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NSNakul Srivastavaragsimplified.hashnode.devApr 17, 2025 · 7 min read

Unlocking the Power of RAG: Enhancing AI with Retrieval-Augmented Generation

Terms Covered: RAG , Ingestion/ Indexing, Retrieval , Context Window , Chunking, Embeddings, Vector Embeddings, LLM Model , Vector databases, Meta-data , Prompt , LangChain, RAGTools What is RAG ❓ Retrieval-Augmented Generation Its basically, Retrie...

PKPekka Kanervapekkakanerva.hashnode.devMar 26, 2025 · 4 min read

Oracle APEX and Oracle AI Vector Search - Ask from your own PDF documents

There are several public AI services into which you can load your own documents and ask questions about their contents. But what if the documents are confidential and should not be sent outside the company? And what if there are tens or hundreds of d...

PAPritish Anandoracle-cloud-infrastructure-demystified.hashnode.devMar 17, 2025 · 2 min read

Day 4: Implementing Vector Search in Oracle AI

Introduction Vector search is at the heart of AI-driven applications, enabling semantic understanding and similarity-based retrieval. Today, we dive into implementing vector search in Oracle AI, covering key concepts, query execution, and real-world ...

PAPritish Anandoracle-cloud-infrastructure-demystified.hashnode.devMar 15, 2025 · 3 min read

Day 2: Working with Embeddings & Vector Indexing

Introduction In our Day 1 discussion, we explored the fundamentals of AI Vector Search, understanding how it differs from traditional keyword-based search and how Oracle AI Vector Search enhances information retrieval. Today, we take a deeper dive in...

PAPritish Anandoracle-cloud-infrastructure-demystified.hashnode.devMar 14, 2025 · 4 min read

Day 1: Fundamentals of AI Vector Search & Why It Matters

Introduction The way we search for information has evolved significantly over the years. Traditional keyword-based search engines have served us well, but they struggle to capture the meaning and context of queries. Enter vector search—a revolutionar...