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
Link To Document :
بازگشت