Retrieval-Augmented Generation (RAG) systems generally rely on dense embedding models that map queries and documents into fixed-dimensional vector spaces. While this approach has become the default for many AI applications, a recent research from Google DeepMind team explains a fundamental architectural limitation that cannot be solved by larger models or better training alone. What Is […] The post Google DeepMind Finds a Fundamental Bug in RAG: Embedding Limits Break Retrieval at Scale app...| MarkTechPost
Compare SearchGPT, Perplexity, and Claude AI search engines. Find the best tool for your needs and improve your search experience.| AI GPT Journal
Live Webinar: Unlock the Future of eCommerce – May 8, 2 PM CET.| Vespa Blog
Introducing Vespa Voice: a podcast on AI infrastructure, hybrid search, and RAG.| Vespa Blog
SCAN plugin for adding web-locations is released. If you haven’t noticed already, there was no simple way to just enter a web URL in SCAN and get a document in the repository. One had to add web documents via del.icio.us or fetch them from RSS. Now it is fixed – with Web plugin you can […]| Cyberborean Chronicles
What’s new in 1.3 version »| Cyberborean Chronicles
New version of SCAN Frequently Asked Questions page is available. “How does SCAN help me?”, “Why should I use it?”, “Who are the users?”, “Why it is smart?…| Cyberborean Chronicles
Have you ever wondered how the world’s largest internet and social media companies can deliver algorithmic content to so many users so fast?| Vespa Blog
How MRL and BQL Make AI-Powered Representations Efficient| Vespa Blog
ColPali simplifies and enhances information retrieval from complex, visually rich documents, transforming retrieval-augmented generation| Vespa Blog
A beginner’s guide to Vespa, exploring its role in information retrieval and its advantages for enterprise AI applications.| Vespa Blog