You’ve probably heard about AI a lot this year. Lately, there’s been talk about something called Retrieval Augmented Generation (RAG). Unlike a regular chat with ChatGPT, RAG lets ChatGPT search through a database for helpful information. This makes the conversation better and the answers more on point. Usually, a Vector Search engine is used as the database. It’s good at finding similar data points in a big pile of data. These data points are often at least 256-dimensional, meaning the...| ashvardanian.com
How can the 2012 Nobel Prize in Economics, Vector Search, and the world of dating come together? What are the implications for the future of databases? And why do Multi-Modal AI model evaluation datasets often fall short? Synopsis: Stable Marriages are generally computed from preference lists. Those consume too much memory. Instead, one can dynamically recalculate candidate lists using a scalable Vector Search engine. However, achieving this depends on having high-quality representations in a...| ashvardanian.com
A few years back, I found a simple trick in tandem with SIMD intrinsics to truly unleash the power of contemporary CPUs. I put the strstr of LibC and the std::search of the C++ Standard Templates Library to the test and hit a throughput of around 1.5 GB/s for substring search on a solitary core. Not too shabby, right? But imagine, that the memory bandwidth could theoretically reach a striking 10-15 GB/s per core.| ashvardanian.com
