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		<title>Sovereign AI: Why Running Models Locally May Be the Only Way to Truly Audit Them</title>
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		<category><![CDATA[AI Governance]]></category>
		<category><![CDATA[business intelligence]]></category>
		<category><![CDATA[cloud computing]]></category>
		<category><![CDATA[data sovereignty]]></category>
		<category><![CDATA[EU AI Act]]></category>
		<category><![CDATA[federated queries]]></category>
		<category><![CDATA[Large Language Models]]></category>
		<category><![CDATA[NIST AI RMF]]></category>
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		<category><![CDATA[risk assessment]]></category>
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					<description><![CDATA[A new formal framework proves that AI risk assessment capability is mathematically bounded by infrastructure sovereignty, showing that cloud models with superior accuracy unlock zero governance mechanisms while self-hosted models enable full auditing on commodity hardware.]]></description>
		
		
		
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