Training AI models across distributed devices rather than a central server, decentralized training enhances data privacy and reduces bandwidth costs. It allows organizations to collaboratively improve models without sharing sensitive information. Developers, researchers, and privacy-focused industries benefit from faster, scalable updates while maintaining compliance with data regulations.
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