Opening Keynote - Relevance in the Age of Generative Search

The search relevance landscape is rapidly shifting. Due to the rise of Transformers and Large Language Models (LLMs) and the more recent emergent capabilities shown with Foundation Models, public search engines are now rushing to integrate models like chatGPT directly into the search experience as a form of "generative search". These models can perform abstractive question answering, summarization, and even new content generation, but when untethered from underlying search results, often hallucinate bogus or misleading information. As search relevance practitioners, it’s important for us to know how these technologies work and how to best integrate them into search experiences to drive accurate, relevant results. In this talk, we’ll walk through code examples and strategies to integrate this emerging class of language models into our search applications, covering the limitations of the models amidst other relevance techniques as well as the amazing new capabilities they enable.

Trey Grainger

Presearch

Trey Grainger is the CTO of Presearch, the decentralized web search engine, and is the founder of Searchkernel, a software company and consultancy building the next generation of AI-powered search. He is lead author of the book AI-Powered Search (Manning 2023) and co-author of Solr in Action (Manning 2014). He is the former Chief Algorithms Officer and SVP of Engineering at Lucidworks, an AI-powered search company whose search technology powers hundreds of the world’s leading organizations. Trey has over 15 years of experience in search and data science, including significant work developing semantic search, personalization and recommendation systems, and building self-learning search platforms leveraging content and behavior-based reflected intelligence. This work resulted in the publications of dozens of research papers, journal articles, conference presentations, and books at the intersection of search and AI.