Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T05:09:32.306Z Has data issue: false hasContentIssue false
  • English
  • Français

What can the brain teach us about building artificial intelligence?

Published online by Cambridge University Press:  10 November 2017

Dileep George
Dileep George*
Affiliation:
Vicarious, Union City, CA 94587. [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Lake et al. offer a timely critique on the recent accomplishments in artificial intelligence from the vantage point of human intelligence and provide insightful suggestions about research directions for building more human-like intelligence. Because we agree with most of the points they raised, here we offer a few points that are complementary.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 40 , 2017 , e265
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P. & Friston, K. J. (2012) Canonical microcircuits for predictive coding. Neuron 76:695–711. http://doi.org/10.1016/j.neuron.2012.10.038.Google Scholar
Cohen, E. H. & Tong, F. (2015) Neural mechanisms of object-based attention. Cerebral Cortex 25(4):1080–92. http://doi.org/10.1093/cercor/bht303.Google Scholar
George, D. & Hawkins, J. (2009) Towards a mathematical theory of cortical micro-circuits. PLoS Computational Biology 5(10):e1000532. Available at: http://doi.org/10.1371/journal.pcbi.1000532.Google Scholar
Lázaro-Gredilla, M., Liu, Y., Phoenix, D. S. & George, D. (2016) Hierarchical compositional feature learning. arXiv preprint 1611.02252. Available at: http://arxiv.org/abs/1611.02252.Google Scholar
Lee, T. S. (2015) The visual system's internal model of the world. Proceedings of the IEEE 103(8):1359–78. Available at: http://doi.org/10.1109/JPROC.2015.2434601.Google Scholar
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., Petersen, S., Beattie, C., Sadik, A., Antonoglous, I., King, H., Kumaran, D., Wierstra, D. & Hassabis, D. (2015) Human-level control through deep reinforcement learning. Nature 518(7540):529–33.Google Scholar
Zhou, H., Friedman, H. S. & von der Heydt, R. (2000) Coding of border ownership in monkey visual cortex. The Journal of Neuroscience 20:6594–611.Google Scholar