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Artificial cognitive memory-changing from density driven to functionality driven
Journal article   Peer reviewed

Artificial cognitive memory-changing from density driven to functionality driven

L. P. Shi, K. J. Yi, K. Ramanathan, R. Zhao, N. Ning, D. Ding and T. C. Chong
Applied physics. A, Materials science & processing, Vol.102(4), pp.865-875
01/03/2011

Abstract

Materials Science Materials Science, Multidisciplinary Physical Sciences Physics Physics, Applied Science & Technology Technology
Increasing density based on bit size reduction is currently a main driving force for the development of data storage technologies. However, it is expected that all of the current available storage technologies might approach their physical limits in around 15 to 20 years due to miniaturization. To further advance the storage technologies, it is required to explore a new development trend that is different from density driven. One possible direction is to derive insights from biological counterparts. Unlike physical memories that have a single function of data storage, human memory is versatile. It contributes to functions of data storage, information processing, and most importantly, cognitive functions such as adaptation, learning, perception, knowledge generation, etc. In this paper, a brief review of current data storage technologies are presented, followed by discussions of future storage technology development trend. We expect that the driving force will evolve from density to functionality, and new memory modules associated with additional functions other than only data storage will appear. As an initial step toward building a future generation memory technology, we propose Artificial Cognitive Memory (ACM), a memory based intelligent system. We also present the characteristics of ACM, new technologies that can be used to develop ACM components such as bioinspired element cells (silicon, memristor, phase change, etc.), and possible methodologies to construct a biologically inspired hierarchical system.

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