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    <title>InfoQ - Generative AI - Articles</title>
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      <title>Article: The Technology Adoption Curve, Twenty Years On</title>
      <link>https://www.infoq.com/articles/adoption-curve-twenty/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Generative+AI-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/adoption-curve-twenty/en/headerimage/generatedHeaderImage-1780670505517.jpg"/&gt;&lt;p&gt;Today, June 8th, InfoQ celebrates 20 years. This is not a comprehensive history, but a deliberately selective look at the technologies and practices InfoQ identified early, where they sit on the adoption curve in 2026, and how that curve may evolve over the next five to ten years.&lt;/p&gt; &lt;i&gt;By Renato Losio, Dio Synodinos&lt;/i&gt;</description>
      <category>Cloud</category>
      <category>Machine Learning</category>
      <category>Generative AI</category>
      <category>Technology Trends</category>
      <category>Java</category>
      <category>Agile</category>
      <category>Kubernetes</category>
      <category>Software Engineering</category>
      <category>Microservices</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>DevOps</category>
      <category>Culture &amp; Methods</category>
      <category>Development</category>
      <category>Architecture &amp; Design</category>
      <category>article</category>
      <pubDate>Mon, 08 Jun 2026 08:30:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/adoption-curve-twenty/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Generative+AI-articles</guid>
      <dc:creator>Renato Losio, Dio Synodinos</dc:creator>
      <dc:date>2026-06-08T08:30:00Z</dc:date>
      <dc:identifier>/articles/adoption-curve-twenty/en</dc:identifier>
    </item>
    <item>
      <title>Article: Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG</title>
      <link>https://www.infoq.com/articles/vector-search-hybrid-retrieval-rag/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Generative+AI-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/vector-search-hybrid-retrieval-rag/en/headerimage/vector-search-hybrid-retrieval-rag-header-1779972811121.jpg"/&gt;&lt;p&gt;In this article, author Aaditya Chauhan discusses the limitations of RAG pipelines based purely on vector search and how an internal omni-search application using Reciprocal Rank Fusion (RRF) that combines BM25 and vector results, can enhance the search solution.&lt;/p&gt; &lt;i&gt;By Aaditya Chauhan&lt;/i&gt;</description>
      <category>vector databases</category>
      <category>ElasticSearch</category>
      <category>Generative AI</category>
      <category>Retrieval-Augmented Generation</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Tue, 02 Jun 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/vector-search-hybrid-retrieval-rag/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Generative+AI-articles</guid>
      <dc:creator>Aaditya Chauhan</dc:creator>
      <dc:date>2026-06-02T09:00:00Z</dc:date>
      <dc:identifier>/articles/vector-search-hybrid-retrieval-rag/en</dc:identifier>
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