video1.0<iframe src="https://www.loom.com/embed/decee52626eb431e8bd52f632d76c693" frameborder="0" width="1728" height="1296" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>12961728Loomhttps://www.loom.com12961728https://cdn.loom.com/sessions/thumbnails/decee52626eb431e8bd52f632d76c693-4f6021745869eff8.gif329.003Hi, this is my Vibridge applied AI music recommender system. I built it from the Module 3 music recommender and added confidence scoring, bias direction checks, edge case warnings, and logging for reliability. I ran three interactive preference examples. With a balanced pop happy profile at energy 0.85 and stance 0.8, system health was healthy with no edge cases detected and it showed top 5 recommendations with mostly medium confidence. With rock sad at energy 0.9 and balance 0.2, it flagged an edge case and lower confidence due to contradictions. I also tested a lofi chill profile with energy 0.5 and acoustic yes, with no edge cases. No action was requested from viewers.