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