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Ep. 194 MongoDB Community Spotlight: Justin Poveda
The interview with Justin Poveda and Brian from the MongoDB User Group in New York City provides valuable insights into the benefits and experiences associated with being part of the MongoDB community. Justin, a recent graduate and organizer of the New York City MongoDB User Group, shares his journey from attending MongoDB World as a scholarship recipient to leading the local user group. His passion for building genuine connections and creating a supportive community shines through. Brian, a new member of the group and a recent graduate in data science, highlights the learning opportunities and the sense of belonging he found in the MongoDB community. Both emphasize the value of networking, learning, and collaborating within the MongoDB ecosystem. Visit https://mdb.link/194-mug
Audio Find - Atlas Vector Search for AudioThis in-depth article explores the innovative creation of a music catalog system that leverages the power of MongoDB Atlas's vector search and a Python service for sound embedding. Discover how sound embeddings are generated using the Panns-inference model via S3 hosted files, and how similar songs are identified, creating a dynamic and personalized audio discovery experience.
RAG with Atlas Vector Search, LangChain, and OpenAILearn about Vector Search with MongoDB, LLMs, and OpenAI with the Python programming language.
Leveraging OpenAI and MongoDB Atlas for Improved Search FunctionalityThis article delves into the integration of search functionality in web apps using OpenAI's GPT-4 model and MongoDB's Atlas Vector search. By harnessing the capabilities of AI and database management, we illustrate how to create a request handler that fetches data based on user queries and applies additional filters, enhancing user experience.
Enhancing LLM Accuracy Using MongoDB Vector Search and Unstructured.io MetadataThis article provides a comprehensive guide on improving the precision of large language models using MongoDB's Vector Search and Unstructured.io's metadata extraction techniques, aiming to equip readers with the tools to produce well-sourced and contextually accurate AI outputs.
Taking RAG to Production with the MongoDB Documentation AI ChatbotExplore how MongoDB enhances developer support with its innovative AI chatbot, leveraging Retrieval Augmented Generation (RAG) technology. This article delves into the technical journey of creating an AI-driven documentation tool, discussing the RAG architecture, challenges, and solutions in implementing MongoDB Atlas for a more intuitive and efficient developer experience. Discover the future of RAG applications and MongoDB's pivotal role in this cutting-edge field.
Unlocking Semantic Search: Building a Java-Powered Movie Search Engine with Atlas Vector Search and Spring Boot
Ep. 193 Revolutionizing Real Estate with Anywhere Real Estate
In this episode, we explore the intricate challenges and digital initiatives that Anywhere Real Estate undertook to revolutionize the real estate experience. From developing scalable platforms that cater to diverse stakeholder needs to embracing MongoDB's flexible, schemaless design for modernizing their data infrastructure, Damien and Brian shed light on how MongoDB plays a pivotal role in their ecosystem.
Discover how they're leveraging MongoDB's document model to handle unique property attributes and enhance search capabilities, and delve into their strategy for building a versatile, modern technology team. Join us as we unpack the lessons learned, best practices, and future plans in Anywhere's journey, highlighting their commitment to innovation and excellence in the ever-evolving world of real estate technology.
Read More at Venture Beat: https://mdb.link/vb-anywhere
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