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NeuroMesh is a distributed training protocol designed to organize the underutilized computing power of devices worldwide for the development of large AI models. By leveraging Predictive Coding Networks (PCN) over the conventional Back Propagation (BP) algorithm, NeuroMesh achieves efficient parallelization, asynchronous learning, and low network costs, facilitating scalable distributed training.
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