Combinatorial Stable Marriages for DBMS Semantic Joins 💍
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 shared Vector Space. While this already works well for text-based features using modern BERT-like architectures, the quality decreases significantly for Multi-Modal data. This shortcoming, reflected in OpenAI’s CLIP and our own Unum’s UForm, signifies the need for improving modern space-alignment techniques. Their advancement could not only catalyze the integration of AI into databases but also enhance the performance of upcoming Generative Vision-Language models. ...