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Why Similarity Breaks Down at Scale

This story is from 2026-09-21. It is preserved in the archive; the latest stories are on the live feed.

Embeddings don't store meaning. They store statistical proximity. When you embed a phrase like "refund policy", the model isn't encoding what a refund actually is. It's placing that phrase in a high-dimensional space based on patterns learned from massive amounts of text. The problem starts when th…

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  1. 2026-09-21 11:42 · DEV Community — AI
    Why Similarity Breaks Down at Scale

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