It’s like data mining, but the data is your music collection. I have roughly 3000 songs in my collection (legal, believe it or not), and I finally joined the iTunes bandwagon. A lot of my music came from a one-year subscription I had to the eMusic downloading service (which was $10/month for unlimited downloads at the time). I got a bunch of jazz this way, as well as some other random stuff that looked interesting–but I didn’t necessarily listen to all of it very much. Now with iTunes shuffling through my entire music collection, I am stochastically discovering interesting music that I might not have come across otherwise. A few of my favorites from the last few days:

Echo and the Bunnymen – Hide & Seek
The Future Sound of London – Divinity
John Cougar – Thundering Hearts
They Might Be Giants – XTC vs. Adam Ant
Arab Strap – Autumnal
Alphaville – Control
Heaven 17 – Dive

Now all we need is a sophisticated music mining algorithm to be developed to wade through those million song databases. The stochastic method is certainly fun, but it’s not terribly efficient.