How do you teach a machine to read images and search?
The answer lies in embeddings—mathematical representations of data that make AI-powered similarity search possible.
This live demo will show you how to generate image embeddings using freely available Hugging Face models. Then, we’ll store them in Redis for fast, scalable semantic search.
Join us as we take a practical, step-by-step approach to building an image search app. Using a series of guided code commits, we’ll cover:
- What embeddings are and how they work
- How to generate image embeddings and store them in Redis
- Building a semantic search app with Redis, Python, and JavaScript
We’ll end with a demo of the full app in action.
Whether you’re new to embeddings or looking to enhance your AI apps, this session will give you the knowledge and working code to get started.
Save your seat and bring semantic image search into your projects.
Event Speaker
Guy Royse
Senior Developer Advocate
Redis
Redis 8 is here—and it's open source
