MyDataWork POV — Conditional generation sounds like a promising evolution for synthetic data, but its practicality remains unproven. The claim that it improves fairness and risk management is ambitious, yet lacks detailed evidence. How do we ensure these 'targeted, realistic datasets' truly mirror complex, real-world nuances? Without clear benchmarks or case studies demonstrating its application, skepticism lingers. It's one thing to promise enhanced model training; it's another to deliver verifiable improvements in AI fairness and trust.