Abstract: In one aspect, a method of guarding an automated software includes generating, by a first language model, a training set of rule-violating data, generating, by the first language model, a training set of contrastive examples by altering the rule-violating data into non-violating data, training a guardrail machine learning model using the generated training sets, generating, with an automated software, an output based on a user input, monitoring with the trained guardrail machine learn model whether the generated output violates a rule, and preventing the automated software from transmitting to the user the generated output that violates a rule.

Abstract: Techniques for responding to a healthcare inquiry from a user are disclosed. In one particular embodiment, the techniques may be realized as a method for responding to a healthcare inquiry from a user, according to a set of instructions stored on a memory of a computing device and executed by a processor of the computing device, the method comprising the steps of: classifying an intent of the user based on the healthcare inquiry; instantiating a conversational engine based on the intent; eliciting, by the conversational engine, information from the user; and presenting one or more medical recommendations to the user based at least in part on the information.

Abstract: Techniques for responding to a healthcare inquiry from a user are disclosed. In one particular embodiment, the techniques may be realized as a method for responding to a healthcare inquiry from a user, according to a set of instructions stored on a memory of a computing device and executed by a processor of the computing device, the method comprising the steps of: classifying an intent of the user based on the healthcare inquiry; identifying the intent as a need to obtain a dermatological diagnosis or treatment; soliciting, from the user and via the computing device, an image of the user's skin area to be diagnosed or treated; instantiating an image classification system to identify a dermatological disease from the image; and presenting one or more medical recommendations to the user based on the identified dermatological disease.

Abstract: Techniques for responding to a healthcare inquiry from a user are disclosed. In one particular embodiment, the techniques may be realized as a method for responding to a healthcare inquiry from a user, according to a set of instructions stored on a memory of a computing device and executed by a processor of the computing device, the method comprising the steps of: classifying an intent of the user based on the healthcare inquiry; instantiating a conversational engine based on the intent; eliciting, by the conversational engine, information from the user; and presenting one or more medical recommendations to the user based at least in part on the information.

Abstract: Techniques for responding to a healthcare inquiry from a user are disclosed. In one particular embodiment, the techniques may be realized as a method for responding to a healthcare inquiry from a user, according to a set of instructions stored on a memory of a computing device and executed by a processor of the computing device, the method comprising the steps of: classifying an intent of the user based on the healthcare inquiry; identifying the intent as a need to obtain a dermatological diagnosis or treatment; soliciting, from the user and via the computing device, an image of the user's skin area to be diagnosed or treated; instantiating an image classification system to identify a dermatological disease from the image; and presenting one or more medical recommendations to the user based on the identified dermatological disease.