What's particularly interesting about it is how the recommendations cross genres, but remain more-or-less consistent to mood.
lots of nice variety in there, and interesting choices.
This is an outgrowth of SIMAC, a project at the Universitat Pompeu Fabra in Barcelona. I first heard from them some time ago, I think it was two years ago, when they asked to use our entire catalog as a seeding engine, and also for demonstration. I then saw a demo back in April that looked promising. Now, they've launched it as a company.
Their current demo points to 30 second versions of our songs as downloads, and quite nicely has a magnatune logo next to each song that goes to the artist page for that song, thus providing a good, strong attribution.
The 2-D map feature is interesting, and shows how similar the genres are when doing a punk similarity search (it shows where a particular set of recommendations lie in a similarity map):
I was thinking about using this technology to generate "similar mood" playlists, and may do that in the future.