LLM Memory Architecture

A LLM Memory Architecture is a neural network architecture that designs LLM memory architecture storage structures and LLM memory architecture retrieval mechanisms for LLM memory architecture conversational persistence.

• AKA: Large Language Model Memory Architecture, Conversational Memory Architecture, LLM Storage Architecture, Neural Memory Architecture.
• Context:
  • It can typically structure LLM Memory Architecture Components including LLM memory architecture embedding layers, LLM memory architecture storage systems, and LLM memory architecture retrieval modules.
  • It can typically implement LLM Memory Architecture Patterns such as LLM memory architecture dual-stream design, LLM memory architecture hierarchical storage, and LLM memory architecture attention mechanisms.
  • It can often support LLM Memory Architecture Functions including LLM memory architecture context preservation, LLM memory architecture information retrieval, and LLM memory architecture response generation.
  • It can often evolve toward LLM Memory Architecture Innovations such as LLM memory architecture non-linguistic encodings and LLM memory architecture multimodal representations.
  • It can range from being an Embedding-Based LLM Memory Architecture to being a Non-Linguistic LLM Memory Architecture, depending on its LLM memory architecture abstraction level.
  • It can range from being a Centralized LLM Memory Architecture to being a Distributed LLM Memory Architecture, depending on its LLM memory architecture topology.
  • It can range from being a Static LLM Memory Architecture to being a Dynamic LLM Memory Architecture, depending on its LLM memory architecture adaptability.
  • It can range from being a Shallow LLM Memory Architecture to being a Deep LLM Memory Architecture, depending on its LLM memory architecture layer depth.
  • ...
• Example(s):
  • ChatGPT Dual-Stream Architecture, combining LLM memory architecture explicit storage with LLM memory architecture implicit embeddings.
  • Claude Raw-Index Architecture, using LLM memory architecture vector search over LLM memory architecture unprocessed history.
  • Transformer Memory Architectures, such as:
    • Attention-Based Memory Architecture for LLM memory architecture context windows.
    • External Memory Architecture for LLM memory architecture augmented storage.
  • Hybrid Memory Architectures combining LLM memory architecture multiple approaches.
  • ...
• Counter-Example(s):
  • Stateless Architecture, which lacks LLM memory architecture persistence mechanism.
  • Fixed-Context Architecture, which lacks LLM memory architecture dynamic retrieval.
  • Rule-Based Architecture, which lacks LLM memory architecture learned representations.
• See: Sequential Data Neural Network Architecture, Memory Augmented Neural Network (MANN), LLM Conversational Memory System, ChatGPT-Style LLM Memory System, Claude-Style LLM Memory System, Retrieval-Augmented Generation (RAG) Framework, Context Rot Phenomenon, LLM-based System Component.

---