<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Explainable AI |</title><link>https://built-insight.org/tags/explainable-ai/</link><atom:link href="https://built-insight.org/tags/explainable-ai/index.xml" rel="self" type="application/rss+xml"/><description>Explainable AI</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 12 Jun 2026 14:50:00 +0000</lastBuildDate><image><url>https://built-insight.org/media/icon_hu_da05098ef60dc2e7.png</url><title>Explainable AI</title><link>https://built-insight.org/tags/explainable-ai/</link></image><item><title>可解釋與稽核之數據驅動預測性維護機制——結合語意建模與自動化執行</title><link>https://built-insight.org/events/htfa-2026-ai-facility/</link><pubDate>Fri, 12 Jun 2026 14:50:00 +0000</pubDate><guid>https://built-insight.org/events/htfa-2026-ai-facility/</guid><description>&lt;p&gt;受邀於台灣高科技廠房設施協會（HTFA）「AI 廠務新時代：創新技術的發掘與合作研討會」發表演講。&lt;/p&gt;
&lt;p&gt;本演講介紹結合語意建模與自動化執行之預測性維護機制，展示如何在高科技廠房環境中，透過知識圖譜與 LLM 推論引擎，實現安全、可控且具備因果邏輯的設施運維自動化決策。&lt;/p&gt;</description></item></channel></rss>