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What is a Vector Database and how does it actually work? If you can explain this clearly, you are already ahead in Gen AI and LLM interviews. Understanding Vector Databases, Embeddings, and Similarity Search is one of the most important concepts in modern Generative AI systems like ChatGPT, RAG pipelines, and AI search engines. You can access the full video here https://youtu.be/gmvWvqSPS8M In this video, we explain how raw data is converted into vectors (embeddings), how vector databases store high-dimensional data, and how similarity search works using distance metrics. You will also understand how tools like FAISS, Pinecone, Weaviate, and ChromaDB are used in real-world AI applications. If you are an engineering student, software developer, or someone preparing for AI, Data Science, or Machine Learning interviews, this video will help you clearly understand how vector databases power semantic search, recommendation systems, and retrieval-augmented generation (RAG). We use a whiteboard + doodle storytelling approach to make these concepts intuitive, visual, and interview-ready. --- š In this video, you will learn: ⢠What is a Vector Database ⢠What are Embeddings in AI ⢠How Similarity Search works ⢠How Vector Databases store and retrieve data ⢠How RAG (Retrieval Augmented Generation) works ⢠Real-world use cases of Vector DB in AI systems --- š” Perfect for: Gen AI learners | LLM interview prep | Software engineers | Data scientists | AI beginners --- This is the part of a playlist - LLM & Gen AI Interview Questions (Complete Guide) š Watch next in this series: š Fine-Tuning vs RAG (critical interview comparison) š AI Agents and Agentic AI systems š Model Context Protocol (MCP) and modern AI architectures --- ## š„ Hashtags (SEO Optimized) #vectordatabase #genai #llm #rag #artificialintelligence #machinelearning #datascience #embeddings #semanticsearch #openai #chatgpt #aiinterview #softwareengineering #techbysketch #learnai #aiforbeginners #weaviate #pinecone #faiss #chromadb ---