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Abstract The brain is the perfect place to look for inspiration to develop more efficient neural networks. The inner workings of our synapses and neurons offer a glimpse of what the future of deep learning might look like. This talk explores how we apply brain-inspired machine learning both at scale and at the edge. From large language models on tiny power budgets, to neuromorphic neuromodulation to help forecast neural disease, ultimately building systems that remain competitive with those coming from big tech companies at a tiny fraction of the cost. Description Join Asst. Prof. Jason Eshraghian (University of California, Santa Cruz) for the webinar, "Everything you always wanted to know about Neuromorphic Computing but were afraid to ask." This talk explores how we apply brain-inspired machine learning both at scale and at the edge. From large language models on tiny power budgets, to neuromorphic neuromodulation to help forecast neural disease, ultimately building systems that remain competitive with those coming from big tech companies at a tiny fraction of the cost.