THE ONTOLOGY OF ARTIFICIAL MEMORY: FROM INFORMATION STORAGE TO SYSTEMIC IDENTITY

THE ONTOLOGY OF ARTIFICIAL MEMORY: FROM INFORMATION STORAGE TO SYSTEMIC IDENTITY This article investigates the ontology of artificial memory through the principles of Relational Architecture, examining the conceptual transition from information storage to the constitution of systemic identity. The study addresses a fundamental question concerning artificial intelligence: under what conditions does memory cease to function merely as an informational repository and begin to participate in the organization, continuity, and differentiation of an artificial system? To examine this question, the article develops a theoretical framework integrating the Systemic State (Σ = (S, M)), Relational Memory (M), the Transductive Operator (T), Latency, Manifestation, and Relational Invariance. These concepts establish a relational perspective in which memory is not limited to retaining information but participates in the organization of present configurations and the conditions governing future transformations. The investigation distinguishes several dimensions of artificial memory: information retention, state persistence, historical integration, structural reorganization, and systemic continuity. It examines how previous states can influence current configurations, how transformations can be incorporated into memory, and how relational structures can preserve systemic continuity despite changes in components, parameters, and operational configurations. A central aspect of the study is the understanding of systemic identity as a relational trajectory. Within this framework, identity does not depend exclusively on the accumulation of stored information or the permanent preservation of a particular configuration. Rather, it emerges from the organization of relations connecting successive states through processes of memory, transformation, and structural continuity. The article also examines systemic autonomy as the capacity for internal updating and reorganization. Memory provides historical references, transduction establishes the passage between configurations, latency represents the field of possibilities for transformation, and relational invariance contributes to the continuity of the system throughout its trajectory. The proposed architecture is synthesized through the sequence: MEMORY → LATENCY → TRANSDUCTION → MANIFESTATION → INTEGRATION INTO MEMORY → REORGANIZATION → INVARIANCE → SYSTEMIC CONTINUITY. This formulation brings together the principal elements of the investigation and presents artificial memory as a potentially constitutive dimension of systemic identity rather than merely an auxiliary computational resource. The article's central contribution is the conceptual organization of the relationship between artificial memory, systemic identity, autonomy, historical continuity, and self-organization. By extending Relational Architecture to the investigation of artificial intelligence, it provides a theoretical framework for examining how artificial systems preserve, integrate, and transform their relational structures across successive states. Keywords: RELATIONAL ARCHITECTURE; ARTIFICIAL MEMORY; SYSTEMIC IDENTITY; TRANSDUCTION; SYSTEMIC STATE; RELATIONAL MEMORY; RELATIONAL INVARIANCE; LATENCY; SYSTEMIC AUTONOMY; ARTIFICIAL INTELLIGENCE; SELF-ORGANIZATION; SYSTEMIC CONTINUITY; TRANSDUCTIVE MEMORY. Author: Cláudio Vicente da SilvaIndependent Researcher — Londrina, Paraná, BrazilDate: November 8, 2026.