1 / 17

Why Can't A Computer Be More Like A Brain?

Why Can't A Computer Be More Like A Brain?. Outline. Introduction Turning Test HTM A. Theory B. Applications & Limits Conclusion. Introduction. Brain allows: conversation, cat or dog, play catch Robots & Computers: NONE Wrong start despite 50 years of research?

markku
Télécharger la présentation

Why Can't A Computer Be More Like A Brain?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Why Can't A Computer Be More Like A Brain?

  2. Outline • Introduction • Turning Test • HTM • A. Theory • B. Applications & Limits • Conclusion

  3. Introduction • Brain allows: conversation, cat or dog, play catch • Robots & Computers: NONE • Wrong start despite 50 years of research? • Neglect of human brain in research • Neural network programming techniques

  4. Turning Test • It asked if a computer hidden away, could converse and be indistinguishable from a human • Today, the answer is NO, Behavioral frame? • Understand then replicate • Jeff Hawkins: Palm Computing, Hand Spring, Numenta • HTM (Hierarchical Temporal Memory) theory

  5. HTM: Theory Cerebral Cortex

  6. HTM: Theory • Neocortex & How it works • Motor control, language, music, vision, different jobs • Uniform structure, suggest common algorithm code • General purpose learning machine • 6 sheets, 30 billion neurons • Learning depends on size, senses, experiences

  7. HTM: Theory

  8. HTM: Theory • Different sheets connected by bundles of nerve fibers • A map reveals a hierarchical design • Input directly to regions, feed others • Info also flows down the hierarchy • Low level nodes, simple input, high more complex • HTM similarly built on hierarchy of nodes

  9. HTM: Theory • Memory not stored in a single location • Example: Cat • Ears, fur, eyes: low level nodes • Head, torso: high level nodes • Takes time, but can learn dog with less memory • Reuse knowledge, unlike AI and neural networks

  10. HTM: Theory • Time is the teacher • Patterns that occur together in generally have common cause • Hear sequence of notes, recognize melody • Memory: hierarchical, dynamic, memory systems • Not computer memory or single instance • Train HTM: Sensory input through time

  11. HTM: Theory • Machine learning difference? • Hybrid with a twist • Hierarchy: HHMM (Hierarchical Hidden Markov Models) • Spatial variation problem • Similarity means same conclusion

  12. HTM: Theory • Biological model: Accurate, neuroanatomy and physiology for direction • HTMs work: Can identify dogs in various forms • Bayesian network • Numenta: Three components • 1) Run-time engine: C++ routines, create, train, run • From small laptops to multi-core PC • Runs on Linux, can use Mac

  13. HTM: Theory • Automatically handles the message processing back and forth in nodes • 2) Tools: Python scripting language, train and test • Sufficient, but could modify/enhance: visualization • 3) Plug-in API and associated source code • Create new kinds of nodes • Two kinds: Basic learning (appears anywhere in net) • Interface node (out of the net to sensors input or effectors that output).

  14. HTM: Applications & Limits • What can you do with Numenta? • Car manufacturers: Spatial inference, data from camera/laser • Social networks, machine net, oil exploration • Work best when hierarchical structure in data (e.g.?) • What sensory data to train with? • Present them in time-varying form

  15. HTM: Applications & Limits • Applications that cannot be solved today: • Long memory sequences or specific timing • Example: Spoken Language, music, robotics require precise timing • Limitation because of tools & algorithms, not platform • Takes time to learn, never learned to program • Not humanlike, not brain, not to pass test

  16. Conclusion • Difference between brain and computer • Wrong approach, Turning test, Neocortex • HTM: Hierarchy, nodes, reuse data, learns on its own • Numenta platform: Run-time engine, Tools, Plug-in API • Applications: Spatial inference, networks • Limits: Long sequence, specific timing

  17. Question Time ?

More Related