2025/06/18 by Erden, Zeki Doruk
#Adaptation and Self-Organizing Systems (nlin.AO) #FOS: Computer and information sciences #FOS: Physical sciences #Neural and Evolutionary Computing (cs.NE) #Other Computer Science (cs.OH)
paper · doi:10.48550/arxiv.2507.02876
This article critically examines the foundational principles of contemporary AI methods, exploring the limitations that hinder its potential. We draw parallels between the modern AI landscape and the 20th-century Modern Synthesis in evolutionary biology, and highlight how advancements in evolutionary theory that augmented the Modern Synthesis, particularly those of Evolutionary Developmental Biology, offer insights that can inform a new design paradigm for AI. By synthesizing findings across AI and evolutionary theory, we propose a pathway to overcome existing limitations, enabling AI to achieve its aspirational goals. We also examine how this perspective transforms the idea of an AI-driven technological singularity from speculative futurism into a grounded prospect.