CPC G06Q 10/063 (2013.01) [G06F 18/2148 (2023.01); G06F 21/6218 (2013.01); G06N 20/00 (2019.01)] | 20 Claims |
1. A method comprising:
obtaining, with one or more processors, a first trained machine learning model accessible to a first entity, wherein:
the first machine learning model is trained on a first training set that includes data the first entity is not permitted to provide to a second entity,
the first trained machine learning model is configured to output tokens, and
the tokens do not reveal more than a threshold amount of information about the data the first entity is not permitted to provide to the second entity;
receiving, with one or more processors, a first set of input features with the first trained machine learning model and, in response, outputting a first token; and
causing, with one or more processors, the first token and a first value associated with the first token to be input into a second trained machine learning model accessible to the second entity, wherein the first value associated with the first token is a token-context value corresponding to the first token, and wherein at least some of the a first set of input features are not provided to the second trained machine learning model.
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