Abstract: Systems and methods for providing a digital human in a virtual space are disclosed herein. A system receives, from a user via a digital platform, a selection of a persona, for a digital human, from a plurality of personas. Further, the system receives, in real-time, an input from the user via the digital platform, and identifies a set of parameters associated with the input. Furthermore, the system determines, from a knowledge database, a response information based on the context of the input, and generates, using a repository, a set of attributes for the response information based at least on the set of parameters associated with the input and the persona selected by the user. Additionally, the system aggregates the set of attributes and the response information to generate a personalized response to the input, and renders the personalized response by the digital human on the digital platform.

Abstract: A device may receive assessment scores for a candidate associated with an entity and performance data identifying performance metrics and time periods associated with existing members of the entity. The device may process the assessment scores and the performance data, with an attrition model, to identify attrition scores for the candidate and confidences of the attrition scores, and may calculate a final attrition score based on the attrition scores. The device may process the assessment scores and the performance data, with a performance model, to identify performance scores for the candidate and confidences of the performance scores, and may calculate a final performance score based on the performance scores. The device may calculate an overall score based on the final attrition score and the final performance score, and may perform one or more actions based on the overall score.

Abstract: A device may receive a query from a user device, and may process the query using a machine learning model to determine categories related to the query. The device may send a message, instructing a user to select a category, to the user device to cause the user device to display the message. The device may receive, from the user device, a selection related to the categories, and may call, based on the selection, a module to cause the module to process the query. The device may receive from the module a response to the query, and may send the response to the user device, to cause the user device to display the response. The device may send the query, the selection, and the response to one or more servers for storage, and may retrain the machine learning model based on information stored by the one or more servers.

Abstract: A device may receive assessment scores for a candidate associated with an entity and performance data identifying performance metrics and time periods associated with existing members of the entity. The device may process the assessment scores and the performance data, with an attrition model, to identify attrition scores for the candidate and confidences of the attrition scores, and may calculate a final attrition score based on the attrition scores. The device may process the assessment scores and the performance data, with a performance model, to identify performance scores for the candidate and confidences of the performance scores, and may calculate a final performance score based on the performance scores. The device may calculate an overall score based on the final attrition score and the final performance score, and may perform one or more actions based on the overall score.

Abstract: The present disclosure relates to a system, computer readable medium, and method for training workers in occupational skills. The disclosure provides highly automated, artificial intelligence driven, ways of improving human capital through the acquisition, development, and verification of multiple career related proficiencies. Generally, the disclosure provides an integrated digital platform that allows workers to (1) receive training on their existing job skills, (2) verify mastery of the existing job skills through various assessments, and (3) receive recommendations regarding which job skills may be useful to acquire.

Abstract: A device may receive a query from a user device, and may process the query using a machine learning model to determine categories related to the query. The device may send a message, instructing a user to select a category, to the user device to cause the user device to display the message. The device may receive, from the user device, a selection related to the categories, and may call, based on the selection, a module to cause the module to process the query. The device may receive from the module a response to the query, and may send the response to the user device, to cause the user device to display the response. The device may send the query, the selection, and the response to one or more servers for storage, and may retrain the machine learning model based on information stored by the one or more servers.