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When & Where: Time and space will be announced

Registration for UdK-students: inkuele@intra.udk-berlin.de (Please also state your course of study, your motivation for wanting to join and your expectations of this workshop)

Local Diffusion - Empower your own Stable Diffusion Generation

Workshop
Aron Petau, SHK InKüLe

Is it possible to create a graphic novel with generative A.I.?
What does it mean to use these emerging media in collaboration with others?
And why does their local and offline application matter?

With AI becoming more and more democratised and GPT-like Structures increasingly integrated into everyday life, the black-box notion of the mysterious all-powerful Intelligence hinders insightful and effective usage of emerging tools. One particularly hands-on example is AI generated images. Within the proposed Workshop, we will dive into Explainable AI, explore Stable Diffusion, and most importantly, understand the most important parameters within it. We want to steer outcomes in a deliberate manner. Emphasis here is on open and accessible technology, to increase user agency and make techno-social dependencies and power relations visible.

Empower yourself against readymade technology!
Do not let others decide on what your best practices are. Get involved in the modification of the algorithm and get surprised by endless creative possibilities. Through creating a short graphic novel with 4-8 panels, participants will be able to utilise multiple flavours of the Stable Diffusion algorithm, and will have a non-mathematical understanding of the parameters and their effects on the output within some common GUIs. They will be able to apply several post-processing techniques to their generated images, such as upscaling, masking, inpainting and pose redrawing. Further, participants will be able to understand the structure of a good text prompt, be able to utilise online reference databases and manipulate parameters and directives of the Image to optimise desired qualities. Participants will also be introduced to ControlNet, enabling them to direct Pose and Image composition in detail.