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Large-Scale Synthetic Data Generation

Large-Scale Synthetic Data Generation

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2026

The platform now supports large-scale synthetic data generation, enabling the creation of diverse and high-signal training data for AI models. This includes systems for procedural generation of physical scenarios using simulators, automatic construction of verified question-answer pairs, and optimization of data generation pipelines for various model sizes and benchmarks. The focus is on moving beyond human annotation to scalable, simulation-driven data creation.

2026

We’re entering the age of large-scale synthetic data

6/18/2026

Introduces Sim2Reason, a system that turns physics simulators into scalable data engines for generating synthetic data. It procedurally generates diverse physical scenarios in MuJoCo, extracts complete physical traces, and automatically constructs verified question-answer pairs (numeric, reverse, symbolic) without human annotation. Models trained on Sim2Reason data showed significant zero-shot performance improvements on physics and math reasoning benchmarks, demonstrating the value of aligned synthetic data.