The research aims to re-evaluate the concept of orthogonality in latent spaces within AI frameworks.
Introduced a new interpretation of trigonometric orthogonality.
Analyzed its application in AI latent spaces.
Explored cyclical patterns present in AI models.
Demonstrated a new understanding of latent space structure.
Identified cyclical behavior in AI patterns.
Provided theoretical insights for future AI model development.
Abstract
A fundamental re-evaluation of orthogonality in latent spaces and its cyclical nature in AI. Affiliation: Mutsumi Communication Institute (623) URL: https://623communication.weebly.com