<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data Serialization on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/data-serialization/</link><description>Recent content in Data Serialization on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 26 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/data-serialization/index.xml" rel="self" type="application/rss+xml"/><item><title>Chapter 10: Building Custom Codecs for Unique Data Formats</title><link>https://ai-blog.noorshomelab.dev/openzl-mastery-2026/building-custom-codecs/</link><pubDate>Mon, 26 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/openzl-mastery-2026/building-custom-codecs/</guid><description>&lt;h2 id="chapter-10-building-custom-codecs-for-unique-data-formats"&gt;Chapter 10: Building Custom Codecs for Unique Data Formats&lt;/h2&gt;
&lt;p&gt;Welcome back, compression enthusiast! In the previous chapters, we explored OpenZL&amp;rsquo;s foundational concepts, its powerful compression graph model, and how to leverage its built-in codecs for various data types. You&amp;rsquo;ve seen how OpenZL intelligently applies different compression strategies based on your data&amp;rsquo;s structure.&lt;/p&gt;
&lt;p&gt;But what if your data is truly unique? What if it doesn&amp;rsquo;t fit neatly into existing types, or you have a highly specialized compression algorithm in mind that OpenZL doesn&amp;rsquo;t provide out-of-the-box? This is where the real power of OpenZL&amp;rsquo;s framework shines: the ability to define &lt;em&gt;custom codecs&lt;/em&gt;.&lt;/p&gt;</description></item></channel></rss>