Leveraging Vector Search for Enhanced Content Interaction

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This chapter explores the integration of vector search in chatbots to improve user experience through relevant content retrieval. It highlights the use of embeddings and large language models for personalized responses, along with the role of open source frameworks in efficient application development.

MongoDB Atlas is a managed NoSQL database that uses JSON-like documents with optional schemas. The platform recently released new vector search capabilities to facilitate building AI capabilities.

Ben Flast is the Director of Product Management at MongoDB. He joins the show to talk about the company’s developments with vector search.

This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book, Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments.

Lee is the host of his podcast, Modern Digital Business, an engaging and informative podcast produced for people looking to build and grow their digital business with the help of modern applications and processes developed for today’s fast-moving business environment. Listen at mdb.fm. Follow Lee at softwarearchitectureinsights.com, and see all his content at leeatchison.com.

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