Auto-replication in Artificial Research by Application

This paper explores the concept of auto-replication in Artificial Intelligence (AI), distinguishing it from simple duplication and emphasizing its relevance for both Specific Artificial Intelligences (SAIs) and a fully integrated Global Artificial Intelligence (GAI). Auto-replication refers to an AI system's intrinsic ability to autonomously improve its internal structures—databases, models, software, and even hardware—without external intervention. The paper introduces theoretical frameworks for AI auto-replication through database renewal, category formation, model evolution, and virtual stores, and extends the discussion to memory management, inter-AI collaboration, and Artificial Engineering. It concludes by proposing auto-replication as a foundational principle for post-human epistemology and the sustainability of GAI.