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      <title>Our approach to EU text provenance rules</title>
      <link>https://asksendai.com/post/2026/25/05/our-approa/</link>
      <pubDate>Mon, 05 Oct 2026 17:25:32 +0000</pubDate>
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      <description>&lt;figure&gt;&lt;img src=&#34;https://images.unsplash.com/photo-1712002641088-1191ef635cf2?crop=entropy&amp;amp;cs=tinysrgb&amp;amp;fit=max&amp;amp;fm=jpg&amp;amp;ixid=M3w5ODE4OTh8MHwxfHNlYXJjaHwxMHx8b3BlbmFpfGVufDB8MHx8fDE3OTE2NzkwMDR8MA&amp;amp;ixlib=rb-4.1.0&amp;amp;q=80&amp;amp;w=400&#34;&#xA;    alt=&#34;Our approach to EU text provenance rules&#34;&gt;&#xA;&lt;/figure&gt;&#xA;&#xA;&lt;p&gt;&#xA;Content provenance helps people understand where content came from, how it was created or edited, and whether it contains signals associated with our models. We’ve already made tools publicly available to identify images and audio generated by our models. Today, we’re sharing our approach to text watermarking in response to the EU AI Act, and how it fits into our broader work.&#xA;&lt;/p&gt;&#xA;&lt;p&gt;Source: &lt;a href=&#34;https://openai.com/index/eu-text-provenance/&#34;&gt;openai.com&lt;/a&gt;&lt;/p&gt;</description>
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