First output co-authored with AI RAVE models: “Spoor” by MARTSM/\N

Artificial intelligence has recently spiked a significant popular interest especially due to easily accessible language models and image processing. 
In the audio realm, both sound processing as well as neural audio synthesis are becoming an integral part of the creative process and production chain and force us to reconsider established formations. 

Spoor has been written in collaboration with an artificial representation of myself in the form of various RAVE models that have been trained on different parts of my body of work. 
I consider these models instruments. I want to learn playing these instruments but I also want these models to hallucinate for me to observe, learn and react. 

The release is available on Bandcamp:

On Nina, I’ve released “Spoor Widen” – a bonus track to the mini album:


RAVE is “A variational autoencoder for fast and high-quality neural audio synthesis” created by Antoine Caillon and Philippe Esling at Artificial Creative Intelligence and Data Science (ACIDS) w/ IRCAM, Paris. 

Paper:  arxiv.org/abs/2111.05011
Source:  github.com/acids-ircam/RAVE