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The Prix Ars Electronica Showcase is a collection where all the artist submissions for the Prix since 1987 can be searched and viewed. The winning projects are documented with extensive information and audio-visual media. ALL other submissions are displayed with a basic metadata in list form.

Digital Musics & Sound Art Golden Nica 2021

Convergence

Alexander Schubert
321240Original: Alexander_Schubert_-_Convergence_Ensemble_Resonanz_KampnagelEclat.mp4 | 1920 * 1080px | 34m 25s | 445.3 MB
321243Original: Alexander_Schubert_-_Presentation_Convergence_Eclat_Festival_Presentation_Series.mp4 | 1280 * 720px | 85m 49s | 1.1 GB
Original: DM_210737_256470_AEC_PRX_2021_convergence_2_3122140.jpg | 3840 * 2160px | 1.1 MB | Alexander Schubert
Original: DM_210737_256470_AEC_PRX_2021_convergence_4_3122144.jpg | 3840 * 2160px | 759.0 KB | Alexander Schubert
Original: Convergence_18.jpg | 3840 * 3840px | 1.2 MB | Alexander Schubert
Original: Convergence_24.jpg | 3840 * 3840px | 1.7 MB | Alexander Schubert
Original: Convergence_27.jpg | 3840 * 3840px | 2.3 MB | Alexander Schubert
Original: convergence_staged_version.jpg | 1895 * 1895px | 560.2 KB | Alexander Schubert
Original: instruments_mosaic_ep40.png | 1080 * 1080px | 849.8 KB | Alexander Schubert
Original: violin_mosaic_ep79.png | 1080 * 1080px | 698.4 KB | Alexander Schubert
    • CATALOG TEXT
    • CREDITS
    • BIOGRAPHY
    Convergence uses the concept of Artificial Intelligence to learn features of human musicians and then recreate new entities based on these recordings. In the piece the players interact with their generated counter-parts. They see theirselves transform and reshape. The technology used is centered around Auto-Encoders (and GANs). Metaphorically they demonstrate a world that is constructed and parametric. The friction between machine perception and human world perception is the starting point for questions that address the fluidity of the self and the restrictions of perception. 

    Human world and self models are parametric systems that make abstract assumptions and classifications of our surroundings. These processes happen partly subconscious and unreflected. They give us the impression of an absolute truth or reality, as the constructed concepts, identities and beliefs are persuasive and internal. That these constructive models are fluid and subject to change is examined through the use of AI in this context. Auto-Encoders allow a formalization of the input data —in this case faces, bodies, and voices. The deep learning yields a low-dimensional—abstract or high-level— description of the input. Contrary  to our black box human mind, the high level parameters in the algorithm are accessible and can be edited and transformed.  

    In this sense the AI systems makes it possible to warp the representation of the human performers, thus stressing the fluidity of the modeling: A different person, character trait, evaluation, or gender is far less substantially disparate as the subject would anticipate. The transformation of the parameters posses the character of (social, societal, clinical, or biological) mind-altering states. The AI system is used to enable this altering with the aim to question the robustness and immobility of identity and world models. It tries to expose the internal constructiveness and in this sense works as a mirroring device. It recreates partial aspects of our perception and classification and through its alteration allows the viewer to draw a parallel to our own mental world building processes. 

    Listen to me now 
    I want to ask you a few questions 
    How do we differentiate  
    if it is a hallucination,  
    a dream 
    or clean perception?  
    All perception is constructive 
    No representation is absolute 
    Everything is encoded 
    and decoded 
    We are parametric 
    Everything parametric can be altered 
    parameter by parameter 
    That is the definition of such a model 
    Normally, we don’t see these sliders 
    these values 
    these adjustment dials 
    But they can move into our consciousness 
    through illness 
    through hallucination 
    through drugs 
    through psychotic states 
    or through computation processes 
    like in this case 
    We then see the constructive aspect of it 
    That everything we do  
    is based on encoding and decoding 
    When we look at a partner  
    we can create a loop 
    A perception and adjustment loop 
    We can exponentiate that process  
    by looking into a mirror 
    This is what we will do now 
    Recursive loops 
    You 
    And Me 
    Regression curls 
    Segregation twirls 
    Adaptive coils 
    A semi-transparent foil 
    I don’t know more than you do  
    I’m also just a mirror of you  
    As I provide a mirror for you  
    In a loop,  
    we can try to turn the opacity  
    of our perception into opaque variations  
    Like a brain lesion  
    a mesmerizing distortion 
    As in a sleep-deprived state  
    Drifting off into a halfword  
    of a dreamlike morphed reality  
    Where we see that other representations  
    of us are possible  
    That our self is fluid,  
    fragile,  
    constructed  
    and diverse 
    post human 
    Like a genetic defect  
    beautifully disturbed  
    genetically enhanced 
    adjusted 
    In a recursive loop 
    I encode and decode myself,  
    in an eternal loop 
    Exaggerating every feature 
    Like a facial distortion 
    Like an unsupervised inbreed 
    Out of control 
    Go to sleep, child 
    Dream off now 
    Saturate with closed eyes 
    Dreaming, of a future  
    and an optimized tomorrow 
    Hand in hand,  
    sliders adjusted, 
    The night sky setting,  
    as the values adjust 
    Peaceful 
    Invisible 
    A clear view of the night 
    Through a transparent interface 
    Always on 
    Always present 
    And  
    Always  
    Loving 

    Text excerpts Convergence, Alexander Schubert
    Ensemble Resonanz 
    Co-developed with IRCAM, Paris 
    Audio Deep Learning Programming: Antoine Caillon, Philippe Esling, Benjamin Levy (Ircam) 
    Video Deep Learning Programming: Jorge Davila-Chacon (Heldenkombinat) 
    Convergence was developed as part of #bebeethoven, a project of PODIUM Esslingen. 
    Funded by Kulturstiftung des Bundes. Digital version commissioned by Eclat Festival.
    Alexander Schubert (DE) (1979) studied bioinformatics, multimedia composition. He’s a professor at the Musikhochschule Hamburg. Schubert’s interest explores the border between the acoustic and electronic world. In music composition, immersive installation, and staged pieces he examines the interplay between the digital and the analogue. He creates pieces that realize test settings or interaction spaces that question modes of perception and representation. Continuing topics in this field are authenticity and virtuality. The influence and framing of digital media on aesthetic views and communication is researched in a post-digital perspective. Recent research topics in his works were virtual reality, artificial intelligence, and online-mediated artworks. Schubert is a founding member of ensembles such as Decoder. His works have been performed more than 700 times in the last few years by numerous ensembles in over 30 countries.
    Links: http://www.alexanderschubert.net/works/Convergence.php, https://www.youtube.com/watch?v=o5UXkJWJciQ, https://www.youtube.com/watch?v=laoV7cGXUNo&t=0s
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