Advancements in quantum computing may present sustainable creative opportunities for artists experimenting with machine learning. ILĀ’s latest album ‘Quantum Computer Music’ aims to show how.
The project saw the London-based artist, producer and vocalist approach machine-learning systems as collaborators rather than automated generators.
Using a combination of quantum reservoir computing (QRC), DNA sonification and AI synthesis (more on that in a second), with her latest piece ILĀ has built on her earlier project ‘Recurse’ — a collaboration with quantum-technology company MOTH and Harvard University that was described as the “world’s first infinite mix”.
What is QRC, and how does it apply to music, you may ask? In brief: it’s a machine learning method in which data can be poured into a system — called the reservoir — causing the system to react in a number of complex ways.
ILĀ’s process involves training the system on her original vocal recordings, which the system produces its own “take” on. ILĀ then sculpts a new version, sometimes then feeding it back in for further iteration.
“It’s an evolving, self-referential dialogue between me and the machine that blurs the line between author and output,” ILĀ told Music Ally. “The outputs are not random generative fragments. In a way they’re reflections of myself through a quantum lens.”
Only available to highly specialised academic researchers until very recently, QRC is being newly utilised among creatives experimenting with small, high quality data sets.
“A big issue with many Large Language Models is that they’re trained on vast amounts of data scraped from the internet — often without artists’ permission,” ILĀ told BBC. “[QRC] requires far less data to create meaningful results, making it more sustainable and collaborative by nature.”
‘ The preceding article may include information circulated by third parties ’
‘ Some details of this article were extracted from the following source musically.com ’
