Session: Unleashing the Power of Vector Databases for AI-Driven Applications
Vector databases are emerging as the cornerstone of next-generation data management, enabling seamless storage, indexing, and retrieval of dense vector embeddings derived from AI models. In an era dominated by artificial intelligence and machine learning, the ability to handle high-dimensional data efficiently is critical and a game-changer.
This talk will demystify the fundamentals of vector databases, their architecture, and how they integrate into the modern data stack to accelerate AI-driven applications.
Through real-world use cases, we will explore how vector databases empower applications such as recommendation systems, semantic search, anomaly detection, and personalization.
Designed for data engineers, AI practitioners, and architects, who are building a cutting-edge chatbot, an intelligent search engine, or an adaptive learning platform, the session will help them discover how vector databases can unlock new possibilities in their AI journey.
