Large language model-based communication assistant
AssigneeApple Inc.
InventorsLorenzo BERTIZZOLO, Murali Mohan CHAKKA, Prashant H. VASHI
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Abstract
Systems and methods provide for training a machine learning model for handling communications on behalf of the user are provided. A plurality of contextual information and a plurality of prior communications is selected based on one or more pre-configured data privacy settings. A training dataset is generated using the contextual information and the prior communications. A machine learning model is trained that can receive a query from an entity and in response, generate a response for the entity. The response is then transmitted back to the entity.
Claims20
A computer-implemented method comprising:
- selecting, by a user device, a plurality of contextual information associated with a user and a plurality of prior communications of the user based on one or more pre-configured data privacy settings;
- generating a plurality of training samples from the plurality of prior communications and the plurality of contextual information;
- training a machine learning model using the plurality of training samples;
- receiving a query from an entity, the query being directed to the user;
- using the machine learning model to generate a response to the query on behalf of the user;
- and
- providing the response to the entity.
A device comprising:
- a memory;
- and
- a processor configured to:
- select a plurality of contextual information associated with a user and a plurality of prior communications of the user based on one or more pre-configured data privacy settings;
- generate a plurality of training samples from the plurality of prior communications and the plurality of contextual information;
- train a machine learning model using the plurality of training samples;
- receive a query from an entity, the query being directed to the user;
- use the machine learning model to generate a response to the query on behalf of the user;
- and
- provide the response to the entity.
A computer program product comprising code stored in a tangible computer-readable storage medium, the code comprising:
- code to select, by a user device, a plurality of contextual information associated with a user and a plurality of prior communications of the user based on one or more pre-configured data privacy settings;
- code to generate a plurality of training samples from the plurality of prior communications and the plurality of contextual information;
- code to train a machine learning model using the plurality of training samples;
- code to receive a query from an entity, the query being directed to the user;
- code to use the machine learning model to generate a response to the query on behalf of the user;
- and
- code to provide the response to the entity.
Dependencies are inferred from the claim text.