<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>SynthID Bio — USASI news</title>
    <link>https://unitedstatesofamericasuperintelligence.com/open/synthid-bio/</link>
    <atom:link href="https://unitedstatesofamericasuperintelligence.com/open/synthid-bio/feed.xml" rel="self" type="application/rss+xml"/>
    <description>Dated, sourced news items in the USASI catalog that mention SynthID Bio. Independent project. Not a United States government website.</description>
    <language>en-us</language>
    <lastBuildDate>Tue, 13 Oct 2026 12:00:00 GMT</lastBuildDate>
    <item>
      <title>Google DeepMind introduces SynthID Bio and open-sources code for watermarking AI-designed proteins</title>
      <link>https://unitedstatesofamericasuperintelligence.com/news/google-deepmind-releases-synthid-bio/</link>
      <guid isPermaLink="true">https://unitedstatesofamericasuperintelligence.com/news/google-deepmind-releases-synthid-bio/</guid>
      <pubDate>Tue, 13 Oct 2026 12:00:00 GMT</pubDate>
      <category>research</category>
      <description>On September 30, 2026 Google DeepMind introduced SynthID Bio, a family of watermarking methods for AI-generated protein sequences and 3D structures, which it describes as a proof of concept. The repository README says SynthID Bio-sequence adds watermarked sampling to ProteinMPNN, and the announcement says SynthID Bio-structure fine-tunes a small part of AlphaFold 3's diffusion network so that predicted coordinates carry a detectable signature. Google DeepMind says it is publishing a methods paper, open-sourcing the code and in vitro data, and releasing weights to the research community. In the public repository, the software is licensed under Apache 2.0, the in vitro validation data supporting the paper is licensed under CC BY 4.0, and AlphaFold 3 model parameters remain under the AlphaFold 3 terms of use. USASI has not tested SynthID Bio.</description>
    </item>
  </channel>
</rss>
