Google Research· Research

Designing synthetic datasets for the real world: Mechanism design and reasoning from first principles

Tim R. Davidson, Student Researcher, and Hamza Harkous, Senior Staff Research Scientist, Google To address the scarcity of data required for specialized AI, we introduce Simula, a framework that reframes synthetic data generation as dataset-level mechanism design. By using reasoning to architect datasets from first principles, Simula enables fine-grained control over coverage, complexity, and quality, providing scalable generation for privacy-sensitive or data-scarce domains. Quick links Paper Share Copy link × The rapid advance of generalist AI models has been fueled by the abundance of internet data. However, widespread integration of AI will require models to specialize in novel, uncommon, and privacy-sensitive applications where data is inherently scarce or inaccessible. To bridge this gap, reliance on real-world data imposes significant limitations: Cost and accessibility: Creating specialized datasets manually is prohibitively expensive, time-consuming, and error-prone. …

Announced

16 Apr 2026 14:41 UTC