Chang Liu Interview – Epsilon Software for Private Machine Learning
In this episode, our final episode in the Differential Privacy series, I speak with Chang Liu, applied research scientist at Georgian Partners, a venture capital firm that invests in growth-stage business software companies in the US and Canada.
Chang joined me to discuss Georgian’s new offering, Epsilon, a software product that embodies the research, development, and lessons learned helps in helping their portfolio companies deliver differentially private machine learning solutions to their customers. In our conversation, Chang discusses some of the projects that led to the creation of Epsilon, including differentially private machine learning projects at BlueCore, Work Fusion, and Integrate.ai. We explore some of the unique challenges of productizing differentially private ML, including business, people, and technology issues. Finally, Chang provides some great pointers for those who’d like to further explore this field.
The notes for this show can be found at https://twimlai.com/talk/135
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