The AI Lab is part of the Electronic Media department in the Faculty of Art. In the AI Lab, the examination of artificial intelligence systems is not only about the mere application of the technology for one's own practice, but also about a deeper understanding of the underlying processes and their reflection. Practical criticality enables artists and designers to not only use existing tools according to predefined methods, but also to modify them according to their own needs. This critical examination of AI is urgently needed in view of its rapid spread in society. Artistic / design research into AI systems is particularly well suited to this task due to its sensory experience and openness to the results. We therefore combine theory and practice, art and AI, technology and design.

Funded by the German Federal Ministry of Education and Research as part of the joint project "KITeGG KI greifbar machen und begreifen: Technologie und Gesellschaft verbinden durch Gestaltung (Making AI tangible and understandable: Connecting technology and society through design)". Further information https://gestaltung.ai/

Experimental AI Lab.​​
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AI systems have become deeply embedded in our everyday lives and are increasingly shaping our ideas of society, the world and ourselves. We want to experience and reflect on this ongoing process of AI-based worlding, shaped by data colonialism and generated/generating world models, through artistic research and aesthetic experiments.

The aim of the course is a deeper exploration of AI technologies. To this end, in the first half of the course we will get to know various technologies together in workshops and explore them experimentally. The second half of the course is dedicated to the individual development of a project based on the workshops, which can ideally be shown during the Rundgang at the AI Lab. In the workshops we will deal with tokens and prompting, LLMs, fine-tuning, chatbots and interfaces, image generation and embeddings, video generation, etc.

​Tuesday, 13:00 - 18:00

(Un-)Creative Coding with Python

»(Un-)Creative Coding with Python« teaches programming skills with Python from the ground up. This easy-to-learn general purpose programming language is used in many areas from image processing, parametric design to web scraping, data processing and machine learning. Python can be used to write stand-alone programs, but it can also be used as a scripting language to extend the functions of many software applications (Blender, Grasshopper, Touchdesigner, etc.).

We start with the installation and setup of a code editor before working on the following aspects using code examples and programming tasks: Syntax, variables, data types, functions, loops, control structures, input/output of data/media, external libraries.

Thursday, 13:00 - 18:00

In addition to courses and an open workshop, we organize AI evenings at irregular intervals to talk about art and design projects, current developments and papers over drinks and snacks. The evening is open to everyone, including interested people from outside the university. It serves as a platform for discussing AI topics. The content of the evenings can be shaped in a participatory way, for example, papers, tools or projects can be presented and discussed. If you have any suggestions, please get in touch with us: kuhn@hfg-offenbach.de, kuehr@hfg-offenbach.de

“What I had not realised is that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.” – Joseph Weizenbaum – Computer Power and Human Reason (1976)

The interactive installation »bl00t - ELIZA bot« explores interactions with a talking chatbot. An adaptation of Joseph Weizenbaum's ELIZA chatbot from 1966 speaks with a real-time AI voice and responds to typed user input. The simple ELIZA algorithm enables latency-free interaction. The robot's voice amplifies the (ELIZA) effect.

Raspberry PI 5, Python, Piper (text-to-speech), light sensor

Im Schaffensprozess sind wir häufig stark von den Tools abhängig, die wir nutzen. Sie können den Prozess so beeinflussen, dass die ursprüngliche Idee verloren gehen kann. Um dieses Feld zu untersuchen, hat Elise Olenina eine Reihe von Befehlen formuliert, die typischen Aufgaben im Designprozess entsprechen, etwa das Erstellen eines Objekts, dessen Neuordnung, das Hinzufügen weiterer Elemente, das Positionieren in bestimmten Formen usw. Diese Eingabeaufforderungen wurden von einem Large Language Model verarbeitet, das aus Code und Text, jedoch nicht aus Bildern gelernt hat. Die Ausgaben erfolgen als SVG-Codes, welche als statische und animierte Vektorgrafiken gezeigt werden.

In Form von Prompts versucht Elise Olenina ihren kreativen Gestaltungsprozess nachzuahmen. Wie strukturieren wir Dinge? Wie schaffen wir Ordnung und wie gehen wir mit Chaos um? Welche Kriterien unterscheiden menschliche Arbeit von maschineller? Und kann die Sprache unsere Intentionen während des Gestaltungsprozesses sichtbar machen?

LLM, Paper, Display

Computer, monitor, graphics tablet, Stable Diffusion (SDXL), Custom Model, ComfyUI, Python

The interactive installation Stuhl (chair) uses AI real-time generation to expand the design process of chairs based on the Thonet chairs. Visitors can draw or sketch freely on a graphics tablet. Whether spontaneous lines or simple sketches—the system stimulates the imagination and helps to design individual Thonet chairs. A ComfyUI workflow ensures that the generation process runs smoothly and quickly and that the AI system can process image requests efficiently. It is based on the basic SDXL model from Stability AI and uses a specially trained LoRA model and the LCM model for real-time image generation. Especially with drawings that are very close to the shapes of chairs, the AI system manages to design a chair that matches the style of the drawing by interpreting the lines.