Keynote: Artistic Applications of Artificial Intelligence
summary
Survey of concrete outcomes not slogans artists use DeepDream outputs and variational autoencoder reconstructions to remake Blade Runner and receive a copyright takedown from Warner Brothers artists train GANs on personal datasets to produce faces and sell aesthetics an artist generates 300 ink drawings then trains pix2pix style models a robot is fed 21,000 sketches to redraw faces projects test recognition with adversarial makeup like CV dazzle and bots mash 3D Thingiverse parts into new objects
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chapters (17)
- 0:00Welcome
- 0:55ML transforms visual art
- 2:20Style transfer perspectives
- 4:13AI film reconstruction copyright
- 5:59Generative adversarial networks in art
- 8:05Artists train personal models
- 12:13AI image recognition
- 16:10AI tools shape art
- 20:08Artworks challenge AI
- 23:01Futures with AI art
- 26:21Ethics of AI art
- 28:23Audience questions on AI art criticism
- 30:52Funding AI art
- 32:44Commercial art world AI
- 34:14Artists use deep learning
- 36:46AI artist or tool?
- 38:23Closing
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