SYNAPSE: A Cognitive Continuity Architecture

Abstract

Large Language Models (LLMs) are transforming the field of Artificial Intelligence (AI) with their impressive abilities in understanding, reasoning, and executing tasks in natural language. However, despite these progressions, most of the currently available AI systems are still stateless, which means that user-generated content such as context, preferences and project history is not retained after the end of a session. This results in users having to enter the same data into various processes, resulting in a higher degree of cognitive effort, interrupted conversations and reduced productivity. This paper proposes a novel Cognitive Continuity Architecture called Synapse, which offers a way for intelligent systems to gain contextual awareness and long-term memory. The proposed architecture proposes a multi-layered memory structure, with each tier representing a distinct type of user knowledge and interaction, namely: Short-Term Memory, Long-Term Memory, Task Memory, Content Memory and Procedural Memory. These memory layers are orchestrated in an intelligent way with a combination of semantic retrieval, vector-based knowledge storage, and structured data management to facilitate the efficient storage, retrieval, and use of relevant information across user sessions. Moreover, the architecture features a reflection and self-correction loop that continuously reviews previous interactions, learns from patterns detected in these interactions and makes adjustments to the system's response over time, allowing for increasingly individualized and context-aware support. Synapse allows for a seamless flow of information and context, which helps reduce information loss and improves long-term human-AI collaboration. The experimental results show that the proposed architecture can provide a better experience in terms of context retention, semantic retrieval, and user productivity than the traditional stateless AI assistants. The suggested design is also scalable, allowing the creation of long-lasting AI systems that can help manage complex projects, workflows, and intelligent decision-making.