Federated Learning: Collaborative AI Training While Preserving Data Privacy

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Introduction

In an increasingly data-driven world, the development of sophisticated Artificial Intelligence (AI) models often hinges on access to vast datasets. However, a significant challenge arises when this data is sensitive, proprietary, or legally restricted from leaving its source. Traditional machine learning approaches typically require centralizing data on powerful servers, which is often not feasible due to privacy concerns, regulatory compliance (like GDPR or HIPAA), or simply the sheer volume of data at

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