Before revision: Biological neural networks operate with extraordinary energy efficiency, owing to properties such as spike-based communication and synaptic plasticity driven by local activity. When emulated in silico, such properties also enable highly energy-efficient machine learning and inference systems. However, it is unclear whether these mechanisms only trade off performance for efficiency or rather they are partly responsible for the superiority of biological intelligence.
After revision: Biological neural networks operate with extraordinary energy efficiency, owing to properties such as spike-based communication and local synaptic plasticity. It remains unclear whether these mechanisms only trade off performance for efficiency or rather they are partly responsible for the superiority of biological intelligence.