Exploiting neuro-inspired dynamic sparsity for energy-efficient intelligent perception

Artificial intelligence (AI) has made significant strides towards efficient online processing of sensory signals at the edge through the use of deep neural networks with ever-expanding size. However, this trend has brought with it escalating computational costs and energy consumption, which have bec...

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Veröffentlicht in:	Nature communications Jg. 16; H. 1; S. 9928 - 15
Hauptverfasser:	Zhou, Sheng, Gao, Chang, Delbruck, Tobi, Verhelst, Marian, Liu, Shih-Chii
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 11.11.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166 639/166/987 Artificial intelligence Artificial neural networks Brain Co-design Computing costs Energy consumption Energy costs Energy efficiency Humanities and Social Sciences Information processing Memory multidisciplinary Neural networks Neurons Optimization techniques Perception Perspective Science Science (multidisciplinary) Sensors Sensory integration Signal processing Sparsity
ISSN:	2041-1723, 2041-1723
Online-Zugang:	Volltext
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