A short, intensive workshop exploring the current state of machine learning techniques for working creatively with audio. As a set of approaches for predictive pattern-matching—classifying, categorizing, translating, generating, etc—machine learning has been applied to everything from captions to gestures to maps to MIDI. Audio, with its intensely complex set of perceptual and contextual resonances, provides a tricky and illuminating challenge for machine learning.
The focus of this workshop will be on identifying the poetic possibilities inherent to this set of approaches, with the goal of initiating our own creative projects. Additionally, attention will be paid to philosophical and political questions embedded in the idea of ‘creative machine intelligence.’ What does it mean to work collaboratively with computers? Moreover, considering the resources required to develop this technology, what is lost when a small set of corporate research groups becomes responsible for the data collected, the tools developed, and the techniques shared? What strategies of resistance might be found in exploiting these techniques, data, and concepts for artistic purposes? What alternative tools are at our disposal for working (playing!) creatively using machine learning?
February 17.-21. 2020, 10:00 – 17:00
Place: BEK in Bergen, Norway
The workshop have a limited number of places. Applicants are kindly asked to submit a short bio and motivation for taking the workshop, and if you have already ongoing projects in the field or ideas for future ones give a short outline to help us prepare the workshop.
Freelance participants NOK 500.
5000 NOK for all academic employees in 50% positions or more.
Contact us for any questions, and we will help find solutions for your travel and stay in Bergen.
Register by December 15th via email to: email@example.com
Luke Fischbeck is an artist, composer, and organizer based in Los Angeles; a PhD candidate in the Interdisciplinary Media Art and Practice program at the University of Southern California, researching music, affect, and machine intelligence; and a contributing member of the collaborative group ‘lucky dragons’.
Image: ‘Rainbowgrams’ of a series of notes reconstructed by the WaveNet autoencoder. “Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders” Engel et al, 2017.
The workshop is produced in collaboration with Notam, as part of a workshop series that we jointly arrange for experienced artists. The workshops will be held in English, and will be arranged alternately in Oslo and Bergen between 2017 and 2020. There is a limited amount of places and highly qualified participants will therefore be prioritized. The series is supported by Arts Council Norway.