• DocumentCode
    761546
  • Title

    Why Can´t a Computer be more Like a Brain?

  • Author

    Hawkins, Jeff

  • Volume
    44
  • Issue
    4
  • fYear
    2007
  • fDate
    4/1/2007 12:00:00 AM
  • Firstpage
    21
  • Lastpage
    26
  • Abstract
    This paper discusses a theory of the neocortical algorithm called the hierarchical temporal memory (HTM). Hierarchical temporal memories are built around a hierarchy of nodes. The hierarchy and how it works are the most important features of HTM theory. In an HTM, knowledge is distributed across many nodes up and down the hierarchy. As an HTM is trained, the low-level nodes learn first. Representations in high-level nodes then share what was previously learned in low-level nodes
  • Keywords
    knowledge based systems; neural nets; hierarchical temporal memory; high-level nodes; knowledge distribution; neocortical algorithm; neural network programming techniques; node hierarchy; robotic perception; Auditory system; Feeds; Humans; Machine intelligence; Machine learning; Microscopy; Motor drives; Nerve fibers; Neurons; Software tools;
  • fLanguage
    English
  • Journal_Title
    Spectrum, IEEE
  • Publisher
    ieee
  • ISSN
    0018-9235
  • Type

    jour

  • DOI
    10.1109/MSPEC.2007.339647
  • Filename
    4141317