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Reservoir computing and the Sooner-is-Better bottleneck

Published online by Cambridge University Press:  02 June 2016

Stefan L. Frank  and
Hartmut Fitz
Stefan L. Frank
Affiliation:
Centre for Language Studies, Radboud University Nijmegen, 6500 HD Nijmegen, The Netherlands. s.frank@let.ru.nlwww.stefanfrank.info
Hartmut Fitz
Affiliation:
Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands. hartmut.fitz@mpi.nlwww.mpi.nl/people/fitz-hartmut
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Abstract

Prior language input is not lost but integrated with the current input. This principle is demonstrated by “reservoir computing”: Untrained recurrent neural networks project input sequences onto a random point in high-dimensional state space. Earlier inputs can be retrieved from this projection, albeit less reliably so as more input is received. The bottleneck is therefore not “Now-or-Never” but “Sooner-is-Better.”

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 39 , 2016 , e73
Copyright
Copyright © Cambridge University Press 2016 

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