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Privacy-enhancing technologies can be generally categorized into two broad desiderata: input privacy and output privacy. Output privacy prevents reverse engineering of inputs given the outputs of a function. At Oblivious, we focus on the latter, allowing organizations who collect information to use and manipulate it in a safe and secure manner. Federated learning, homomorphic encryption, differential privacy, secure enclaves are all examples of PETs, which come in handy when you want to ensure privacy is not shared by data holders.