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What are the real tradeoffs of k-NN, and what breaks it at scale and in high dimensions?

k-NN looks trivial until you ask about choosing k, why distances stop meaning anything in high dimensions, and how to make prediction fast on millions of points. Here is the tradeoff-aware answer.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

k-NN looks trivial until you ask about choosing k, why distances stop meaning anything in high dimensions, and how to make prediction fast on millions of points. Here is the tradeoff-aware answer.

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