Vectors Embeddings | Spring AI

Build a strong foundation in AI Engineering by understanding one of the most important concepts behind modern intelligent systems: embeddings. In this video, we explain how text is transformed into numerical representations that help AI systems identify meaning, similarity, and relationships between words and sentences. Along with the core theory, we also walk through the practical implementation using Spring AI and Mistral AI. What You’ll Learn: ▶️Understanding the Core Idea Why meaning matters more than exact word matching in AI applications How text is converted into vectors in multi-dimensional space How similarity between vectors is measured using cosine similarity Why embeddings are essential for semantic search, recommendation systems, and RAG-based applications ▶️Practical Implementation Live walkthrough of generating embeddings using the Mistral AI API Testing embedding APIs using Insomnia Integrating embeddings into a Java Spring Boot project with Spring AI Adding and configuring Mistral and Anthropic dependencies Handling real-world issues such as bean conflicts and multi-model configuration Resources: Spring AI Source Code: https://github.com/teluskoOrg/SpringAI-YT/tree/main/Embeddings/SpringAIDemo Check out our courses: Industry-Ready Spring Boot, React & Gen AI -Live Course : https://go.telusko.com/industry-ready-springboot Coupon: TELUSKO10 (10% Discount) Master Java Spring Development : https://go.telusko.com/masterjava Coupon: TELUSKO10 (10% Discount) For More Queries WhatsApp or Call on : +919008963671 website : https://courses.telusko.com/ Instagram : https://www.instagram.com/navinreddyofficial/ Linkedin : https://in.linkedin.com/in/navinreddy20 WhatsApp : https://go.telusko.com/whatsapp TELUSKO Android App : https://go.telusko.com/TELUSKOAPP TELUSKO IOS App : https://apple.co/3SsgmU2 Discord : https://discord.gg/D8hWe9BqfF