Abstract
We are used to viewing noise as a nuisance in computing systems. This is a pity, since noise will be abundantly available in energy-efficient future nanoscale devices and circuits. I propose here to learn from the way the brain deals with noise, and apparently even benefits from it. Recent theoretical results have provided insight into how this can be achieved: how noise enables networks of spiking neurons to carry out probabilistic inference through sampling and also enables creative problem solving. In addition, noise supports the self-organization of networks of spiking neurons, and learning from rewards. I will sketch here the main ideas and some consequences of these results. I will also describe why these results are paving the way for a qualitative jump in the computational capability and learning performance of neuromorphic networks of spiking neurons with noise, and for other future computing systems that are able to treat noise as a resource.
Original language | English |
---|---|
Pages (from-to) | 860-880 |
Journal | Proceedings of the IEEE |
Volume | 102 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2014 |
Fields of Expertise
- Information, Communication & Computing
Treatment code (Nähere Zuordnung)
- Basic - Fundamental (Grundlagenforschung)