We here summarize our experience running a challenge with open data for musical genre recognition. Those notes motivate the task and the challenge design, show some statistics about the submissions, and present the results.

Researchers tested the AI by having a pianist play a variety of music -- baroque, classical, ragtime and jazz -- in a live demonstration. The AI then assessed the likely genre in real time, vastly outperforming conventional software hand-coded by humans. "I think the deep learning system performs better because it's had a dispassionate look at quite a lot of audio material," says Monty Barlow, director of Machine Learning at Cambridge Consultants. "It's found the best way to detect one genre from another without any prejudice or bias. It's strangely more human-like in its capabilities than our programmers were in the classical engineering approach."