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      <title>Tracking and Controlling Data Flows at Scale in GenAI: Meta’s Privacy-Aware Infrastructure</title>
      <link>https://www.infoq.com/news/2026/01/meta-pai-genai-data-flows/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Data+Lineage-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/01/meta-pai-genai-data-flows/en/headerimage/generatedHeaderImage-1768161477564.jpg"/&gt;&lt;p&gt;Meta has revealed how it scales its Privacy-Aware Infrastructure (PAI) to support generative AI development while enforcing privacy across complex data flows. Using large-scale lineage tracking, PrivacyLib instrumentation, and runtime policy controls, the system enables consistent privacy enforcement for AI workloads like Meta AI glasses without introducing manual bottlenecks.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>policy</category>
      <category>AI Architecture</category>
      <category>Products</category>
      <category>Data Privacy</category>
      <category>Architecture</category>
      <category>Privacy</category>
      <category>Data Lineage</category>
      <category>Generative AI</category>
      <category>Extensibility</category>
      <category>AI Development</category>
      <category>AI, ML &amp; Data Engineering</category>
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      <pubDate>Tue, 20 Jan 2026 15:00:00 GMT</pubDate>
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      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-01-20T15:00:00Z</dc:date>
      <dc:identifier>/news/2026/01/meta-pai-genai-data-flows/en</dc:identifier>
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