Scaling Vector Database Operations with MongoDB and Voyage AI
The news is out! Voyage AI, a leader in embedding and reranking models that make AI-powered search and retrieval more accurate, has now joined MongoDB. In our recent webinar, MongoDB’s Frank Liu, Staff Product Manager and Richmond Alake, Staff Developer Advocate break down the powerful new AI capabilities that are now easily accessible to developers everywhere. A few highlights from the discussion include:
*Why these embedding models are so important is if you have a very really powerful one—one that’s able to understand semantic relationships between texts and one that is able to pick apart a lot of the nuances in your inputs—then you're going to be able to have a really powerful search and retrieval system.*
— Frank Liu, Staff Product Manager, MongoDB
*What does this mean for you as a developer? Well, I build these AI applications almost every day. So it really means less code. If you have your data layer that can handle the embedding generation and also the re-ranking. It's just less code—and that's good—but also it really means that you can have a reliable retrieval process. And Voyage AI embedding models are the state of the art, the best in class across any way you want to cut them, including domain specific models.*
— Richmond Alake, Staff Developer Advocate, MongoDB
Watch it on-demand now for a deep dive into reranking and vector embeddings for building AI-powered user experiences followed by a technical question-and-answer period. We hope to see you at our next webinar!
