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minimizing error and maximizing efficiency, is computationally challenging—no known polynomial-time algorithm exists to solve it optimally in all cases. Because of this complexity, researchers typically rely
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science, and brain-inspired computation, encompassing a wide range of specialties such as algorithmic approaches, hardware innovations, artificial intelligence, deep learning, and the software foundations
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