Memory Management Techniques in Large Language Models

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This presentation explores the impact of large language models (LLMs) on operating systems, focusing on their lack of state memory. It analyzes current memory techniques like MemGPT, RAG, and Compressor-Retriever, categorizes methods into a taxonomy, and evaluates them using metrics such as accuracy and scalability. Findings highlight memory classifications, technique comparisons, and gaps in research. Future plans include broad comparisons and hierarchical techniques, distributed among team...