[A version of this post appears on the O’Reilly Radar.]
The O’Reilly Data Show Podcast: Alon Kaufman on the interplay between machine learning, encryption, and security.
In this episode of the Data Show, I spoke with Alon Kaufman, CEO and co-founder of Duality Technologies, a startup building tools that will allow companies to apply analytics and machine learning to encrypted data. In a recent talk, I described the importance of data, various methods for estimating the value of data, and emerging tools for incentivizing data sharing across organizations. As I 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. Kaufman and his stellar roster of co-founders are doing some of the most interesting work in this area.
Here are some highlights from our conversation:
Running machine learning models on encrypted data
Four or five years ago, techniques for running machine learning models on data while it’s encrypted were being discussed in the academic world. We did a few trials of this and although the results were fascinating, it still wasn’t practical.
… There have been big breakthroughs that have led to it becoming feasible. A few years ago, it was more theoretical. Now it’s becoming feasible. This is the right time to build a company. Not only because of the technology feasibility but definitely because of the need in the market.