DocumentCode :
3068978
Title :
CAM-BRAIN The evolutionary engineering of a billion neuron artificial brain by 2001 which grows/evolves at electronic speeds inside a cellular automata machine (CAM)
Author :
De Garis, Hugo
Author_Institution :
ATR Human Inf. Process. Res. Labs., Kyoto, Japan
fYear :
1995
fDate :
20-23 Sep 1995
Firstpage :
62
Lastpage :
69
Abstract :
This paper reports on the second year of an ambitious 8 year research project which aims to implement a cellular automata based artificial brain with a billion neurons by 2001, which grows/evolves at (nano-)electronic speeds inside a Cellular Automata Machine-ATR´s so-called “CAM-Brain Project”. The basic idea is to use cellular automata based neural networks which grow under evolutionary control at (nano-)electronic speeds. The states of the cellular automata (CA) cells and the CA state transition rules can be stored cheaply in gigabytes of RAM. By using state of the art cellular automata machines, e.g. MIT´s “CAM8” machine ($40000), which can update 200 million CA cells a second, it may be technically feasible within a year or so to evolve artificial nervous systems containing a hundred thousand neurons, and within 5 years, a million neurons. By the end of the current research project, i.e. 2001, it should be possible using nanoscale electronics to grow/evolve artificial brains containing a billion neurons and upwards. This is the author´s aim
Keywords :
cellular automata; genetic algorithms; neural nets; CAM-BRAIN; artificial brains; cellular automata based neural networks; cellular automata machine; evolutionary control; Artificial neural networks; Biological neural networks; Brain modeling; CADCAM; Computer aided manufacturing; Genetic algorithms; Humans; Information processing; Laboratories; Neurons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neuroinformatics and Neurocomputers, 1995., Second International Symposium on
Conference_Location :
Rostov on Don
Print_ISBN :
0-7803-2512-5
Type :
conf
DOI :
10.1109/ISNINC.1995.480837
Filename :
480837
Link To Document :
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