Complexity science meets ancient Japanese art
Generative AI drawing complexity science
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I was wondering if a generative AI can manage to represent a complex concept in some visual and appealing way. Maybe, using the beautiful style of ancient Japanese art?
Many of you probably know the work by Kanō Einō (狩野 永納, 1631–1697), a Japanese painter of the Kyō-ganō [ja] sub-school of the Kanō school of painting
or the famous Great Wave off Kanagawa, by Katsushika Hokusai:
The question: what if we use generative AI to (imperfectly) mimick the style of those beautiful Japanese paintings to draw specific concepts in complexity science?
In the following, there is a short journey through the results of my exploration at the edge of complexity concepts and generative AI (DALL-E 3).
All the images below are original work and released under the CC BY 4.0 license with attribution (click here for a copy of the license).
Stigmergy
Collective behavior: flocking birds
Pattern formation
Autopoiesis
Synchronization
Self-organization
Hierarchical and modular organization
Information
Decentralization
Interconnections and interdependency
Self-organized criticality
Chaos
Homeostasis
Turbulence
Adaptation and feedback loops
Collective intelligence and liquid brains
Self-similarity
Assembly and self-replication
Functional self-organization
Did you like them? Feel free to leave a comment and share the representations.