Why Your AI Agent Needs Memory: Unveiling the Secrets Behind Intelligent Behavior
Explore how LLM agents use memory modules to simulate human-like short-term and long-term memory, enhancing real-world application performance.
The agent serves as a bridge between large models and real-world applications, making it incredibly important.
From a functional perspective, an Agent consists of several components, including planning, memory, and tool usage.
Agent = LLM + Planning + Feedback + Tool Use
Today, let's focus on one component: Memory.
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