Generative AI (GenAI) is changing how forward-looking organizations approach search, knowledge management, and other forms of knowledge discovery. Search is foundational for helping organizations discover, analyze, and utilize key data. However, with ever-increasing amounts of data, legacy search systems can struggle to help users quickly find what they need and avoid wasting time. Modern search systems have made great leaps […]
Read more ›Articles By: Elastic
Building search in the age of generative AI: A blueprint for success
There’s never been a better time to create exceptional search experiences. By leveraging the capabilities of LLMs and generative AI, we can predict user intent, improve relevance, surface timely content, and even provide human-like responses. But one size doesn’t fit all for search. You can utilize out-of-the-box technology, build your own with feature-rich, custom design and functionality, or anything in-between. […]
Read more ›Semantic search excellence: Getting started with AI
Overview This is part one of a two-part series on the journey to semantic search and generative AI excellence. Join us as we guide you through the spectrum of search methodologies, the steps to building search that understands the meaning of a query, and the choices and options along this path. We’ll start with foundational text search using BM25 and […]
Read more ›Beyond RAG basics: Strategies and best practices for implementing RAG
Overview Join us to explore advanced techniques in retrieval augmented generation (RAG). This talk is for developers, data scientists, and AI enthusiasts, and provides essential insights to elevate your RAG systems. If you’ve played around with RAG, and are looking to optimize existing implementations, our speakers will discuss practical steps to help you build RAG-based systems that run in production […]
Read more ›AI deep dive: A technical guide to the foundations of search and generative AI
This technical whitepaper takes you deep into the inner workings of generative AI and vector databases. It provides a detailed look at the technical foundations of vector embeddings, generative AI architecture, and how retrieval-augmented generation (RAG) works to provide LLMs with the critical domain-specific knowledge they need. Highlights• Demystifying ChatGPT: Different methods for building AI search• Generative AI architectures with […]
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