SOURCE-LINKED INTELLIGENCE

Quantum Materials for Integrated nanoscale Neuromorphic computing Devices

CORDIS · observation · Publication date unknown

Quantum Materials for Integrated nanoscale Neuromorphic computing Devices In the last years, artificial intelligence (AI) has driven critical advancements in sectors like healthcare, autonomous vehicles, entertainment, and finance, transforming science, technology, and our daily lives. Deep-learning neural networks (NNs) are central to many of these AI systems due to their ability to learn complex patterns, largely owing to their nonlinear activation function. However, NNs are typically built on traditional von Neumann architectures, where separate memory and processing units result in inefficiencies, leading to high costs and energy consumption as AI models grow more complex. This has boosted great interest in unconventional computing architectures, like neuromorphic computing, which mimics the brain's design for more sustainable and scalable AI systems. Photonics presents a promising solution here, offering unmatched speed, parallel processing, and energy efficiency that outpe

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award

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SIGNED

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EU

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193643.28

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EUR