SOURCE-LINKED INTELLIGENCE

Metaplastic Spintronics Synapses

CORDIS · observation · Publication date unknown

technology based on spintronics nanodevices that will prevent catastrophic forgetting, i.e. the loss of memory of previously learned tasks upon learning new ones, a major flaw currently faced by all artificial intelligence applications. We will develop a new class of neuromorphic hardware that will use magneto-ionics to support synaptic metaplasticity, i.e. a feature inspired by the human brain based on assigning a ‘hidden value’ to the states of artificial synapses to encode how important each state is. This will make it easier or harder to reconfigure the synaptic state upon learning a new task, giving a hierarchy to previously learned information and thus preventing catastrophic forgetting. The synaptic states will be given by the two magnetisation orientations in ferromagnets with perpendicular magnetic anisotropy, and by ferro/antiferromagnetic order in materials where the two phases coexist. In all cases, magneto-ionic gating will be used to locally modulate intrinsic magnetic properties to assign ‘hidden states’ to each synaptic state. The magneto-ionic hidden states will tra

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recordType

award

status

SIGNED

region

EU

value

2999750

unit

EUR