Table of Contents GenAI systems as layersVector RAGGraph RAGAI AgentsModel Context Protocol (MCP)What should you choose?Wrapping up!Resources In the last post, we discussed the basics of Retrieval Augmented Generation (RAG) and how it enhances the capabilities of Large Language Models …
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Intro to RAG: Foundations of Retrieval Augmented Generation, part 1
Table of Contents Why RAG?Large Language Models (LLMs)Vector embeddingsVectors applied to wordsVectors applied to dataSimilarity searchWrapping up!Resources Retrieval Augmented Generation (RAG) may sound complex, but it accurately represents the process of the system. RAG is a method that enhances the …
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GenAI blood, sweat, and tears: Loading data to Pinecone
Table of Contents Getting startedIssue #1: APIs, SDKs, and rapid changeIssue #2: ConfigIssue #3: JSON formatIssue #4: Loading data to Pinecone1. Metadata keysAlternative embeddings – Book descriptionsWrapping up!Resources As someone who is pretty familiar with relational and graph databases, I …
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Breaktime Tech Talks (Ep37): Vector Database Frustration + Microsoft LazyGraphRAG
Table of Contents Devnexus conference shout-outVector database explorationIssues getting up and runningOverall experienceMicrosoft LazyGraphRAGWrapping up! This is episode 37 of the Breaktime Tech Talks. You are listening to the Breaktime Tech Talks podcast, a bite-sized tech podcast for busy developers, …
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Foojay Podcast #56: Vectors in Java Code, Databases, and LLMs
In this Foojay podcast, we enter the world of mathematics by discussing Vectors and how they are crucial for AI and machine learning.
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Spring AI: How to Write GenAI Applications with Java
We’ll look at how to write GenAI applications with Java using the Spring AI framework and utilize RAG for improving answers.