<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/5fea292175a64ef6bfd8686b143c85d5&quot; frameborder=&quot;0&quot; width=&quot;1152&quot; height=&quot;864&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>864</height><width>1152</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>864</thumbnail_height><thumbnail_width>1152</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/5fea292175a64ef6bfd8686b143c85d5-83808e78a95bd9e1.gif</thumbnail_url><duration>300.177</duration><title>Vive Finder AI Music Mood Matching Emoji🎵</title><description>Hi everyone, I am Jamale, and this is my final applied AI system project, Vive Finder AI. I built a four layer system that checks input contradictions, converts your natural language mood into a structured profile, ranks songs with a weighted score, and generates an English summary explaining why. In my demo, with a happy, danceable, high energy request, it ranked 20 songs and the top result was Sunrise City at 0.82. I also tested a classical, sad, very quiet vibe to show how it handles conflicting signals. I did not ask viewers to take any action.</description></oembed>