Brief

Researchers have developed Larch, a new framework designed to optimize the execution of semantic filters within AI SQL queries. Larch addresses the high inference costs and latencies associated with semantic operators, which treat AI-generated filters as black boxes, hindering traditional optimization. The framework utilizes embedding-augmented neural networks and supervised learning models to predict filter selectivities and determine optimal evaluation orders, significantly reducing token usage. AI