@modal: The @datologyai team tested their Curation Studio at scale by generating large amounts of synthetic data on Modal, scal…

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Summary

DatologyAI 发布 Curation Studio,面向训练自研模型的团队提供可定制的前沿数据筛选服务,并在 Modal 上利用数百块 B300 GPU 进行大规模合成数据测试验证。

The @datologyai team tested their Curation Studio at scale by generating large amounts of synthetic data on Modal, scaling to hundreds of B300s on demand.
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The @datologyai team tested their Curation Studio at scale by generating large amounts of synthetic data on Modal, scaling to hundreds of B300s on demand.

DatologyAI (@datologyai): Today, we’re excited to launch the Datology Curation Studio, customizable frontier data curation for every team training its own models.

Data quality is the ultimate compute multiplier, and Curation Studio makes it easy for everyone.

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In the arXiv preprint (2606.25996), Meta's team proposes the Autodata method, where an AI agent acts as a data scientist to iteratively generate high-quality synthetic training and evaluation data. The core mechanism, Agentic Self-Instruct, forms a closed loop using an orchestrator, challenger, weak/strong solver, and judge, and introduces meta-optimization to evolve prompts, significantly improving data quality.