Machine and learning, trial and error

His Master's Voice (HMV)

In the winter at Strata West I had a chance to see Oscar Celma of Pandora discuss machine learning from the perspective of the most established streaming music company. Because at root Pandora has a lot of human intelligence about music, its machine learning applications of song suggestion are even more interesting.

 The thing I picked up from Celma's presentation was that you can only get so far with your basic breed of suggestion engine. In the radio days a big voice intoned 'don’t touch that dial'. Now something else is in order.

 You see, if you play the straight and narrow and give them what you know they want, they get bored, and tune out. The element of surprise has been intrinsic to good showmanship immemorial . The machines can get better and better, but at a slower and slower rate. People eventually want to come across a crazed Jack Black pushing the 13th Floor Elevator button in HiFidelity.

The machines have trouble contemplating the likelihood that a viewer may be prone to enjoy Napoleon Dynamite, as was précised in this story about the 2008 NYTimes Magazine story about the Netflix algorithm contest that fate (my brother cleaning the upstairs) cast upon my stoop.

 TO BE CONTINuED