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Explore personalized search using multimodal latent behavioral embeddings. Learn to integrate user behavior into modern search retrieval pipelines for RAG and end-user search, enhancing relevance and user experience.
Learn to build production-ready RAG applications with insights from Moody's rapid development. Gain strategies for embedding, relevance measurement, cost management, and team organization for impactful AI-driven data interaction.
Explore Moody's journey from legacy SOLR to cloud-native AWS OpenSearch, enhancing search architecture with AI integration and custom relevance systems for improved cross-product usability and intelligent search experiences.
Learn techniques to measure and enhance retrieval quality in RAG systems, exploring alternatives to human expert judgments and methods for tuning retrieval to improve generated responses.
Explore how a simple Round Robin algorithm significantly improved search relevance in an enterprise application, challenging the notion that complex solutions are always better.
Explore multimodal RAG workflows for enhanced retrieval and generation, incorporating text, tables, and images. Live demo showcases PDF processing, vector database usage, and LLM-enriched responses.
Explore cutting-edge search and AI topics through lightning talks from Haystack US 2024. Gain insights on information retrieval, LLMs, vector search, semantic search, and more from industry experts.
Explore strategies for enhancing search relevance by combining traditional keyword-based methods with semantic search, addressing limitations and improving user satisfaction.
Discover how User Behavior Insights system standardizes data collection for search professionals, enabling improved relevance and user experience through analysis of search patterns and behaviors.
Explore common pitfalls in RAG projects and learn strategies to ensure success. Gain insights on project organization, execution, and overcoming challenges in implementing chatbots and QA systems.
Explore AI-powered information retrieval strategies with Women of Search experts. Analyze fine-tuning ML models, RAG pipelines, and reranking methods for optimal use in search applications.
Explore image-based recommendations for grocery shopping using AI. Learn to build and evaluate benchmarks for image vectorization models, improving differentiation between similar food items.
Explore hybrid search in RAG systems, combining metadata filtering and re-ranking for scalable LLM recommenders. Learn core concepts of retrieval, filtering, and ranking.
Explore Yelp's journey in leveraging LLMs for search query understanding, from concept to production. Learn about challenges, solutions, and the impact on user experience in search functionality.
Explore dense vector search at scale, balancing cost, speed, and quality. Learn reusable methods for testing index and query performance, gaining insights for integrating vector search into existing pipelines.
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