<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Private Deployment on C.CUI's Log</title><link>https://cuicaihao.github.io/tags/private-deployment/</link><description>Recent content in Private Deployment on C.CUI's Log</description><generator>Hugo</generator><language>en-AU</language><lastBuildDate>Sun, 30 Aug 2026 07:00:00 +1000</lastBuildDate><atom:link href="https://cuicaihao.github.io/tags/private-deployment/index.xml" rel="self" type="application/rss+xml"/><item><title>Unpacking AI Model Open Source: What's Truly 'Open'? A Full Panorama from Open Weights, Business Closed Loops, to Enterprise Adoption</title><link>https://cuicaihao.github.io/posts/2026-08-30-unpacking-ai-model-open-source-whats-truly-open-a-full-panorama-from-open-weights-business-closed-loops-to-enterprise-adoption/</link><pubDate>Sun, 30 Aug 2026 07:00:00 +1000</pubDate><guid>https://cuicaihao.github.io/posts/2026-08-30-unpacking-ai-model-open-source-whats-truly-open-a-full-panorama-from-open-weights-business-closed-loops-to-enterprise-adoption/</guid><description>The majority of the LLM &amp;lsquo;open source boom&amp;rsquo; is merely open weight, rather than genuine OSI-compliant open source. Major vendors open weights to construct a new closed-loop monetization model through public cloud compute taxes, private deployment TCO harvesting, and MaaS licensing barriers. This article dissects the four tiers of LLM openness and engineering reproducibility criteria, clarifies the underlying business balance sheet, and provides an actionable enterprise deployment guide covering MLA memory planning, quantization trade-offs, supply chain security, and hybrid routing architectures.</description></item></channel></rss>