TIDE is a neuro-inspired architecture using stabilized asymmetric E-I networks with lateral inhibition and 80:20 balance that trains in under half the time of CTM while gaining +1.65% top-1 accuracy on perturbed ImageNet.
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Workshop report identifies AI gaps in physical interaction, brittle learning, and energy inefficiency, then proposes neuroscience principles and a research roadmap for NeuroAI.
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TIDE: Asymmetric Neural Circuits for Stabilized Temporal Inhibitory-Excitatory Dynamics
TIDE is a neuro-inspired architecture using stabilized asymmetric E-I networks with lateral inhibition and 80:20 balance that trains in under half the time of CTM while gaining +1.65% top-1 accuracy on perturbed ImageNet.
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NeuroAI and Beyond: Bridging Between Advances in Neuroscience and ArtificialIntelligence
Workshop report identifies AI gaps in physical interaction, brittle learning, and energy inefficiency, then proposes neuroscience principles and a research roadmap for NeuroAI.