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    <title>Federated Learning on Referently.com</title>
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      <title>Training Without Collecting: How Federated Learning Redefines Data Ownership</title>
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      <pubDate>Wed, 25 Mar 2026 00:00:00 +0000</pubDate>
      
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      <description>Federated learning feels like a quiet inversion of how machine learning has traditionally worked. Instead of pulling data into one central place to train a model, the model itself travels outward, learning from data where it already lives. Phones, hospitals, edge devices, enterprise systems—each becomes a local training ground. The raw data never leaves its environment. Only the learned updates, the distilled “experience” of the model, are shared back and combined into something larger.</description>
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