Self-referential memory tensor

We present a technical architecture for persistent identity in AI sys- tems, based on the Self-Referential Memory Tensor (SRMT). The archi- tecture integrates transformer encoders, differentiable memory, persistent embeddings, and long-context attention to enable temporal continuity, self-recognition, narrative integration, and autonomous coherence. We show that the SRMT is not speculative but immediately feasible with existing technologies. The architecture is a bridge to AI qualia.