Your embedding axes can move while cosine neighbours stay put
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An embedding can look substantially different after an orthogonal change of basis, even though its cosine similarities have not changed. I built a small browser instrument that makes that mismatch visible: the points move, the axes change, and every phrase keeps the same five cosine neighbours. The measured numerical drift stays below 2e-15 across 180 short phrases embedded into 384 dimensions with MiniLM. That is the narrow result. It is not a claim that every transformation preserves an…
1Key Takeaways
- An embedding can look substantially different after an orthogonal change of basis, even though its cosine similarities have not changed.
- I built a small browser instrument that makes that mismatch visible: the points move, the axes change, and every phrase keeps the same five cosine neighbours.
- The measured numerical drift stays below 2e-15 across 180 short phrases embedded into 384 dimensions with MiniLM.
- It is not a claim that every transformation preserves an….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that an embedding can look substantially different after an orthogonal change of basis, even though its cosine similarities have not changed.
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