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    <title>InfoQ - Open Source - News</title>
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    <description>InfoQ Open Source News feed</description>
    <item>
      <title>Pinterest and Intel Take Open-Source Profiling to Internet Scale</title>
      <link>https://www.infoq.com/news/2026/11/pinterest-intel-profiling/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/pinterest-intel-profiling/en/headerimage/generatedHeaderImage-1793692423906.jpg"/&gt;&lt;p&gt;Pinterest has partnered with Intel to extend gProfiler, an open-source continuous profiler that provides production performance visibility across an internet-scale fleet of infrastructure.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>Code Generation</category>
      <category>Open Source</category>
      <category>Profilers</category>
      <category>Code Profiler</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Tue, 10 Nov 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/pinterest-intel-profiling/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-11-10T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/11/pinterest-intel-profiling/en</dc:identifier>
    </item>
    <item>
      <title>Open Source pg_vectorsearch Brings More Scalable Vector Search to PostgreSQL</title>
      <link>https://www.infoq.com/news/2026/11/postgresql-vector-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/postgresql-vector-search/en/headerimage/generatedHeaderImage-1792331528868.jpg"/&gt;&lt;p&gt;Tiger Data has released pg_vectorsearch, an open source PostgreSQL extension for vector similarity search, currently in alpha. Its PRISM index uses data partitioning and compression instead of the graph-based approach used by pgvector’s HNSW index, reducing memory requirements and index build times.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Database</category>
      <category>Relational Databases</category>
      <category>vector databases</category>
      <category>Open Source</category>
      <category>Postgres</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Sat, 07 Nov 2026 09:49:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/postgresql-vector-search/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-11-07T09:49:00Z</dc:date>
      <dc:identifier>/news/2026/11/postgresql-vector-search/en</dc:identifier>
    </item>
    <item>
      <title>Building a Culture for a Kubernetes-Based Platform in a Bank</title>
      <link>https://www.infoq.com/news/2026/11/culture-kubernetes-bank/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/culture-kubernetes-bank/en/headerimage/generatedHeaderImage-1793781033508.jpg"/&gt;&lt;p&gt;In banking, open source can earn trust by running real workloads, as Marcy Paramonova and Stéphane Cusin explained in their talk Building Cloud Native Culture in a Bank at KubeCon &amp; CloudNativeCon Europe. Deploying Kubernetes was the easy part; the hard part was culture: community of practice, shared knowledge, rituals, ownership. Teams try things, keep what works, and improve bottom-up.&lt;/p&gt; &lt;i&gt;By Ben Linders&lt;/i&gt;</description>
      <category>Platforms</category>
      <category>Regulation</category>
      <category>Open Source</category>
      <category>Open Banking</category>
      <category>Continuous Improvement</category>
      <category>Platform Engineering</category>
      <category>Culture Change</category>
      <category>learning</category>
      <category>Kubernetes</category>
      <category>Culture</category>
      <category>Community</category>
      <category>Culture &amp; Methods</category>
      <category>news</category>
      <pubDate>Thu, 05 Nov 2026 11:11:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/culture-kubernetes-bank/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</guid>
      <dc:creator>Ben Linders</dc:creator>
      <dc:date>2026-11-05T11:11:00Z</dc:date>
      <dc:identifier>/news/2026/11/culture-kubernetes-bank/en</dc:identifier>
    </item>
    <item>
      <title>Google Launches LiteRT Tensor API for Building, Customizing, and Optimizing ML Models for On-Device</title>
      <link>https://www.infoq.com/news/2026/11/litert-tensor-api/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/litert-tensor-api/en/headerimage/litert-tensor-api-1793729374644.jpeg"/&gt;&lt;p&gt;Google has introduced the LiteRT Tensor API, a lightweight C++ API that allows developers to build, customize, and optimize machine learning models directly for on-device execution. According to Google, it combines the flexibility of native model authoring with cross-platform portability.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>iOS</category>
      <category>GPU</category>
      <category>AI coding agents</category>
      <category>Open Source</category>
      <category>Google</category>
      <category>Android</category>
      <category>TensorFlow</category>
      <category>C++</category>
      <category>Mobile</category>
      <category>Edge Computing</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Tue, 03 Nov 2026 19:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/litert-tensor-api/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-11-03T19:00:00Z</dc:date>
      <dc:identifier>/news/2026/11/litert-tensor-api/en</dc:identifier>
    </item>
    <item>
      <title>Google and Meta Open-Source TorchTPU to Bring Native PyTorch Support to Google TPUs</title>
      <link>https://www.infoq.com/news/2026/11/torchtpu-native-pythorch-tpu/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/torchtpu-native-pythorch-tpu/en/headerimage/torchtpu-1793636927771.jpeg"/&gt;&lt;p&gt;TorchTPU is an open-source project developed by Google in collaboration with Meta that provides a native PyTorch backend for Google TPUs. It enables PyTorch workloads to execute on TPU hardware with minimal code modifications, supporting eager and compiled execution, distributed computing, and hardware-specific optimizations.&lt;/p&gt; &lt;i&gt;By Sergio De Simone&lt;/i&gt;</description>
      <category>GPU</category>
      <category>Open Source</category>
      <category>Facebook</category>
      <category>Google</category>
      <category>PyTorch</category>
      <category>Large language models</category>
      <category>Agents</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Mon, 02 Nov 2026 17:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/torchtpu-native-pythorch-tpu/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</guid>
      <dc:creator>Sergio De Simone</dc:creator>
      <dc:date>2026-11-02T17:00:00Z</dc:date>
      <dc:identifier>/news/2026/11/torchtpu-native-pythorch-tpu/en</dc:identifier>
    </item>
    <item>
      <title>File Mover Express: AWS Releases Open-Source Tool for S3 File Transfers</title>
      <link>https://www.infoq.com/news/2026/11/aws-s3-file-transfer/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/aws-s3-file-transfer/en/headerimage/generatedHeaderImage-1792218946629.jpg"/&gt;&lt;p&gt;AWS has recently released File Mover Express, an open-source application under the Apache 2.0 license for transferring large files between local systems and Amazon S3. Available for macOS, Windows, and Linux, it supports parallel transfers, automatic performance tuning, retries, pause and resume, and file integrity verification.&lt;/p&gt; &lt;i&gt;By Renato Losio&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>S3</category>
      <category>Open Source</category>
      <category>Data Transfer Objects</category>
      <category>Data Storage</category>
      <category>Go Language</category>
      <category>AWS</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Sun, 01 Nov 2026 06:32:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/aws-s3-file-transfer/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Open+Source-news</guid>
      <dc:creator>Renato Losio</dc:creator>
      <dc:date>2026-11-01T06:32:00Z</dc:date>
      <dc:identifier>/news/2026/11/aws-s3-file-transfer/en</dc:identifier>
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