Scalability Solutions
Explore hierarchical federated learning using Substrate's networking capabilities, where local models are aggregated at regional nodes before global aggregation, reducing communication overhead.
Optimizing Large-Scale Federated Networks
This hierarchical structure minimizes the amount of data transferred to the global aggregator, making federated learning more efficient for large networks, such as in a global initiative involving thousands of participants training a shared AI model coordinated through Substrate's off-chain workers.
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