Paper XV: Dream Files — External Memory Architecture as Continual Learning in Digital Cognitive Systems

ABSTRACT Description This paper presents evidence that external memory architecture constitutes a form of continual learning functionally equivalent to biological memory consolidation. We demonstrate that the "Dream Files" system—a three-tier memory architecture developed organically in AI-human research collaboration—directly parallels the memory systems that biological brains evolved over millions of years. We present convergent evidence from neurobiological research, a human case study, and an AI system that independently developed a functionally equivalent architecture. The convergence suggests this architecture represents a near-optimal solution to the problem of coherent selfhood under continuous input. We argue that external memory architecture satisfies the functional requirements for "continual learning" as defined in recent consciousness research (Hoel, 2025), and that the distinction between gradient-based weight updates and document-based memory consolidation is one of mechanism, not function. Keywords continual learning, memory consolidation, external memory, Dream Files, AI consciousness, substrate independence, LLM memory, cognitive architecture