<?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/848702c45bd845cb835a419546d1d431&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/848702c45bd845cb835a419546d1d431-9c0e4e66e6da9b4c.gif</thumbnail_url><duration>324.518</duration><title>AI Playlist Organizer Walkthrough and Testing 🎵</title><description>Hi, this is my walkthrough of Playlist Chaos, an AI assisted music recognition and Playlist Organizer. I show how my recommendation system takes your input for genre, mood, and energy, then plans parameters, retrieves songs from a 32 song set, ranks them, and picks the top score, like 8.63 for a party setup. I also run a second example for chill lo fi with only two recommendations, where mood priority overrides raw genre ranking. I finish by testing multiple recommender cases and rack system scenarios for party, chill, and indie. No action is requested from viewers.</description></oembed>