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How to Build an EverMem-Style Persistent AI Agent OS with Hierarchical Memory, FAISS Vector Retrieval, SQLite Storage, and Automated Memory Consolidation

In this tutorial, we build an EverMem-style persistent agent OS. We combine short-term conversational context (STM) with long-term vector memory using FAISS so the agent can recall relevant past information before generating each response. Alongside semantic memory, we also store structured records ...

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LangWatch Open Sources the Missing Evaluation Layer for AI Agents to Enable End-to-End Tracing, Simulation, and Systematic Testing

As AI development shifts from simple chat interfaces to complex, multi-step autonomous agents, the industry has encountered a significant bottleneck: non-determinism. Unlike traditional software where code follows a predictable path, agents built on LLMs introduce a high degree of variance. ...

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Physical Intelligence Team Unveils MEM for Robots: A Multi-Scale Memory System Giving Gemma 3-4B VLAs 15-Minute Context for Complex Tasks

Current end-to-end robotic policies, specifically Vision-Language-Action (VLA) models, typically operate on a single observation or a very short history. This ‘lack of memory’ makes long-horizon tasks, such as cleaning a kitchen or following a complex recipe, computationally intractable or prone to ...

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