As many enterprises move to running AI training or inference on their data, the data and the code need to be protected, especially for large language models (LLMs). Many customers can’t risk placing their data in the cloud because of data sensitivity. Such data may contain personally identifiable information (PII) or company proprietary information, and the trained model has valuable intellectual…
]]>Rapid digital transformation has led to an explosion of sensitive data being generated across the enterprise. That data has to be stored and processed in data centers on-premises, in the cloud, or at the edge. Examples of activities that generate sensitive and personally identifiable information (PII) include credit card transactions, medical imaging or other diagnostic tests, insurance claims…
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