Nguni Machina: Explorations in AI, neural networks/machine learning music generation.

3 min readMay 22, 2021

Could AI make all this hardware obsolete or is its future entrenched in collaboration with human artists?

The initial motivation for the Nguni Machina project was driven by curiosity: How compelling can AI-generated music sound in 2021. As this was in itself a very subjective question without a clear cut answer due to how we as humans respond to art I had to establish some form of yardstick to gauge the success of the project.

This is where I turned to the age-old Turing Test proposed by one of the earliest figures in Artificial Intelligence, Alan Turing who himself in the early developments of AI theory had dabbled in rudimentary art created using an early computer in 1951. The Test: a test of a machine’s ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. If the art created by the machine is indistinguishable in a blind test to its human counterpart, this would pose some measure of success.

The results were surprising, they were flourishes of “artistic brilliance” in some of the pieces. This led to the development of Nguni Machina into a more expansive project that would not only address ai but other fields of particular interest.

Nguni Machina is open source and released under the creative commons license to encourage interaction and interrogation of its questions.

The questions:

Who owns art created by AI?
What is the role of a human artist in the era of compelling AI-created art?
How easy is it to create such works and the practicality of the exercise.

The project was created using Google's Magenta which is an open-source research project exploring the role of machine learning as a tool in the creative process and MuseNet AI, a deep neural network that can generate musical compositions from collected training data from many different sources. using large collections of MIDI files spanning several genres, including jazz, pop, African, Indian, and Arabic styles. Additionally, a MAESTRO dataset was used.

It was important that I did not interfere with the AI in any way nor introduce any human assistance in the complete album creation process from composing, arranging to mixing and mastering which was all done by the machine.

This was done to ensure as accurate as possible a representation of what AI is able to create without any human assistance besides the initial data set training.

Also, it was important that the album did not overstay its welcome and remained with a relatively short runtime which ended up being 5 minutes enough time for the audience to grasp the concept and allow interpretation of its implications.

AI created music is not anything new as great examples recently by Babusi Nyoni with his Gqom Robot and others have proven to be exciting explorations of what is possible if we let the robots run free in popular culture.

There are two major camps of thought in terms of how AI in its current or immediate future could be:

AI as a collaborator

AI as a creator

Could our collaboration with AI lead to new kinds of art we’ve never before imagined?

/ NGUNI MACHINA: Open-source neural network explorations in artificial intelligence generated music. Released under the Creative Commons (cc) license for everyone to freely remix, share, rearrange, destroy or improve as they wish. Available on all platforms from 10.05.21