A lot of our experience in this domain came from our work in big corporates and large companies where we saw that things are not as efficient as we were hoping for as naive students, perhaps. The main value that we want to bring organizations as PVML is democratizing data. This can only happen if you, on one hand, protect this very sensitive data, but, on the other hand, allow easy access to it, which today is synonymous with AI.
Differential privacy is far from a new concept. The core idea is to ensure the privacy of individual users in large data sets and provide mathematical guarantees for that. One of the most common ways to achieve this is to introduce a degree of randomness into the data set, but in a way that doesn't alter the data analysis.
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