Latent Space 发布前沿 AEO 追踪器：分析模型推荐偏好与偏差
原标题：The Frontier AEO Tracker: What Astra Chooses (and every other frontier model, and what you can do about it)
AI 摘要
Latent Space 发布了一个前沿 AEO（AI 引擎优化）追踪器，基于 7 个前沿模型在 161 个类别中的推荐结果，分析各产品在 AI 推荐中的主导地位。报告发现模型存在偏好偏差（如 Claude 推荐自家产品），但也观察到跨模型推荐案例。此外，Anthropic 的新模型 Astra 比 Sol 更自信且搜索来源更少，影响了 AEO 策略的有效性。该追踪器还提供了可检查的提示-回答对，并开放商业合作。
正文节选
Naive autoresearch investment in our AEO have yielded impressive ROI, and so naturally it was time to take it seriously. We were inspired by What Claude Code Actually Chooses, and decided to extend/adjust it to our tastes. After a few billion tokens of prototyping, aligning, and scaling pipelines, here’s the Latent Space Frontier AEO tracker. Our methodology extends AmplifyingAI’s to run 6 prompt variations over 7 models1 (search on) in 161 categories, from coding agents to AI podcasts to AI San