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About This Project
Modern AI systems consume vast energy, limiting their use in real-time decision-making, especially in edge environments with constrained resources. Inspired by the brain's efficiency, we explore energy-efficient AI based on medically accurate neuron models (SNN's). We aim to simulate these models and test systems that reduce energy consumption and improve performance. Success will showcase the potential of brain-inspired computing for critical, real-time applications with limited training data.