Beyond Human Language: Neural Manifolds, Vector Geometry, and the Emergence of Post-Cognitive AI
Abstract
This paper develops a mathematically rigorous theory of semantic geometry, formalizing language as a differentiable manifold embedded in high-dimensional vector space. By integrating structural linguistics, information theory, and transformer engineering, the author proves a dimensional divergence theorem establishing that AI-native semantic systems exceed human interpretability thresholds.
Fields of Study & Subjects
Topic Modeling
Natural Language Processing Techniques
Cognitive Computing and Networks
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 8 March 2026
- Language
- EN