Neural aesthetics

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An overview of the intersections of art, design and artificial neural networks in machine learning.


Artists, designers


Literature, resources

Courses and textbooks for artists

Video lectures
  • Gene Kogan, "Machine Learning for Artists", course taught at ITP, New York University, New York, Spring 2016. 6 lectures, ~15 hours. Incl. video recordings.
  • Gene Kogan, "The Neural Aesthetic", course taught at School Of Machines, Making, and Make-Believe, Berlin, Summer 2016. 8 lectures, ~18 hours.
  • A.I. Experiments, a resource on machine learning art developed by Alexander Chen, creative director at Google Creative Lab, with Yotam Mann, C Christiansen, Jonas Jongejan, Gene Kogan, Kyle McDonald, et al. Launched on 16 Nov 2016.

Scientific introduction into deep learning

  • Ian Goodfellow, Yoshua Bengio, Aaron Courville, Deep Learning, MIT Press, 2016.

Historization of deep learning

Recent debates on artificial intelligence in the humanities

Art and Culture

Avant-garde and modernist magazines, Artists' publishing, Graphic design, Photography, Typewriter art, Multimedia environments, Design research, Video activism, Urban practices, Zine culture, Demoscene, VJing, Live cinema, Art and technology centres, Cyberfeminism, Community television, Hacktivism, Art servers, Hackerspaces, CD-ROM art, Circuit bending, Pure Data, Media archives, VVVV, Maker culture, Glitch art, Live coding, Locative media, Libre graphics, Electromagnetism, Surf clubs, DIY biology, Post-digital, Neural aesthetics.
See also Art styles and movements.

communities of practice

Art and technology centres, Art servers, Circuit bending, Copyright activism, Cypherpunk, Data activism, Demoscene, Digital libraries, DIY biology, Federated networks, File sharing, FLOSS, Game art, Hacker culture, Hackerspaces, Hacktivism, Internet activism, Internet of things, Libre graphics, Live coding, Maker culture, Media archives, Net art, Neural aesthetics, Open hardware, Software art, VJing, VVVV.
See also Artists' cultures.