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AIintermediate
Recommender Systems: The Two-Stage Machine
No model ranks the whole catalogue: a cheap retrieval stage cuts millions of items to hundreds, an expensive ranker orders those hundreds, and the trap nobody warns you about is that the model trains on clicks it caused. This path builds the architecture, the two-tower geometry of taste, the objective functions that encode what a product values, and the feedback loops and exploration budgets that decide what the system becomes.
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