Why this matters: ML engineers, data scientists, and privacy engineers working with synthetic data must communicate precisely about generation methods, privacy guarantees, and evaluation frameworks. Vocabulary like epsilon-DP, fidelity vs. utility, and TSTR lets you contribute confidently to privacy-preserving ML discussions.