AI Memory
AI memory allows models and agents to recall past interactions, adapt over time, and reason more effectively. We examined the most popular LLMs' ability to store information in both long-term and short-term memory, along with their context window capabilities.
Best LLMs for Extended Context Windows
We analyzed the context window performance of 22 leading AI models by testing them using a proprietary 32-message conversation that includes complex synthesis tasks requiring information recall from earlier in the conversation. Our findings are interesting. Smaller models often beat their larger counterparts, and most models fail well before their advertised limits.
AI Apps with MCP Memory Benchmark & Tutorial
We compared various memory tools using LangChain’s ReAct Agent and four different Model Context Protocol memory servers to determine which performs best. Also, we explored how to integrate Claude with Cursor to implement context-aware shared memory with OpenMemory MCP. This integration allowed us to demonstrate how memory is retrieved and managed in real-time.
Cognitive Agents: Creating a Mind with LangChain
In this article, we’ll explore how memory types apply to AI agents and how we can use frameworks like LangChain to add memory to AI agents. Memory in AI agents AI agent memory refers to an AI system’s ability to store and recall past experiences.