<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>InfoQ - Embedded Devices - News</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Embedded Devices News feed</description>
    <item>
      <title>Google DeepMind Launches EmbeddingGemma, an Open Model for On-Device Embeddings</title>
      <link>https://www.infoq.com/news/2025/09/embedding-gemma/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Embedded+Devices-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2025/09/embedding-gemma/en/headerimage/header+%2850%29-1757614506140.jpg"/&gt;&lt;p&gt;Google DeepMind has introduced EmbeddingGemma, a 308M parameter open embedding model designed to run efficiently on-device. The model aims to make applications like retrieval-augmented generation (RAG), semantic search, and text classification accessible without the need for a server or internet connection.&lt;/p&gt; &lt;i&gt;By Robert Krzaczyński&lt;/i&gt;</description>
      <category>Artificial Intelligence</category>
      <category>Google</category>
      <category>Open Source</category>
      <category>Google DeepMind</category>
      <category>Large language models</category>
      <category>Embedded Devices</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Thu, 11 Sep 2025 18:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2025/09/embedding-gemma/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Embedded+Devices-news</guid>
      <dc:creator>Robert Krzaczyński</dc:creator>
      <dc:date>2025-09-11T18:30:00Z</dc:date>
      <dc:identifier>/news/2025/09/embedding-gemma/en</dc:identifier>
    </item>
  </channel>
</rss>
