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Keith Bourne

The Memriq AI Inference Brief – Engineering Edition

The Memriq AI Inference Brief – Engineering Edition is a weekly deep dive into the technical guts of modern AI systems: retrieval-augmented generation (RAG), vector databases, knowledge graphs, agents, memory systems, and more. A rotating panel of AI engineers and data scientists breaks down architectures, frameworks, and patterns from real-world projects so you can ship more intelligent systems, faster.

Auteur

Keith Bourne

Catégorie

Technology

Dernier épisode

8 juin 2026

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Épisodes

Vectors & Vector Stores in RAG (Chapter 7) 11.12.2025

Unlock the core infrastructure powering retrieval-augmented generation (RAG) systems in this technical deep dive. We explore how vector embeddings and vector stores work together to enable fast, scalable, and semantically rich retrieval for LLMs, drawing insights directly from Chapter 7 of Keith Bourne ’s book . In this episode: - Understand the role of high-dimensional vectors and vector stores i...

Similarity Searching with Vectors (Chapter 8) 11.12.2025

Unlock the power of similarity search with vectors in this episode of Memriq Inference Digest – Engineering Edition. We explore how dense and sparse vector techniques combine to enable scalable, accurate semantic retrieval for AI systems, inspired by Chapter 8 of Keith Bourne ’s book . Join us and special guest Keith Bourne as we unpack the engineering trade-offs, indexing algorithms, hybrid searc...

Evaluating RAG: Quantitative Metrics and Visual Insights (Chapter 9) 11.12.2025

In this episode of Memriq Inference Digest — Engineering Edition, we dive deep into rigorous evaluation strategies for Retrieval-Augmented Generation (RAG) systems. Drawing from Chapter 9 of Keith Bourne ’s book , we explore how quantitative metrics and visualizations help AI engineers optimize retrieval and generation performance while managing cost and complexity. In this episode: - Why continuo...

Key RAG Components in LangChain (Chapter 10) 11.12.2025

Unlock the inner workings of Retrieval-Augmented Generation (RAG) pipelines using LangChain in this episode of Memriq Inference Digest - Engineering Edition. We bring insights directly from Keith Bourne , author of ' Unlocking Data with Generative AI and RAG ,' as we explore modular vector stores, retrievers, and LLM integrations critical for building scalable, flexible AI systems. In this episode...

Welcome to The Memriq AI Inference Brief 10.12.2025

Your weekly briefing on RAG, agents, and AI memory systems. The Memriq Inference Brief is a panel-style podcast breaking down the technologies reshaping how we build intelligent systems — from retrieval-augmented generation to agentic architectures to the emerging field of AI memory. Two editions. Same topic. Different depths. 🎯 Leadership Edition — For executives, product leaders, and decision-m...

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