Machine learning on encrypted data? with Alexander Fried at Flybits
The Data Standard
The world is changing and privacy is becoming a huge concern. The area of machine learning on encrypted data is booming and expected to grow significantly over the next 5 years. In this episode of the Data Standard Audio Experience, we spoke with Alexander Fried, Director of Data and Computational Science at Flybits. In a recent talk, we described the importance of data, various methods for estimating the value of data, and emerging tools for incentivizing data sharing across organizations. As we noted, the main motivation for improving data liquidity is the growing importance of machine learning. We’re all familiar with the importance of data security and privacy, but probably not as many people are aware of the emerging set of tools at the intersection of machine learning and security.
Meet The Host
Data scientist at The Data Standard
Catherine Tao is a tech enthusiast looking for new methods for building connections with businesses around the world. Her extensive knowledge of data science allowed her to develop new solutions and implement them into existing ecosystems. She is currently working as a Data scientist and Exclusive Podcast Producer at The Data Standard.
Meet The Guest
Director of Data and Computational Science at Flybits
I am a data scientist leader, product innovator and full stack machine learning expert, generally interested in opportunities in deep-tech. I have had much experience identifying opportunities and then enabling teams to rapidly progress from research stage efforts to fully deployed applications.