<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Embedding on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/embedding/</link><description>Recent content in Embedding on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 17 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/embedding/index.xml" rel="self" type="application/rss+xml"/><item><title>USearch &amp;amp; ScyllaDB Vector Search Practical Field Guide</title><link>https://ai-blog.noorshomelab.dev/guides/usearch-scylladb-vector-search-guide/</link><pubDate>Tue, 17 Feb 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/guides/usearch-scylladb-vector-search-guide/</guid><description>&lt;h2 id="welcome-to-the-world-of-ultra-fast-vector-search"&gt;Welcome to the World of Ultra-Fast Vector Search!&lt;/h2&gt;
&lt;p&gt;Are you ready to dive into one of the most exciting areas in modern AI and data management? This guide is your comprehensive pathway to mastering &lt;strong&gt;USearch&lt;/strong&gt; – an incredibly efficient open-source vector search library – and integrating it seamlessly with &lt;strong&gt;ScyllaDB&lt;/strong&gt;, a real-time, high-performance NoSQL database. Together, they form a powerhouse for building scalable, lightning-fast AI applications.&lt;/p&gt;
&lt;h3 id="what-is-usearch-and-scylladb-vector-search"&gt;What is USearch and ScyllaDB Vector Search?&lt;/h3&gt;
&lt;p&gt;Imagine you have millions of items – perhaps images, documents, or user queries – and you want to find others that are &amp;ldquo;similar&amp;rdquo; in meaning or content, not just by exact keyword matches. This is where &lt;strong&gt;vector search&lt;/strong&gt; shines!&lt;/p&gt;</description></item></channel></rss>