Haystack EU 2024 – Tetiana Torovets,Giulio Santo & Lucas Cardozo:A Multimodal Housing Search Chatbot
Building a Multimodal LLM-Based Search Assistant Chatbot to Enhance Housing Search QuintoAndar Group is the largest…
Haystack EU 2024 – Jo Kristian Bergum:What You See Is What You Search: Vision Language Models & PDFs
Extracting information from complex document formats like PDFs usually involves a multi-step process, including text extraction,…
Haystack EU 2024 -Marcin Gumkowski & Catarina Gonçalves:LTR Framework-how to train an army of models
At OLX, we faced a significant challenge: the need to experiment with rankings across many countries…
Haystack EU 2024 – Sean MacAvaney: Re-Thinking Re-Ranking
Re-ranking systems often rely on a ‘cascading’ approach, where an initial set of documents is re-sorted…
Haystack EU 2024 – Aswath N Srinivasan:Leveraging User Behavior Insights to Enhance Search Relevance
Even with the all advancements in search engine technologies with vectorDBs and LLMs, for Search practitioners…
Haystack US 2024 – Trey Grainger: Personalizing search using multimodal latent behavioral embeddings
earning user context from behavioral signals is critical for optimizing search relevance, but most search engine…
Haystack US 2024 – Jeff Capobianco: Chat With Your Data – A Practical Guide to Production RAG Apps
At Moody’s, we went from a laptop prototype to a premium-subscription RAG product in under 6…
Haystack US 2024 – Jeremy Hudson & René Kriegler: Evolution of Moody’s Search & AI
Day 2 Keynote – Evolution of Moody’s Search: Embracing Cloud-Native Solutions to Enable AI-Powered Product This…
Haystack US 2024 – Scott Stults: Measuring and Improving the R in RAG
The quality of text generated by a RAG system is limited by the quality of the…
Haystack US 2024 – Joelle Robinson: Revisiting the Basics: How Round Robin Improved Search Relevancy
In the rapidly evolving landscape of search technologies, the allure of novel, complex algorithms often overshadows…
