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Open a larger version of the following image in a popup: Latent Listening — Studio Above&Below (Daria Jelonek & Perry-James Sugden)

Studio Above&Below (Daria Jelonek & Perry-James Sugden)

Latent Listening
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  • Latent Listening
Latent Listening is a computational artwork that transforms field recordings of local bird species into slowly unfolding three-dimensional forms across a four-storey LED façade. The work considers how artificial intelligence...
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Latent Listening is a computational artwork that transforms field recordings of local bird species into slowly unfolding three-dimensional forms across a four-storey LED façade. The work considers how artificial intelligence perceives, organises and interprets the acoustic world.

Developed through a custom AI model developed by the artists and generative 3D workflow, the installation analyses the frequency, rhythm and temporal relationships within bird choruses to generate an ever-changing visual language. At its centre lies a simple question: what does artificial intelligence see when it hears? Rather than translating sound into image, the work investigates the latent space through which machine learning models interpret information, a multidimensional realm where similarities, relationships and patterns emerge before they become recognisable outputs. The resulting forms are not representations of birds or sound, but manifestations of how a machine internally organises and understands complex acoustic environments.

Presented at an architectural scale, Latent Listening unfolds through a deliberately slow choreography informed by the rhythm of the source recordings. Within the movement of the city, the installation creates moments of stillness, inviting audiences to reflect on the invisible processes through which artificial intelligence transforms non-human information into spatial form.

Rather than presenting AI as a tool for efficiency or automation, Latent Listening proposes a more contemplative encounter with machine perception. By giving form to the hidden processes of interpretation, the work encourages reflection on how artificial intelligence mediates our understanding of the living world, revealing that every act of perception, whether biological or computational, is shaped by the structures through which information is organised. The work proposes latent space not simply as a technical mechanism within machine learning, but as a new conceptual territory for thinking about perception, knowledge and our relationship with more-than-human intelligence.

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