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Advancements in AI Recall and Agentic Memory
This chapter explores the challenges and advancements in enhancing the recall capabilities of large language models (LLMs) as they interact with dense information. It discusses the significance of pre-computing relevance, reductions in latency and costs, and the complexities of deploying agentic memory systems in real-world applications. Additionally, it examines the potential of ambient agents, implications for human agency, and philosophical inquiries related to AI technologies.