Generative AI and Design, explores the creative application of generative systems in studio art practice. This course combines lab sessions, discussions, and lectures, covering bio-inspired design such as genetic algorithms, L-systems, and artificial life, as well as complexity theory systems like fractals, cellular automata, and chaos theory.
Students will develop a creative pipeline for art generation using these methods. With the advancements brought by tools like Stable Diffusion since 2022, the course emphasizes computationally generated artworks that inspire new artistic experiences. Generative methods are seen as tools that enhance the creative process.
You will gain practical knowledge of image-generative tools, learning to perform clean installations and use tools independently in local machine. The course also addresses ownership issues and responsibilities in using generative technologies.
Instructor: You-Jin Kim (Dr. Kim)
Email: yujnkm@tamu.edu
Lecture Time: Tuesday & Thursday 5:30 – 7:30 p.m.
Location: Langford Center - Building C – 414
Office Hours: TBD (by appointment only) - Utilize the one hour before and after the class lecture at the Dynamic Reality Lab (DRL 421) as the instructor will be present in those time.
The course will be taught in person and occasionally via Zoom, adopting a studio-style format centered around assignments, class exercises, laboratory work, and seminars. All these activities are integral to the class, and active participation from each student is expected. Please ensure that students can allocate the time required according to the university's guidelines. Carefully review the class schedule available on this website. One day of the week will focus more on lectures, while the other will concentrate on studio and lab work.
*On the occasional, Zoom session/ meeting, please make sure to turn on the video to show the participation.
Course Goals
Upon the completion of the course, in addition to mastering the concepts and methodology behind generative art and design, students should be able to:
Navigate the generative tools available today with confidence.
Understand how these images and patterns are generated computationally.
Connect their creative work to these tools for inspiration.
Analyze and identify the generative tool pipeline used in various artworks.
Understand and refine their creative processes with the aid of generative assistive tools.
Publish their explorations using IEEE, ACM, and arXiv formats.
Install and configure Stable Diffusion on a local machine, customizing modules and plugins to suit specific needs (to your artwork).
Develop and maintain a GitHub repository to showcase their work, open-source their processes, and manage version control.
Textbook and/or Resource Materials
All the materials will be provided.
Some useful links:
Visual Studio Code - https://code.visualstudio.com/
Python - https://www.python.org/downloads/
Overleaf - https://www.overleaf.com/
GitHub Desktop - https://github.com/apps/desktop
Google Colab (Art Machine) - https://colab.research.google.com/
Stable Diffusion - https://github.com/CompVis/stable-diffusion
ComfyUI - https://github.com/comfyanonymous/ComfyUI
Course Focuses
Graduate Seminar Focus: This class is structured for in-depth discussions typical of a graduate seminar, emphasizing high-level concepts and theories while also incorporating elements of lab and studio courses.
Theoretical Emphasis: This class goes beyond coding. It combines a rigorous scientific approach with generative methods in art-making and foundational coding skills, including algorithmic understanding. You'll learn how these elements work together.
Scientific rigor: The course emphasizes creating comprehensive reports, referencing sources, and crediting projects that inspired or preceded your work. These are considered specialized skills to effectively convey your ideas, rather than soft skills.
Broad Application Scope: The course is not limited to specific applications like CAD. Instead, it explores broad concepts that are applicable across various tools and platforms.
Generative Inspiration: We explore how generative inspiration operates and how these concepts can lead to innovative products, recognizing that future advancements may transform traditional practices like 3D character creation.
Creative Generative Methods: The course examines how to create designs and art using generative methods, encouraging students to integrate these techniques into their creative processes.
Is this AI class? While the course is not specifically about AI, it acknowledges the significant role AI plays in the rapidly evolving generative creative pipeline.
Project-based learning requires class participation from every student. To ensure that participation is widespread, and that all students have the opportunity to participate, students may be randomly selected to contribute to class discussion. This format will provide you with the opportunity to defend your ideas and to learn from contrasting points of view, skills that will be invaluable in your forthcoming careers. When evaluating your contribution to the discussion, factors such as the following are considered:
Timeliness: Is the comment timely, given the discussion that is taking place?
Accuracy: Does the comment accurately reflect case facts that have not already been stated?
Advancement: Does the comment advance the discussion?
Creativity: Does the comment yield a new perspective and add to understanding of the situation?
Constructiveness: Does the comment help maintain a constructive atmosphere?
A portion of the class will be devoted to small group discussion of readings and concepts from the lecture, and group critique of peer work and presentations. Students are responsible for actively and thoughtfully contributing to these discussions and critiques. Students are also responsible for providing feedback on reading reflections and course assignments by other students.
Quality of participation is more important than quantity. It is possible for someone to talk a lot and receive a low grade for class participation. It is also important that you actively participate in your team discussions. To discourage "gunning," class participation will be graded on a diminishing marginal return basis. Attendance is expected. The student who misses 3 classes will receive a considerably lower grade for this class. If you miss class, the quality of the class discussion suffers, and this can significantly detract from the class experience for other students. Similarly, if they miss class, your experience suffers. If you must miss class, be sure that you clear the absence with me before the class.
© You-Jin Kim
College Station, Texas