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Exploring Ineffable Computing: Justifying Existence in the Age of Perception

This piece delves into the intriguing realm of ineffable computing, where human perception intersects with advanced technologies. It questions how we justify existence, communication, and learning in a world filled with complex networks and uncertainties. The narrative tackles topics such as dangerous versus safe examples in supervised learning, the significance of feature selection, and the impact of grounding states in perceptual systems. Join us as we explore these concepts and the future directions of computational understanding, communication, and learning mechanisms.

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Exploring Ineffable Computing: Justifying Existence in the Age of Perception

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  1. Ineffable Computing

  2. Tales of the Black Widowers

  3. How do you Justify your Existence?

  4. 2n

  5. 2n

  6. The Philosopher’s Stone  TM inside steady-state result Out code + data In constant time

  7. Another Interesting Space

  8. It is hard to describe Moo

  9. Cog’s Agenda Moo

  10. Fighting the Ineffable • Use minimal descriptions • Use strategic viewpoints • Just get better at describing stuff • Big complicated perceptual networks

  11. Human perception

  12. “moo moo-moo moo moo moo” Communicating with an Alien

  13. Example, “Dangerous” Example, “Safe” Example, “Dangerous” Examples Dangerous Supervised Learning Pointy

  14. “Pointy” Mind-Reading Pointy Pointy

  15. Example, “Dangerous” Example, “Safe” Example, “Dangerous” “Pointy” “Fast” Pointy, Approaching rapidly Feature Selection Bootstrapping Dangerous Supervised Learning

  16. “Pointy” “Fast” Bootstrapping Dangerous Pointy… Fast… Feature Selection

  17. Shared Activity Sorting Red Left Blue Right

  18. ENOUGH! Collapsing Uncertainty Significance Tests

  19. Training Data Task Learning Mechanism Sequencing Model Instructor Task Modeling Task Grounding State Grounding Perceptual System Demonstrated Task Perceptual Network

  20. Why Communication? • Why not just programming? • Referential indeterminacy is disruptive • Why not just learning? • How to use what is learned • How to pose next learning task • Hand-holding but not spoon-feeding

  21. Future Directions • Ineffable Computing • Unprovoked Computing • Dysfunctional Computing • Quantum Dysfunctional Computing

  22. Brief Rants • Why not imitation? • Imitation is a question, not an answer • Why not naïve users? • Humans don’t stay naïve for long • Humanoids, Cog, Kismet, simulation, emotions, faces, scientific pointillism

  23. Another Interesting Space ENOUGH!

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