When: 11. April 2024, 15:00 - 18:00h (THU)

Where: Design & Computation studio - TU main building, Straße des 17. Juni 135, 10623 Berlin   (https://www.newpractice.net/get-here)  

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)

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.

Aron Petau, InKüLe SHK 

is a cognitive Science Bachelor, now enrolled in the Design and Computation Masters @ TU/UdK Berlin. He has prior experience in coding deep neural networks in Python and hates stuff that needs the cloud to run properly. Aron likes 3D Printing and researches in AI-Generated 3D Objects for further additive fabrication. He is also researching how to utilize generated Images within larger workflows and World Building. He is also employed within the UdK InKüLe project and hosting this workshop as part of the InKüLe peer-to-peer initiative.