Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Using AI as a Tool in Artistic Creation

60 views

Published on

Presented live at FITC Toronto 2018
More info at http://fitc.ca/event/to18/

Presented by Xavier Snelgrove, Element AI

Overview
The last couple years have seen an explosion in research using AI and machine learning techniques for creative purposes, especially for image creation. If you’ve seen apps like Prisma, or images from Google’s Deep Dream, then you’ve seen these algorithms in action. It’s early days, and while some of the new aesthetics are beautiful, the tools and approaches are still embryonic. In this talk Xavier will show work he and others have made with new algorithms, and explain at a high level how some of these neural-network based tools actually work. In particular he’ll explain his “multiscale neural texture synthesis” algorithm that has allowed for the creation of much more varied and high-resolution images.

Many of these techniques are not yet usable by people without a deep technical background, and Xavier will discuss directions he is taking his work to try to make the algorithms more accessible and expressive. Just as you don’t need to be an audio engineer to create electronic music on a synthesizer, neither should you need to be an AI researcher to create electronic images with a neural net. Just as you don’t expect a synthesizer to write your music, neither should we look to algorithms to create our images.

Objective
To share some of the advances in using AI to create images, and explain how the algorithms work.

Target Audience
Technically curious creatives who want to better understand how visual neural algorithms like style transfer and deep dream actually work.

Assumed Audience Knowledge
None: the talk will be mostly accessible, with just occasional more hardcore diversions

Five Things Audience Members Will Learn
How a neural network works (at a very high level)
How style transfer algorithms (like Prisma) work
Some tools they can use today to create neural images
Current frontiers in creative AI
Interesting artists working with AI today

Published in: Design
  • Be the first to comment

  • Be the first to like this

Using AI as a Tool in Artistic Creation

  1. 1. Using AI as a tool in artistic creation Xavier Snelgrove (@wxswxs) FITC Toronto, April 8, 2018
  2. 2. https://www.reddit.com/r/MachineLearning/comments/3a1ebc/image_generated_by_a_convolutional_network/ June 2015
  3. 3. August 2015 Gatys, L. A., Ecker, A. S., & Bethge, M. (2015, August 26). A Neural Algorithm of Artistic Style.
  4. 4. July 2016
  5. 5. July 2016 "Photoshop Filter Effect"
  6. 6. Explosion of work
  7. 7. Olah, et al., "The Building Blocks of Interpretability", Distill, 2018.
  8. 8. Miyato, T. et al, "cGANs with Projection Discriminator" ICLR 2018
  9. 9. Robbie Barrat: art-DCGAN https://github.com/robbiebarrat/art-DCGAN
  10. 10. Robbie Barrat: art-DCGAN https://github.com/robbiebarrat/art-DCGAN
  11. 11. Robbie Barrat: art-DCGAN https://github.com/robbiebarrat/art-DCGAN
  12. 12. Helena Sarin 2018: @glagolista
  13. 13. Mario Klingemann 2018 https://twitter.com/quasimondo/status/982711735001010176
  14. 14. Mario Klingemann 2018 https://twitter.com/quasimondo/status/982711735001010176
  15. 15. My (slightly out of fashion) technique (https://wxs.ca/research/multiscale-neural-synthesis/)
  16. 16. Layer 1 Layer 7 Layer 17
  17. 17. Layer 1 Layer 7 Layer 17
  18. 18. Layer 1 Layer 7 Layer 17 Generalization of colour!
  19. 19. Gram Matrix How often is the "fur" feature active at the same time as the "stripy" feature? Fur Eyes Grass Stripy Smooth Fur Eyes Grass Stripy Smooth 0.8 2.3 0.1 0.03 ... (This is an over-simplification…)
  20. 20. Optimization Create a new image that matches the Gram matrix of a target image (at multiple scales)
  21. 21. Open up a new possibility space Provide tools to explore this space
  22. 22. Levers of control
  23. 23. Initialization
  24. 24. Gram combination +
  25. 25. Gram modification
  26. 26. New directions: untargeted synthesis
  27. 27. New directions: animation
  28. 28. Code open-source
  29. 29. This is a microcosm for, more broadly, how we will interact with these algorithms.
  30. 30. Questions? Xavier Snelgrove http://wxs.ca @wxswxs
  31. 31. Subjective Function x Lionize Collaboration with Leo Krukowski: https://www.leokru.com/
  32. 32. Subjective Function x Lionize Collaboration with Leo Krukowski: https://www.leokru.com/

×