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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)

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Towards Evolvable Hardware

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1062))

Abstract

This chapter describes 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 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 ($40,000, which can update 200 million CA cells a second) it will be technically feasible by early 1996 to evolve artificial nervous systems containing a hundred thousand neurons, and within a few years, a million neurons. By the end of the current research project, i.e. 2001, it should be possible using nano-scale electronics to grow/evolve artificial brains containing a billion neurons and upwards. This is our aim.

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Authors and Affiliations

  1. Evolutionary Systems Department ATR Human Information Processing Research Laboratories, Brain Builder Group, 2-2 Hikaridai, Seika-cho, Soraku-gun, 619-02, Kansai Science City, Kyoto, Japan

    Hugo de Garis

Authors
  1. Hugo de Garis
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Eduardo Sanchez Marco Tomassini

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© 1996 Springer-Verlag Berlin Heidelberg

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de Garis, H. (1996). 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). In: Sanchez, E., Tomassini, M. (eds) Towards Evolvable Hardware. Lecture Notes in Computer Science, vol 1062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61093-6_4

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  • DOI: https://doi.org/10.1007/3-540-61093-6_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61093-9

  • Online ISBN: 978-3-540-49947-3

  • eBook Packages: Springer Book Archive

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