Unbound is a music genre discovery app that breaks listeners out of their Spotify suggestion bubbles by mathematically finding the music they are wired to love but have never discovered. Instead of relying on AI to hallucinate recommendations, Unbound fetches real listener tags from Last.fm, maps the user's "taste fingerprint," and uses a K-Nearest Neighbors (KNN) algorithm with cosine similarity against 40 global genre centroids to pick the top 5 unexplored matches. Gemini 2.0 Flash is then used purely for the explanation layer, translating the mathematical proximity into beautifully written, emotionally resonant reasons for why the genre fits the user's sound identity. It is the personalized, fully computed successor to the famous app - Every Noise at Once.
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