A model for language- and / or image- processing based on computational training from large datasets (of text, of imagery, of mixed-modality data) and applied to various practical uses including natural language processing tasks, AI conversation, image creation, video creation and others Re-visioning: To re-think, to reconceptualize, to re-visualize.
Published in Chapter:
Engaging Future-Minded Visualizations and Artful Aesthetics: “Seeing Different” With Human-Machine Collaborations With Artmaking Generative AIs
Shalin Hai-Jew (Kansas State University, USA)
Copyright: © 2024
|Pages: 27
DOI: 10.4018/979-8-3693-0074-9.ch014
Abstract
Artmaking generative AIs have been used to create visual works (still images, motion videos, and animated sequences, including simulations) that are photorealistic, high-fidelity, hyper-realistic, and emulative of the world; artful works are translated in style transfers derivative of known artist, artworks, art styles, schools of art practices, and defined visual styles. This work argues that artmaking generative AIs should not be about reproductions of the familiar but should be used for future-minded visualizations and future-minded aesthetics, through true collaborations between human and machine imaginations. Through generative AI, people should be “seeing different” to enable nouveau “thinking” and “doing” and “being” different… into the near- and far- futures. This early and exploratory work is based on research, year-long experimentation with multiple public artmaking generative AI tools, and abductive logic.