Conversational AI System with Memory

A Conversational AI System with Memory is a conversational AI system that can engage in extended conversations by managing contextual information over time.

• Context:
  • It can manage different memory tiers.
  • It can use interrupts to manage control flow between the system and the user, enhancing user interaction.
  • It can support Memory-Requiring Conversational AI Tasks.
  • …
• Example(s):
  • one that uses MemGPT, a system that manages memory tiers in LLMs for extended conversations and document analysis.
  • ...
• Counter-Example(s):
  • A Stateless Chatbot that lacks extended memory capabilities and cannot manage long-term context.
  • A Rule-Based AI System without the capability to adapt or remember past interactions.
• See: Large Language Model, Virtual Context Management, Hierarchical Memory System, Operating System.

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References

2023

• GBard
  • Conversational AI systems with memory are a type of artificial intelligence (AI) that can remember and use information from past conversations to improve their current interactions with users. This allows them to provide more personalized and relevant responses, as well as to build relationships with users over time.

2023

• (Packer et al., 2023) ⇒ Charles Packer, Vivian Fang, Shishir G. Patil, Kevin Lin, Sarah Wooders, and Joseph E. Gonzalez. (2023). “MemGPT: Towards LLMs As Operating Systems.” In: arXiv preprint arXiv:2310.08560. DOI:10.48550/arXiv.2310.08560
  • QUOTE: Large language models (LLMs) have revolutionized AI, but are constrained by limited context windows, hindering their utility in tasks like extended conversations and document analysis. To enable using context beyond limited context windows, we propose virtual context management, a technique drawing inspiration from hierarchical memory systems in traditional operating systems that provide the appearance of large memory resources through data movement between fast and slow memory. Using this technique, we introduce MemGPT (Memory-GPT), a system that intelligently manages different memory tiers in order to effectively provide extended context within the LLM's limited context window, and utilizes interrupts to manage control flow between itself and the user.

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