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Northwestern University researchers have printed artificial neurons from MoS2 and graphene ink that produce biologically realistic electrical spikes, which living mouse brain cells recognized as natural signals, a breakthrough with major implications for energy-efficient neuromorphic computing.
The article discusses the 'AI power wall' where compute growth outpaces efficiency gains, proposing four paradigm shifts—neuromorphic, photonic, memory-centric, and approximate computing—to make AI sustainable, and promotes the upcoming 'Watt Matters in AI' conference addressing full-stack energy reduction.
Proposes Selective Alignment Knowledge Distillation (SeAl-KD) for Spiking Neural Networks, which selectively aligns class-level and temporal knowledge by equalizing competing logits at erroneous timesteps and reweighting temporal alignment based on confidence and inter-timestep similarity, achieving consistent improvements over existing distillation methods on static and neuromorphic datasets.