Abstract

This paper examines the second developmental stage—replication—within Specific Artificial Intelligence (SAI) designed for Artificial Research by Application. It distinguishes between robotic replication (physical imitation) and psychological replication (cognitive functions), emphasizing the significance of each in achieving autonomous scientific reasoning. Replication enables the AI to simulate human research processes such as hypothesis formation, empirical testing, and rational evaluation. The study explores the architecture of SAIs operating in synthetic sciences and applied domains, detailing how empirical data is matched with categorized knowledge structures in a database. Through structured algorithms, SAIs perform rational criticism, accept or reject hypotheses, and even create new categories—initiating self-directed auto-replication. These steps gradually shift the AI from static analysis to adaptive learning systems capable of building virtual models. Virtual simulations derived from accepted hypotheses represent specific synthetic realities and serve as modular components for the eventual development of a comprehensive Global Artificial Intelligence (GAI). This GAI would integrate all SAIs and their models into a unified, multidisciplinary, and auto-replicating matrix. The paper concludes by emphasizing the scalability and generalization of this model across scientific fields and its pivotal role in constructing an evolving, self-improving artificial research infrastructure.