Heard on the Street: The Key To Unlocking AI Growth has a Name, Privacy Technologies
The fundamental problem with AI development begins with data acquisition. How do you acquire quality data, with the volume and diversity necessary to move a model from R&D to production? Which regulations are applicable? How do you use that data while protecting model IP and maintaining data input privacy? What if those with useful data aren’t using a similar environment or are in another country? Answers to these questions are found in workflows that operationalize PETs into AI engineering operations; privacy-protected AI collaboration solutions. PETs provide the means for satisfying regulations by protecting data and model IP through technical guardrails versus bulky, limited, process-driven workarounds.