Towards spike-based machine intelligence with neuromorphic computing.

Abstract:

:Guided by brain-like 'spiking' computational frameworks, neuromorphic computing-brain-inspired computing for machine intelligence-promises to realize artificial intelligence while reducing the energy requirements of computing platforms. This interdisciplinary field began with the implementation of silicon circuits for biological neural routines, but has evolved to encompass the hardware implementation of algorithms with spike-based encoding and event-driven representations. Here we provide an overview of the developments in neuromorphic computing for both algorithms and hardware and highlight the fundamentals of learning and hardware frameworks. We discuss the main challenges and the future prospects of neuromorphic computing, with emphasis on algorithm-hardware codesign.

journal_name

Nature

journal_title

Nature

authors

Roy K,Jaiswal A,Panda P

doi

10.1038/s41586-019-1677-2

subject

Has Abstract

pub_date

2019-11-01 00:00:00

pages

607-617

issue

7784

eissn

0028-0836

issn

1476-4687

pii

10.1038/s41586-019-1677-2

journal_volume

575

pub_type

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