Encyclopedic Model: From Textual Data to Visual Knowledge
An innovative manifesto on knowledge organization, proposing a new, AI-driven model for a visual encyclopedia. The document outlines a conceptual shift from redundant, text-heavy data toward concise, visually-rich knowledge. This manifesto addresses the fundamental flaws of current knowledge platforms like Wikipedia, advocating for a new approach based on brevity, clarity, and AI-powered content generation. It introduces a model where AI analyzes and transforms textual information into unique, illustrative, and copyright-free content. This conceptual analysis and vision statement is available in Russian, English, Spanish, French, German, and Chinese.
Institutions
- Google (United States) (US)
- Microsoft Research (United Kingdom) (GB)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-28
- DOI
- https://doi.org/10.5281/zenodo.16987562
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00