AI models run on large amounts of good quality data, and when it comes to sensitive tasks like medical diagnosis or financial risk assessments, you need access to private data during both training and inference. When performing machine learning tasks in the cloud, enterprises are understandably concerned about data privacy as well as their model’s intellectual property. Additionally, stringent industry regulations often prohibit the sharing of such data.

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John Martin, Director and Principal Consultant at Broch Solutions, shares his thoughts on the biggest changes in the financial services industry.