• DocumentCode
    2922382
  • Title

    Toward Human-Level Machine Intelligence

  • Author

    Zadeh, Lotfi A.

  • Author_Institution
    University of California Berkeley, USA; Director of BISC (Berkeley Initiative in Soft Computing)
  • fYear
    2006
  • fDate
    Nov. 2006
  • Abstract
    Can machines think? This question has been an object of discussion and debate for over half-a-century. My interest in the question goes back to the beginning of my academic career. Officially, AI was born in l956. At its birth there was widespread expectation that within a few years it will be possible to build machines that could think like humans. I did not share that belief. To the pioneers, symbolic logic was all that was needed. Anything that involved numerical computations was unwelcome. It took close to thirty years for probability theory to gain grudging acceptance. Clearly, adding probability theory to the armamentarium of AI is a step in the right direction. But is it sufficient? In my view, the answer is: No.
  • Keywords
    Artificial intelligence; Computer science; Decision making; Engineering profession; Humans; Machine intelligence; Probabilistic logic; Sense organs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on
  • Conference_Location
    Arlington, VA, USA
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2728-0
  • Type

    conf

  • DOI
    10.1109/ICTAI.2006.114
  • Filename
    4031871