Uploaded July 2024 | Updated September 2026, 56 minutes ago

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Retrieval Augmented Generation (RAG) has quickly become a popular use case for Large Language Models. In this video, we’ll dive into the various use cases of RAG systems and demonstrate how generative feedback loops can enhance performance and take your RAG applications to the next level.

RAG Benefits: Improving chatbot interactions and semantic search with Weaviate.

Verba Demo: Our open-source RAG app for Airbnb showcases enhanced booking assistance.

Generative Feedback Loops (GFL): Boosting efficiency and reducing costs by saving generated responses into the database.

Real-World Applications: Implementing self-healing databases in healthcare, legal, e-commerce and more

GFL Blogpost: weaviate.io/blog/generative-feedback-loops-with-llms
GFL Documentation: weaviate.io/developers/weaviate/configuration/modules#generative-modules

Weaviate Academy: weaviate.io/developers/academy
Weaviate Starting Guide: weaviate.io/developers/weaviate/starter-guides

Verba GitHub: github.com/weaviate/verba
Verba Demo: verba.weaviate.io

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Music:
Linear Daybreak - Brendon Moeller
Melodic Flow - VELDA

00:00 - Introduction
00:22 - Real-life Usecase
02:24 - RAG as Solution
04:11 - AI Agents in RAG
06:00 - RAG in Weaviate
08:00 - GFL Examples
09:25 - Outro