What happens when you apply machine learning research to experimental sound – and then play live in front of a festival crowd? Recently, in St. Petersburg, RU, we got to find out.
Our team for Gamma_LAB AI gathered a diverse international team of artists, musicians, musicologists, coders, and researchers, including people who are deep in the field of data science work outside of the arts. (One of our co-hosts was juggling her work in path finding for drones – so not the usual media art approach to AI!) Organizing team (of which I was the only non-Russian member this time):
From Natalia Fuchs, Curator:
“My connection to AI is coming from my general research interests: I am a media art historian and I am deeply concerned by the new media research in relation with AI nowadays. I find it extremely stimulating and exciting – this enormous philosophical quest towards finding the big “other.” So as soon as I started to work closely with Helena Nikonole, conceptual artist of Gamma_LAB, being a peer for her “deus x mchn” project at Rodchenko School in Moscow and advising this artwork to the “Open Codes” exhibition at ZKM Centre for Art and Media in Karlsruhe, I was developing my curatorial approaches to art and AI. Then there were AI-related projects for the Barbican and CTM, but Gamma_LAB for me conceptually throwing my practice back to the Polytech.Science.Art program that I [previously was] curating at the Polytechnic Museum in Moscow. The way we build the processes here including theory, applied studies, performative aspects, it brings same strategy to the next level. In terms of the scale, Gamma_LAB with its connection to the Gamma Festival ([with its] 12000 visitors) has definitely jumped much higher.”
Adafruit has had paid day off for voting for our team for years, if you need help getting that going for your organization, let us know – we can share how and why we did this as well as the good results. Here are some resources for voting by mail, voting in person, and some NY resources for our NY based teams as well. If there are additional resources to add, please let us know – adafruit.com/vote
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