| There is a group of highly dissatisfied users (like me) who have found that current solutions are really inadequate. You'll have to trust me on this. Using suggestion models based on curated reputable crowdsourcing as opposed to simply volume of popularity is a way around this. Here's a contrived example; say I'm looking for something that goes well with say, Lonnie Smiths' 1980 "In the Park" (http://www.youtube.com/watch?v=uBPSf-VoDZk) and say, Jon Lucien's Listen Love (http://www.youtube.com/watch?v=6Bm7c0z_0ws) and let's toss Fela Anikulapo Kutis' Witchcraft in there (http://www.youtube.com/watch?v=31cGWpe8_L0). There is no software in the world that can curate music like that based on predictive modeling that I've seen. I've been trying to make one for years that can span decades, nations, and genres like that. I've found that if I aggregate a selective circle of people than I can get there. But that's the only way I've found so far. Ok, USE CASE 2. What's Justin Bieber or Keith Richards currently listening to? What about a talent scout at BMI? What if you could follow and tap into those people's personal playlists like twitter allows you to tap into what's on their plates for dinner and other personal things? And I mean right now. Shania Twain hits play and it sends that to the server. Thousands of users world-wide tapping into her personal radio station immediately get a non-time-shifted instant feedback. I think it would be compelling and addictive. It's the classic celeb allure that's been twitter's mainstream pot of gold. |