In this episode of our Differential Privacy series, I’m joined by Zahi Karam, Director of Data Science at Bluecore, whose retail marketing platform specializes in personalized email marketing.
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I sat down with Zahi at the Georgian Partners portfolio conference last year, where he gave me my initial exposure to the field of differential privacy, ultimately leading to this series. Zahi shared his insights into how differential privacy can be deployed in the real world and some of the technical and cultural challenges to doing so. We discuss the Bluecore use case in depth, including why and for whom they build differentially private machine learning models.
Thanks to our Sponsor!
Thanks to Georgian Partners for their continued support of the podcast and for sponsoring this series. Georgian Partners is a venture capital firm that invests in growth stage business software companies in the US and Canada. Post investment, Georgian works closely with portfolio companies to accelerate adoption of key technologies including machine learning and differential privacy. To help their portfolio companies provide privacy guarantees to their customers, Georgian recently launched its first software product, Epsilon, which is a differentially private machine learning solution. You’ll learn more about Epsilon in my interview with Georgian’s Chang Liu later this week, but if you find this field interesting, I’d encourage you to visit the differential privacy resource center they’ve set up at https://gptrs.vc/twimlai
Mentioned in the Interview
- “Robust De-anonymization of Large Sparse Datasets – Privacy Lives.”
- Georgian Partners
- Visit the Differential Privacy series page!
- Check out @ShirinGlander’s Great TWIML Sketches!
- TWIML Presents: Series page
- TWIML Events Page
- TWIML Meetup
- TWIML Newsletter
“More On That Later” by Lee Rosevere licensed under CC By 4.0