Advancing Artificial General Intelligence: A Comparative Analysis of Non-Binary and Temporally Complex Paradigms Abstract The pursuit of Artificial General Intelligence (AGI) necessitates a paradigm shift beyond traditional binary computation. This article presents a comparative analysis of three pioneering works that explore novel architectural and algorithmic approaches for AGI: Mitchell D. McPhetridge's "Fractal Flux Temporal (F²T)" and Klenio Araújo Padilha's "Beyond Binary Constraints: A Non-Binary Framework for Artificial General Intelligence Inspired by Complex Wave Dynamics" and "Fractal Processing with Crystals and Light: A Novel Computational Paradigm Based on Complex Wave Dynamics." We highlight the shared commitment to transcending binary limitations, with a particular emphasis on the crucial role of non-linearity in generating complexity, emergent behaviors, and fractal patterns. While F²T emphasizes retrocausality and temporal dynamics for cognitive modeling, Padilha's contributions center on a complex wave function as a mathematical and physical foundation for non-binary computation. This comparative review elucidates their synergistic contributions to the broader landscape of post-binary AGI research, including neuromorphic, quantum, and optical computing. 1. Introduction The ambition to achieve Artificial General Intelligence (AGI)—systems capable of performing any intellectual task a human can—demands a fundamental re-evaluation of prevailing computational models. Current Artificial Intelligence (AI) often operates within the constraints of binary logic and the Von Neumann architecture, which struggle to effectively capture the continuous, contextual, and emergent properties characteristic of human cognition. This challenge has propelled research into innovative computational paradigms, seeking inspiration from the inherent complexity of natural systems. This article provides a comparative analysis of three significant contributions to this evolving field. Mitchell D. McPhetridge's "Fractal Flux Temporal (F²T)" proposes a framework centered on temporal dynamics and fractal principles for AGI. Concurrently, Klenio Araújo Padilha's "Beyond Binary Constraints: A Non-Binary Framework for Artificial General Intelligence Inspired by Complex Wave Dynamics" (hereinafter "AGI Framework") and "Fractal Processing with Crystals and Light: A Novel Computational Paradigm Based on Complex Wave Dynamics" (hereinafter "Fractal Processing") present a unified approach rooted in complex wave mechanics. While developed independently, these works exhibit notable convergences in their aims to transcend binary limitations and leverage non-linear dynamics, alongside crucial distinctions in their proposed mechanisms and focuses.