Big Data and music: Creating hit records with machine learning

May 14th, 2020

Title : Big Data and music: Creating hit records with machine learning
Blog#4
Name : Jevon Jerico
Student ID : D0708513
Written by : Bernard Marr

The music industry is using big data more and more. in this article, Bernard Marr asked his acquaintance, Alex,  how he produces his music. Alex then began to explain how the insights from the data contributed to the single. he said he scraped millions of conversations, newspaper headlines and speeches, all of which showed him how emotionally volatile we as humans are and have been, particularly over the last five years.


Based on the analytics, Alex picked the theme of “heartbreak” for his single. After settling on the theme, Alex used Watson BEAT, the cognitive system’s machine learning-driven music generation algorithms, to come up with different musical elements . The music is still created by a human being, but AI and machine learning has a big contribution on it.The resulting single, Not Easy, featuring Elle King, Sam Harris and Wiz Khalifa, reached number four in the iTunes Hot Tracks chart, and number six in the alternative chart, within 48 hours of its release.
 Marr conducted an interview with IBM and they said, "BEAT goes further than your average algorithmic suggestion engine to find a piece of music that might be appropriate. While generally this is done by matching ratings between listeners with similar tastes, Watson dives deeper into individual tracks to collect data on pitch, time and key signatures, and note sequences to work out what a listener might want to hear – or an artist may be inspired by."

Alex said, Musicians will use it to better understand their audience, to predict which songs will be successful, to tailor to specific market, and also help with the creative process of making music. Marr realized that this is the goal of every business and industry. AI and machine learning is therefore something all business leaders should be keeping an eye on.

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