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      <title>Google BigQuery Adds SQL-Native Managed Inference for Hugging Face Models</title>
      <link>https://www.infoq.com/news/2026/01/bigquery-sql-huggingface-managed/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Gemma</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/01/bigquery-sql-huggingface-managed/en/headerimage/generatedHeaderImage-1768996012519.jpg"/&gt;&lt;p&gt;Google has launched SQL-native managed inference for 180,000+ Hugging Face models in BigQuery. The preview release collapses the ML lifecycle into a unified SQL interface, eliminating the need for separate Kubernetes or Vertex AI management. Key features include automated resource governance via endpoint_idle_ttl and secure identity-based execution using existing data warehouse permissions.&lt;/p&gt; &lt;i&gt;By Steef-Jan Wiggers&lt;/i&gt;</description>
      <category>Gemma</category>
      <category>Google BigQuery</category>
      <category>Cloud</category>
      <category>Artificial Intelligence</category>
      <category>Hugging Face</category>
      <category>Google Cloud Platform</category>
      <category>Google Cloud</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>Architecture &amp; Design</category>
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      <category>news</category>
      <pubDate>Wed, 28 Jan 2026 10:55:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/01/bigquery-sql-huggingface-managed/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Gemma</guid>
      <dc:creator>Steef-Jan Wiggers</dc:creator>
      <dc:date>2026-01-28T10:55:00Z</dc:date>
      <dc:identifier>/news/2026/01/bigquery-sql-huggingface-managed/en</dc:identifier>
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    <item>
      <title>Google Introduces TranslateGemma Open Models for Multilingual Translation</title>
      <link>https://www.infoq.com/news/2026/01/google-translategemma-models/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Gemma</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/01/google-translategemma-models/en/headerimage/generatedHeaderImage-1769531019828.jpg"/&gt;&lt;p&gt;Google has released TranslateGemma, a set of open translation models based on the Gemma 3 architecture, offering 4B, 12B, and 27B parameter variants designed to support machine translation across 55 languages and to run on platforms ranging from mobile and edge devices to consumer hardware and cloud accelerators.&lt;/p&gt; &lt;i&gt;By Daniel Dominguez&lt;/i&gt;</description>
      <category>Gemma</category>
      <category>Natural Language Processing</category>
      <category>Google</category>
      <category>Model Fine Tuning</category>
      <category>Translation</category>
      <category>Large language models</category>
      <category>Reinforcement Learning</category>
      <category>Gemini</category>
      <category>Artificial Intelligence</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Wed, 28 Jan 2026 10:16:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/01/google-translategemma-models/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Gemma</guid>
      <dc:creator>Daniel Dominguez</dc:creator>
      <dc:date>2026-01-28T10:16:00Z</dc:date>
      <dc:identifier>/news/2026/01/google-translategemma-models/en</dc:identifier>
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