<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI/ML on Landry Zetam - Tech Blog</title><link>https://blog.landryzetam.net/tags/ai/ml/</link><description>Recent content in AI/ML on Landry Zetam - Tech Blog</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Mon, 11 Aug 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.landryzetam.net/tags/ai/ml/index.xml" rel="self" type="application/rss+xml"/><item><title>How I Clustered Three Mac Studios for Local AI Processing with GPUStack</title><link>https://blog.landryzetam.net/posts/gpustack-mac-clustering/</link><pubDate>Mon, 11 Aug 2025 00:00:00 +0000</pubDate><guid>https://blog.landryzetam.net/posts/gpustack-mac-clustering/</guid><description>&lt;h2 id="opening-hook">Opening Hook&lt;/h2>
&lt;p>I&amp;rsquo;ve always loved the idea of running powerful AI workloads without relying on expensive cloud GPUs. Recently, I turned that idea into reality by transforming three Mac Studios into a fully functioning local AI cluster using &lt;strong>GPUStack&lt;/strong>. This setup lets me run distributed inference workloads across multiple Macs with Apple Metal acceleration — and it&amp;rsquo;s a lot more affordable and energy-efficient than most people think.&lt;/p>
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&lt;p>&lt;strong>Related:&lt;/strong> See &lt;a href="https://blog.landryzetam.net/posts/mac-ai-cluster/">Mac AI Cluster: From EXO Vision to GPUStack Reality&lt;/a> for the philosophical journey that led to this technical implementation.&lt;/p></description></item></channel></rss>