CORDIS Project
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FELICE develops a novel computing architecture for edge AI that integrates processing and memory to enhance real-time learning and decision-making. By utilizing ferroelectric leaky integrate-and-fire neurons and non-volatile memory, it significantly reduces power consumption and area requirements, making it suitable fo…
The rapid growth of AI demands efficient hardware solutions that enable real-time learning and decision-making in power-constrained edge applications, such as autonomous systems, medical diagnostics, and industrial monitoring.
However, current AI hardware faces fundamental trade-offs between power consumption, processing efficiency, and accuracy, limiting its deployment at the edge.
Traditional computing architectures separate memory and processing, leading to high energy costs associated with d…
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