Meta 提出 Autodata：用 AI 智能体动态构建训练数据

New research from Meta.

Building synthetic training data has stayed a fixed pipeline that you hand-tune and then freeze.

Autodata casts an AI agent as a data scientist that builds training and evaluation data, with an implementation called Agentic Self-Instruct that extends classic Self-Instruct with agentic planning and tool use.

Think of it as meta-optimization, where the data scientist agent is itself trained to produce stronger data, so the pipeline keeps improving instead of staying static.

Across computer science research, legal reasoning, and reasoning over mathematical objects, it beats classical synthetic-data methods, and meta-optimizing the agent delivers an even larger uplift.

Paper: https://arxiv.org/abs/2606.25996

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