Separate and Reassemble: Generative AI through the lens of art and media histories
AI image generation represents a logical evolution from early digital media algorithms, starting with basic paint programs in the 1970s and advancing to sophisticated 3D graphics and media creation software by the 1990s. Early algorithms struggled to simulate materials and effects, but advances in the 1970s and 1980s led to realistic simulations of natural phenomena and artistic techniques. Generative AI continues this trend, using neural networks to combine and interpolate visual patterns from extensive datasets. This method of digital media creation underscores the modular and discrete nature of computer-generated imagery, distinguishing it from traditional optical media.
Authors
- Lev Manovich (ORCID: https://orcid.org/0000-0003-0667-7584)
Institutions
- City University of New York (US)
Publication Details
- Journal
- Matrizes
- Published
- 2024-08-30
- DOI
- https://doi.org/10.11606/issn.1982-8160.v18i2p7-18
- Citations
- 6
- Primary Topic
- Aesthetic Perception and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.06