『RAG-Based Agentic Memory in AI (Chapter 17)』のカバーアート

RAG-Based Agentic Memory in AI (Chapter 17)

RAG-Based Agentic Memory in AI (Chapter 17)

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Unlock how RAG-based agentic memory is transforming AI from forgetful chatbots into intelligent assistants that remember and adapt. In this episode, we break down the core concepts from Chapter 17 of Keith Bourne’s “Unlocking Data with Generative AI and RAG,” exploring why memory-enabled AI is a game changer for customer experience and operational efficiency.

In this episode, you’ll learn:

- What agentic memory means in AI and why it matters for leadership strategy

- The difference between episodic and semantic memory and how they combine

- Key tools like CoALA, LangChain, and ChromaDB that enable memory-enabled AI

- Real-world applications driving business value across industries

- The trade-offs and governance challenges leaders must consider

- Actionable tips for adopting RAG-based memory systems today


Key tools and technologies: CoALA, LangChain, ChromaDB, GPT-4, vector embeddings


Timestamps:

00:00 – Introduction and overview

02:30 – The AI memory revolution: episodic and semantic memory explained

07:15 – Why now: Technology advances driving adoption

10:00 – Comparing memory approaches: stateless vs episodic vs combined

13:30 – Under the hood: architecture and workflow orchestration

16:00 – Real-world impact and business benefits

18:00 – Risks, challenges, and governance

19:30 – Practical leadership takeaways and closing


Resources:

- "Unlocking Data with Generative AI and RAG" by Keith Bourne - Search for 'Keith Bourne' on Amazon and grab the 2nd edition

- Memriq.ai – Tools and resources for AI practitioners and leaders


Thanks for listening to Memriq Inference Digest - Leadership Edition.

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