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Designing synthetic datasets for the real world: Mechanism design and reasoning from first principles
This Google Research work presents guidelines for synthetic data mechanism design and provides insights into generating and evaluating synthetic data at scale. The research introduces a reasoning-driv
This Google Research work presents guidelines for synthetic data mechanism design and provides insights into generating and evaluating synthetic data at scale. The research introduces a reasoning-driven framework that employs a seedless, agentic approach to generate synthetic datasets with fine-grained control, allowing users to define desired dataset characteristics through an explainable and controllable process. The work unlocks new opportunities for developing and deploying AI in domains where data scarcity or privacy concerns are paramount.
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Source: Google Research | 2026-04-16