• DocumentCode
    3748085
  • Title

    "What the brain tells us about the future of silicon"

  • Author

    Jeff Hawkins

  • Author_Institution
    Numenta, Inc., 791 Middlefield Road, Redwood City, CA 94063
  • fYear
    2015
  • Abstract
    Many computer and semiconductor manufacturers are looking for new growth opportunities that are not based on traditional von-Neumann architectures. They are also concerned about the potential end of "Moore´s law". This has led to an increased interest in artificial neural networks, and neuromorphic hardware that can support these systems. It is well known that the brain is power efficient and naturally fault tolerant. Therefore, much research is being done on how silicon can support neural architectures while achieving greater power efficiency and greater storage density. I will make two main arguments.
  • Keywords
    "Neurons","Computer architecture","Artificial neural networks","Neuromorphics","Computational modeling","Silicon"
  • Publisher
    ieee
  • Conference_Titel
    Electron Devices Meeting (IEDM), 2015 IEEE International
  • Electronic_ISBN
    2156-017X
  • Type

    conf

  • DOI
    10.1109/IEDM.2015.7409629
  • Filename
    7409629