Optimize RAG scale: Quality meets cost
Learn how to optimize your large-scale RAG apps for the perfect balance of quality and cost by enabling binary quantization with oversampling. With Azure AI Search, you can enhance your apps with retrieval-augmented generation capabilities and manage large-scale datasets while maintaining high-quality search results. By leveraging techniques like binary quantization, oversampling, and Matryoshka Representation Learning (MRL), you can achieve significant cost savings and improved performance without compromising quality. Azure AI Search also offers seamless integration of semantic ranking and hybrid search functionalities, allowing you to deliver personalized responses and insights. Check out Azure AI Search to optimize your RAG apps.
Video 5m
Login now to access my digest by 365.Training
Learn how my digest works
Features
- Articles, blogs, podcasts, training, and videos
- Quick read TL;DRs for each item
- Advanced filtering to prioritize what you care about
- Quick views to isolate what you are looking for right now
- Save your favorite items
- Share your favorites
- Snooze items you want to revisit when you have more time