International Conference on Neural Information Processing

ICONIP 2016: Neural Information Processing pp 275-281

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

Conference paper

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

Volume 9947 of the book series Lecture Notes in Computer Science (LNCS)
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 intelligenceComputational neuroscienceBiologically 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