I'm similar - I have an eclectic taste in music that is often not served well by static, long-term algorithms that place me into a "well" of the same sounding music. It's a problem I think about a lot.

Matrix factorization can deal with this a bit by using the high dimensional space to place your tastes into an area that reflects many different styles at the same time. In part 2 of the blog post we're going to talk about how we're modeling the acoustic qualities of music, which can find common patterns from completely different genres (for example, you may like soothing music with female vocals in both jazz and indie rock). In part 3 we'll talk a bit about how we can combine recent signals (like thumbs) to take into account your current mood, which I find helps pinpoint interesting music to surface right now.