and analyzing data
    Using GreenPhosphor’sGlassHouse Gateway
    Richness of Expression
    More than 3D
    Ben Lindquist of Green Phosphor
  • 26. Hovering between Art and Science
    The Spirit of the Data
    …listening and being one with the data
    ART + TOI  Engagement
    Ann Cudworth
  • 27. Immersive Intelligence is an Approach
    Levels of Immersive Intelligence
    Immersion is the Secret Sauce
    D. Putting It Together
  • 28. It is an Approach
    Not a tool, not a methodology,
    Collaborative data-driven decision process for understanding and managing complex systems using immersive virtual spaces
    Subject to continual change! 
    Actionable information
    What do you do with what you know?
    plus the means to execute
    Immersive Intelligence
  • 29. Levels of Immersive Intelligence
    R. Hackathorn, Serious Games in Virtual Worlds, 2007
  • 30. Immersion is the Secret Sauce
    You are there … surrounded by others
    Feels as an actor inside, rather than observer outside
    Analogy: Snorkeling versus SCUBA
  • 31. Architecture - A
    Abstraction of
    Complex System
    In Virtual World
    Complex System
    In Physical World
    The System
  • 32. Architecture - B
    Shape Definer
    The System
    Abstraction of
    Complex System
    In Virtual World
  • 33. DW Appliances as VW Backends
    IBM Smart
    Analytics System
    DW Appliance
    Sun Oracle
    Database Machine
  • 34. Need for an open “community of practice”
    By sharing information and experiences, learn from each other and develop the skills needed
    Methodically pool knowledge…by wiki-izing
    Need a diverse array of skills and experiences
    Too many engineer-types; need more artists!
    Foster learning and innovation
    Provide a low barrier to that “Hello, World” experience
    Facilitate that “A-ha… I get it!” experience
    Got a start with the IM-TEL community
    Contribute, share, and leverage…at
    Share alike with Creative Commons with Attribution
    E. What’s Next?
  • 35. Sponsor contests within SL community
    Focus on data visualization
    How best to illustrate clustering or decision trees?
    Engage in Proof-of-Concept projects to…
    Surface the issues and roadblocks
    Demonstrate the benefits
    Offering 2-day custom workshop
    Bring your team to common ground
    Assess the business justification for specific use case
    E. What’s Next?
  • 36. Immersive Intelligence: What and Why?
    Elevator pitch in 30 seconds!
    Realistic business-oriented assessment
    Emerging technology; unproven use case
    When and how . . . for what expected benefit
    Motivated to jump in-world and contribute!
    Workshop Objectives-Revisited