Bring AI-Based Search to Your Web App

Daniel Phiri

Bring AI-Based Search to Your Web App
ChatGPT took the tech world by storm. Everyone talks about it, from your CTO to your hairdresser (at least my barber does). And there are many reasons why we should all be excited about it and many other AI/ML innovations.

But how do you bring them into your tech stack, your website/backend, to work with your data and provide AI-driven search and data augmentation?
There is a new generation of AI-Native databases, which use deep learning models to find answers to natural language queries. We are talking about the ability to search through text, images, videos, DNA, or any unstructured data, all with a single query.
The rule of thumb: if there is an ML model, we can search through it.

Join me to learn about the foundation blocks (LLMs and vector embeddings, Vector Databases), how they all play together, and most importantly - how to build something yourself with open-source tech.
And, of course!!! There will be a live-coding demo, where I will take you through the experience of building an AI-based search – with Weaviate, an open-source Vector Database – and adding it to an app. Now the question... should this be done in Angular, React, Vue or just pure JS ;)
#MayTheDemoGodsBeWithUs

Daniel Phiri - Developer Advocate, Weaviate | France
Daniel is a senior developer advocate for Weaviate - an open source vector database. He spends a lot of his time curating music and writing (about) software. He is passionate about working with developers and building cool projects.