{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/decee52626eb431e8bd52f632d76c693\" frameborder=\"0\" width=\"1728\" height=\"1296\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1296,"width":1728,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1296,"thumbnail_width":1728,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/decee52626eb431e8bd52f632d76c693-4f6021745869eff8.gif","duration":329.003,"title":"Vibridge Music Recommender with Confidence and Bias Checks","description":"Hi, 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."}