Whole Brain Architecture Approach Is a Feasible Way Toward an Artificial General Intelligence

Conference paper

DOI: 10.1007/978-3-319-46687-3_30

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9947)
Cite this paper as:
Yamakawa H., Osawa M., Matsuo Y. (2016) Whole Brain Architecture Approach Is a Feasible Way Toward an Artificial General Intelligence. In: Hirose A., Ozawa S., Doya K., Ikeda K., Lee M., Liu D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science, vol 9947. Springer, Cham

Abstract

In recent years, a breakthrough has been made in infant level AI due to the acquisition of representation, which was realized by deep learning. By this, the construction of AI that specializes in a specific task that does not require a high-level understanding of language is becoming a possibility. The primary remaining issue for the realization of human-level AI is the realization of general intelligence capable of solving flexible problems by combining highly reusable knowledge. Therefore, this research paper explores the possibility of approaching artificial general intelligence with such abilities based on mesoscopic connectome.

Keywords

Artificial general intelligence Computational neuroscience Biologically inspired cognitive architecture 

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Hiroshi Yamakawa
    • 1
  • Masahiko Osawa
    • 1
  • Yutaka Matsuo
    • 1
  1. 1.Dwango Artificial Intelligence LaboratoryDWANGO Co., Ltd.KyotoJapan

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