Mycélium Garden

Diane Schuh et al., 2022—2023
installation, Max/MSP, supervised learning

A machine listening prototype for mycelium’s electric waves, beyond sound. A wavelet analysis enables to sense the low-frequencies typical of mycelium’s electrical behaviour. A shallow Gaussian Mixture Model classifies this frequency distribution in real-time. The installation leverages machine learning uncertainty as a form of other-than-human microperformativity, which adds to those of the myceliums and their instrumental apparatus.

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Year
2022—2023

Credits
The project was developed by Diane Schuh, Roberto dell’Orco and David Fierro, with the support of Anne Sèdes, Alain Bonardi, Charlotte Janis and Stephen Whitmarsh, in collaboration with SPORA, the CICM group of Université Paris 8, the CSLF group of Université Paris Nanterre, and the ICM, in the context of a research-creation fellowship from EUR ArTeC.

Events
Exhibition @ MSH Paris Nord, Fr (May.2023)

Publication
Paper at FKL XI (2023)