SOURCE-LINKED INTELLIGENCE

Memristive Neurons and Synapses for Neuromorphic Edge Computing

CORDIS · observation · Publication date unknown

Memristive Neurons and Synapses for Neuromorphic Edge Computing In recent years, Artificial Intelligence has shifted towards collaborative learning paradigms, where multiple systems acquire and elaborate data in real-time and share their experience to improve their performance. MEMRINESS will generate new fundamental computing primitives that will overcome the current challenges for the deployment of intelligent systems on the edge. The requirements of a system operating on the edge are very tight: power efficiency, low area occupation, fast response times, and online learning. Brain-inspired architectures such as Spiking Neural Networks (SNNs) use artificial neurons and synapses that perform low-latency computation and internal-state storage simultaneously with very low power consumption, but at present they mainly rely on standard technologies, which make SNNs unfit to meet the above-mentioned constraints. Indeed, the dream of compact and efficient neurons and syna

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recordType

award

status

SIGNED

region

EU

value

1499488

unit

EUR