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Title: Rebooting Computers as Learning Machines

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.
Authors:
 [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Report Number(s):
SAND2017-8677J
Journal ID: ISSN 0018-9162; 656722
Grant/Contract Number:
AC04-94AL85000
Type:
Accepted Manuscript
Journal Name:
Computer
Additional Journal Information:
Journal Volume: 49; Journal Issue: 6; Journal ID: ISSN 0018-9162
Publisher:
IEEE
Research Org:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING
OSTI Identifier:
1411876

DeBenedictis, Erik P. Rebooting Computers as Learning Machines. United States: N. p., Web. doi:10.1109/mc.2016.156.
DeBenedictis, Erik P. Rebooting Computers as Learning Machines. United States. doi:10.1109/mc.2016.156.
DeBenedictis, Erik P. 2016. "Rebooting Computers as Learning Machines". United States. doi:10.1109/mc.2016.156. https://www.osti.gov/servlets/purl/1411876.
@article{osti_1411876,
title = {Rebooting Computers as Learning Machines},
author = {DeBenedictis, Erik P.},
abstractNote = {Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.},
doi = {10.1109/mc.2016.156},
journal = {Computer},
number = 6,
volume = 49,
place = {United States},
year = {2016},
month = {6}
}