Jeff Dean: AI Search relies on classic ranking and retrieval
- 4 hours ago
- 1 min read
In an interview on Latent Space: The AI Engineer Podcast, Google’s chief AI scientist explained how Google’s AI systems work and how much they rely on traditional search infrastructure.
The architecture: filter first, reason last. Visibility still depends on clearing ranking thresholds. Content must enter the broad candidate pool, then survive deeper reranking before it can be used in an AI-generated response. Put simply, AI doesn’t replace ranking. It sits on top of it.
Dean said an LLM-powered system doesn’t read the entire web at once. It starts with Google’s full index, then uses lightweight methods to identify a large candidate pool — tens of thousands of documents.
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