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When it comes to cutting-edge AI, Daniel Svonava, CEO of Superlinked, always has something fascinating to share. At AIQON 2024, he dove into the world of Retrieval-Augmented Generation (RAG) and vector search, breaking down how we can evaluate and improve these systems to make them even more impactful.
Daniel touched on a lot of important ground, starting with how we currently evaluate RAG quality. He pointed out that embedding models are at the core of these systems, and benchmarking them effectively is key to driving real progress. Beyond just the tech, he emphasized the importance of setting clear goals and measuring retrieval performance against them—a step many teams overlook.
Drawing inspiration from the search and relevance industry, Daniel showed how tried-and-true practices can help solve modern challenges. But he didn’t shy away from addressing the unique hurdles that come with embedding-powered retrieval, like managing high-dimensional data and maintaining consistent results in complex systems.
To bring it all home, Daniel shared practical tips for boosting vector search performance. His message was clear: small, strategic adjustments to retrieval can make a huge difference in how these systems perform in the real world.
Curious to learn more? Watch the full session below to see how you can level up your RAG and vector search projects!
Need help getting the most out of your vector-powered projects? We’re here to help, let’s chat!—Superlinked can help you build smarter, more scalable solutions.