<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Open-Weight-Models on CuraSec</title><link>https://curasec.metacog.co.kr/tags/open-weight-models/</link><description>Recent content in Open-Weight-Models on CuraSec</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 17 Oct 2026 14:12:31 +0000</lastBuildDate><atom:link href="https://curasec.metacog.co.kr/tags/open-weight-models/index.xml" rel="self" type="application/rss+xml"/><item><title>Microsoft/NVIDIA whitepaper on open-weight AI model enterprise risk</title><link>https://curasec.metacog.co.kr/insights/2026-10-17-managing-open-weight-model-risk-in-enterprise-deployments/</link><pubDate>Sat, 17 Oct 2026 14:12:31 +0000</pubDate><guid>https://curasec.metacog.co.kr/insights/2026-10-17-managing-open-weight-model-risk-in-enterprise-deployments/</guid><description>&lt;ul>
&lt;li>&lt;strong>Engineer — Learn:&lt;/strong> Provides a shared taxonomy and control framework for open-weight model deployments; worth reading if you&amp;rsquo;re operationalizing models like Llama or Mistral in your infrastructure, but no immediate patch or config change required.&lt;/li>
&lt;li>&lt;strong>SOC/IR — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Microsoft and NVIDIA&amp;rsquo;s joint framework could anchor an internal AI governance policy for open-weight model use, but the summary is thin and this is vendor-backed guidance — useful background for a future AI risk board deck, not an immediate action.&lt;/li>
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