Robot DJs: Better Spotify Playlists through Music Theory and Discrete Optimization

GOTO Chicago 2019

I am a Spotify addict, former DJ, amateur musician, and professional software engineer. I take special pride in making expertly-curated playlists for myself and friends. It takes a lot of time and energy to set the right mood and tone, and even more time and energy to transition smoothly from one song to another in a way that makes sense and is pleasing to the ear. Through many years of practice, I've observed that making a good playlist is a lot like solving a puzzle; and just like puzzles, there are rules and patterns to follow if you want to produce a cohesive output. In this talk, we'll explore the notion of teaching these rules to a computer, building a planning & optimization algorithm that follows these rules, and letting it loose on a set of tracks to generate delightful playlists on Spotify. We'll also cover the basics of music theory and why certain songs sound better together. There will likely also be fast talking, live keyboard playing, and some unrehearsed demos against a random sample of Spotify playlists submitted by the audience.

This talk is from our partner.