Embedding Drift Detection Is Broken by the Curse of Dimensionality
TL;DR — Most ML observability stacks still monitor embeddings the way they monitor table columns: one statistical test per dimension. That approach is mathematically unsound in high-dimensional vector space, where marginal stability can coexist with catastrophic structural shift. Real embedding obs…
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- 2026-10-14 13:16 · DEV Community — Machine Learning
Embedding Drift Detection Is Broken by the Curse of Dimensionality