Why semantic search is a game-changer for AI-driven applications (spoiler: it’s all about meaning, not just keywords!).
How to transform images into vectors (embeddings) and store them alongside your data—no clunky ETL pipelines required!
A live demo showcasing real-time image search on a 40,000+ product dataset (spoiler #2: it’s blazing fast and shockingly simple to build!).
Pro tips on choosing embedding models, optimizing indexes, and avoiding common pitfalls.
Why MongoDB’s unified data model crushes traditional databases for AI/ML workloads.
👥 For Developers & Data Engineers:
Whether you’re a JavaScript, AI enthusiast, or just tired of JOINs, this episode is your roadmap to building smarter, faster apps. Plus, learn why companies like Toyota and Verizon trust MongoDB for mission-critical AI workloads.