Big Data and music: Creating hit records with machine learning

Big Data and music: Creating hit records with machine learning

How Big Data is being used in the music industry

I asked Alex to explain how the insights from the data contributed to the single, and he told me, “Watson scraped millions of conversations, newspaper headlines and speeches – all of which showed me 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 until he found ones that inspired him about how the piece should sound. So, it’s fairer to say the single was inspired by AI, rather than created by it. Nevertheless, this project shows that the technology is there to create a hit record using AI and machine learning.

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.

 

The technical details

IBM tells me that 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.

 

Ideas and insights you can steal

When I asked Alex where he saw AI taking music in the future, he said, “Musicians will use it to understand what their audience wants, to help more accurately predict which songs will be successful, to tailor songs to specific audiences, and even to help move the creative process into different spaces.”

To me, those sound like ambitions that any business should be striving for: to better understand what their customers want, to help predict more accurately which products or service elements will be successful, and to tailor products/services to specific customer segments. AI and machine learning is therefore something all business leaders should be keeping an eye on.

You can read more about how all types of companies and industries are using Big Data to drive success in Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results.


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Written by

Bernard Marr

Bernard Marr is a bestselling author, keynote speaker, and advisor to companies and governments. He has worked with and advised many of the world's best-known organisations. LinkedIn has recently ranked Bernard as one of the top 10 Business Influencers in the world (in fact, No 5 - just behind Bill Gates and Richard Branson). He writes on the topics of intelligent business performance for various publications including Forbes, HuffPost, and LinkedIn Pulse. His blogs and SlideShare presentation have millions of readers.

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