# Meta 发布 A-MLE 智能体框架，自动化广告排序模型的 ML 实验流程

- 来源：Rohan Paul (@rohanpaul_ai)
- 发布时间：2026-09-22 08:42
- AIHOT 分数：57
- AIHOT 链接：https://aihot.news/items/cmuby98mu04miro9iti6amw42
- 原文链接：https://x.com/rohanpaul_ai/status/2102196680665788479

## AI 摘要

Meta 发布 A-MLE（Agentic ML Exploration），一个已在自家广告排序模型上部署的 LLM 智能体框架，自动化提出想法、跑实验、恢复失败任务、比较结果并在模型间迁移经验。

## 正文

Meta published A-MLE, a new AI agent framework they actually built and deployed to automate ML experimentation across their ads-ranking models.

All because, production ML is often limited by how fast engineers can test ideas.

A-MLE, Meta's automates the repetitive loop behind improving ads-ranking models: proposing ideas, running experiments, recovering failed jobs, comparing results, and carrying useful lessons to other models.

A generic LLM scored 8% on Meta’s basic capability test, while the domain-equipped agent reached 68%.

On 1 experimental ranking model, broader exploration cut offline regression error by 2.56% relative to baseline while training QPS stayed essentially unchanged at +0.42%.