A brain-inspired cognitive system that mimics the dynamics of human thought

Ji, Yuehu, Gamez, David ORCID logoORCID: https://orcid.org/0000-0002-3075-655X and Huyck, Christian R. ORCID logoORCID: https://orcid.org/0000-0003-4015-3549 (2018) A brain-inspired cognitive system that mimics the dynamics of human thought. Artificial Intelligence XXXV: 38th SGAI International Conference on Artificial Intelligence, AI 2018, Cambridge, UK, December 11–13, 2018, Proceedings. In: AI-2018 Thirty-eighth SGAI International Conference on Artificial Intelligence, 11-13 Dec 2018, Cambridge, UK. ISBN 9783030041908. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-030-04191-5_4)

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In recent years, some impressive AI systems have been built that can play games and answer questions about large quantities of data. However, we are still a very long way from AI systems that can think and learn in a human-like way. We have a great deal of information about how the brain works and can simulate networks of hundreds of millions of neurons. So it seems likely that we could use our neuroscientific knowledge to build brain-inspired artificial intelligence that acts like humans on similar timescales. This paper describes an AI system that we have built using a brain-inspired network of artificial spiking neurons. On a word recognition and colour naming task our system behaves like human subjects on a similar timescale. In the longer term, this type of AI technology could lead to more flexible general purpose artificial intelligence and to more natural human-computer interaction.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Paper published as:
Ji Y., Gamez D., Huyck C. (2018) A Brain-Inspired Cognitive System that Mimics the Dynamics of Human Thought. In: Bramer M., Petridis M. (eds) Artificial Intelligence XXXV. SGAI 2018. Lecture Notes in Computer Science, vol 11311. Springer, Cham
Research Areas: A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 24994
Notes on copyright: The final authenticated version is available online at https://doi.org/10.1007/978-3-030-04191-5_4
Useful Links:
Depositing User: David Gamez
Date Deposited: 18 Sep 2018 14:37
Last Modified: 29 Nov 2022 19:26
URI: https://eprints.mdx.ac.uk/id/eprint/24994

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