TAGGEDPRIVACY 4 POSTS

Posts about PRIVACY.

2026.06.26 PRIVACY

Differential privacy for fine-tuning: when it earns its cost.

Fine-tune on data with PII in it and the model can be made to recite it back verbatim. DP-SGD bounds that — at a measured cost of a point or two of accuracy for a pretrained model, not the catastrophe the folklore claims. When the threat model justifies paying it.

11 min →

2026.04.17 PRIVACY

PII redaction that does not wreck retrieval.

Stripping PII before documents reach the embedding model is often necessary. But naive redaction destroys the semantic signal retrieval depends on. How to redact without wrecking retrieval.

10 min →

2026.03.25 PRIVACY

Confidential RAG: keep the context secret, not just the query.

Most private RAG protects the user's query in transit and leaves the corpus exposed. But the corpus is the sensitive asset — the embeddings, the vector store, and the chunks the model sees all need protecting.

11 min →

2026.01.18 PRIVACY

FHE vs TEE for ML: when to use which.

Two ways to compute on data you can't see. One is cryptographically pure and 100,000x slower; the other is fast and depends on a chip vendor not being broken. A decision tree.