Protected fine-tuning of a machine learning model

A computing system comprising:

• one or more processors;
• and
• one or more computer-readable media having thereon computer-executable instructions that are structured such that, if executed by the one or more processors, the computing system would be configured to fine-tune a machine learning model in a protected environment such that a tune initiator system that instruct that the fine-tuning occur does not having visibility of a resulting fine-tuned model or at least some information used in the fine-tuning, by being configured to perform the following:
• receive first input into the protected environment from the tune initiator system via a first channel that is visible to the tune initiator system, the first input including training data;
• access second input over a second channel that is not visible to the tune initiator system;
• use the first input and the second input to fine-tune a machine learning model to thereby form a fine-tuned machine learning model;
• and
• store the fine-tuned machine learning model in the protected environment such that the fine-tuned machine learning model is available for the tune initiator system to provide input data to and receive output data from, but such that the fine-tuned machine learning model cannot be directly accessed by the tune initiator system.