Artistic Strategies to Guide Neural Networks
- URL: http://arxiv.org/abs/2307.07521v1
- Date: Thu, 6 Jul 2023 22:57:10 GMT
- Title: Artistic Strategies to Guide Neural Networks
- Authors: Varvara Guljajeva, Mar Canet Sola, Isaac Joseph Clarke
- Abstract summary: This paper explores the potentials and limits of current AI technology, in the context of image, text, form and translation of semiotic spaces.
In a relatively short time, the generation of high-resolution images and 3D objects has been achieved.
Yet again, we see how artworks act as catalysts for technology development.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Artificial Intelligence is present in the generation and distribution of
culture. How do artists exploit neural networks? What impact do these
algorithms have on artistic practice? Through a practice-based research
methodology, this paper explores the potentials and limits of current AI
technology, more precisely deep neural networks, in the context of image, text,
form and translation of semiotic spaces. In a relatively short time, the
generation of high-resolution images and 3D objects has been achieved. There
are models, like CLIP and text2mesh, that do not need the same kind of media
input as the output; we call them translation models. Such a twist contributes
toward creativity arousal, which manifests itself in art practice and feeds
back to the developers' pipeline. Yet again, we see how artworks act as
catalysts for technology development. Those creative scenarios and processes
are enabled not solely by AI models, but by the hard work behind implementing
these new technologies. AI does not create a 'push-a-button' masterpiece but
requires a deep understanding of the technology behind it, and a creative and
critical mindset. Thus, AI opens new avenues for inspiration and offers novel
tool sets, and yet again the question of authorship is asked.
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