n a world increasingly shaped by data-driven insights, the way we train artificial intelligence (AI) models has profound implications for innovation, user trust, and societal values. Conventional machine learning approaches often centralize vast amounts of sensitive data—medical records, personal photos, financial transactions—on servers or cloud platforms, raising concerns about privacy, security, and data ownership. Meanwhile,…

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