Week 2 · Day 11/30

Memory Systems for AI

Short-term, long-term, episodic memory, vector stores

📅 2026-03-14 ⏱️ 6-7 hodín 📊 Agent Systems
Celkový progres 37%

🎯 Cieľ dňa

Pochopiť taxonómiu AI memory systémov a implementovať persistent memory s vector store a scoping.

core practice

📚 Study Resources

🏢

IBM — What Is AI Agent Memory?

Komprehenzívny overview: short-term, long-term, episodic, semantic, procedural.

article
🧠

ML Mastery — 3 Types of Long-term Memory AI Agents Need

Deep dive: episodic, semantic, procedural memory s implementation stratégiami.

article
💻

DataCamp — Mem0 Tutorial: Persistent Memory Layer

Hands-on: Mem0 open-source memory layer. User/session/agent memory scopes.

tutorial
🔧

Mem0 Blog — Agentic RAG Chatbot With Memory

Production-grade: Chroma pre dokumenty + Mem0 pre user memory, oba ako agent tools.

tutorial

💡 Key Concepts

Memory Taxonomy — Short-term (conversation), Long-term (persistent), Episodic (events), Semantic (facts), Procedural (how-to)
Vector Stores — ChromaDB, Pinecone, Weaviate, pgvector, FAISS — semantic similarity search
Memory Scoping — User memory (per person), Session (per conversation), Agent (per instance) — Mem0 implementácia
Hybrid Memory — Vector search + knowledge graphs; Mem0 +26% vs OpenAI built-in memory na LOCOMO benchmarku

🔧 Praktické cvičenie

Buildni personal assistant s persistent memory.

  1. Conversation context management (short-term)
  2. User preferences a fakty do vector DB (long-term semantic)
  3. Event logging s timestamps (episodic)
  4. Sémantické hľadanie v pamäti ('Čo som hovoril o X minulý týždeň?')
  5. Storage aj retrieval ako agent tools