“Scientists and engineers around the world have been attempting something undeniably impossible— and yet, no one could ever question their motives. Laid bare, the act of ‘understanding music’ by a computational process feels offensive. How can something so personal, so rooted in context, culture and emotion, ever be discretized or labeled by any autonomous process? Even the ethnographical approach — surveys, interviews, manual annotation — undermines the raw effort by the artists, people who will never understand or even perhaps take advantage of what is being learned and created with this research. Music by its nature resists analysis. I’ve led two lives in the past ten years— first as a “very long-tail” musician and artist, and second as a scientist turned entrepreneur that currently sells “music intelligence” data and software to almost every major music streaming service, social network and record label. How we got there is less interesting than what it might mean for the future of expression and what we believe machine perception can actually accomplish.
The core of the Echo Nest remains true to our dogma: we strongly believe in the power of data to enable new music experiences. Since we crawl and index everything, we’re able to level the playing field for all types of musicians by taking advantage of the information given to us by any community on the internet. Work in music retrieval and understanding requires a sort of wide-eyed passion combined with a large dose of reality. The computer is never going to fully understand what music is about, but we can sample from the right sources and do it often enough and at a large enough scale that the only thing in our way is a leap of faith from the listener.”