Descriptif

Dernière séance du séminaire de recherche Postdigital 2017-2019 sur l'imagination artificielle à travers le prisme des sciences, de l'informatique, des technologies, de l'art contemporain et de la philosophie.
Organisateurs : Béatrice Joyeux-Prunel (ENS), Alexandre Cadain (ENS), Vincent Rioux (Pôle numérique, ENSBA).

Rencontre avec Mario Klingemann et Matteo Pasquinelli autour de "Machines, culture subjectivité"

Introduction de Grégory Chatonsky
Mario Klingermann : "Instruments of Creation"
Matteo Pasquinelli : "On the Logical and Political Form of Machine Learning"

Instruments of Creation (Mario Klingemann)
The ability to wield tools is one of the core qualities that define humanity. The evolution of human culture has always run parallel to the evolution of the tools and instruments at our disposal. Machine learning and what is commonly known as artificial intelligence is a very recent instrument that we have created and we are starting to apply it to all possible areas, including the creation of art. As with any instrument it takes time to learn how to use it skillfully or how to play it masterfully. Mario Klingemann has been experimenting with the possibilities to create visual art with artificial neural networks for several years and is beginning to understand the potential and limitations of these instruments. In his talk he will give insights into his process and show some of the latest developments in this fast-moving field.

On the Logical and Political Form of Machine Learning (Matteo Pasquinelli)
Félix Guattari said that machines are « hyperdeveloped and hyperconcentrated forms of certain aspects of human subjectivity ». In which way then does machine learning « concentrate » social features and knowledge? My talk brings back the genealogy of the different techniques of machine learning (what is popularly termed as AI) to the paradigm of computational geometry that is shared by computer science pioneers such as Frank Rosenblatt, Marvin Minsky, John von Neumann and Konrad Zuse. If machine intelligence emerged with neural networks as a sophisticated technique of spatial pattern recognition, today’s computer scientists prefer the more general and abstract notion of input-ouput mapping. In this sense, (artificial) « intelligence » has become recently just the most effective solution to the problem of information compression. The problem of the definition of AI could stop here with this arid quantitative concept of « compression ». What information compression implies, however, is information loss and a new breed of errors, transformation of collective perception, apophenia (seeing things that are not actually there) and asymmetrical accumulation of knowledge yet to be discussed. If machine intelligence is distorted, however, this is not necessarily bad, as human knowledge and art are always a form of distortion, that is a hypothesis about the world.

Thèmes : Arts
Catégories: Séminaire de recherche Postdigital
Mot-clés : logiciel, informatique, numérique, sciences, machine learning, intelligence artificielle, imagination

Aucun exposé du même auteur.

Les Futurs de l'intelligence artificiell... Yann LeCun, Jean Ponce, Alexandre Cadain Qu'est-ce que l'imagination artificiell... Alexandre Cadain, Grégory Chatonsky Cybernétique, intelligence et imaginatio... Mathieu Triclot, Reza Negarestani Pouvoir, réseau et imagination Yves Citton, Jonas Lund Hesitant Hand. The Programmed, The Spont... Catherine Malabou, Ugnius Gelguda, Neringa Cerniauskaite Machines organiques, machines textuelle... Michel De Broin, Kim Gerdes

Mario Klingemann

Artiste

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Matteo Pasquinelli
Université des Arts et du Design de Karlsruhe
Professeur en philosophie des médias

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