Confidential AI with Ubuntu on Azure: a deep dive | Data & AI Masters | Canonical and Microsoft
When performing machine learning tasks in the cloud, enterprises understandably have concerns about the potential compromise of their sensitive data privacy as well as their model’s intellectual property. Additionally, stringent industry regulations often prohibit the sharing of such data. This makes it difficult, or outright impossible, to utilise large amounts of valuable private data, limiting the true potential of AI across crucial domains.
