Generally speaking, the more data you have, the better your machine learning model is going to be.
However, stockpiling vast amounts of data also carries a certain privacy, security, and regulatory risks.
With new privacy-preserving techniques, however, data scientists can move forward with their AI projects without putting privacy at risk.
To get the low down on privacy-preserving machine learning (PPML), we talked to Intel’s Casimir Wierzynski, a senior director in the office of the CTO in the company’s AI Platforms Group. Wierzynski leads Intel’s research efforts to “identify, synthesize, and incubate” emerging technologies for AI.
