Abstract: A persona system determines a player persona for a player of a gaming system based on gameplay information for the user and, for example, performs dynamic content generation or additional product recommendations based on the player persona. The persona system may receive a request for content based on a persona of a player and receive gameplay data associated with gameplay of the player in a plurality of games. The persona system may then generate a player persona of the player based on the gameplay data associated with the gameplay of the player in the plurality of games, determine persona based content based at least in part on a portion of the player persona, and output the persona based content in response to the request.

Abstract: A persona system determines a player persona for a player of a gaming system based on gameplay information for the user and, for example, performs dynamic content generation or additional product recommendations based on the player persona. The persona system may receive a request for content based on a persona of a player and receive gameplay data associated with gameplay of the player in a plurality of games. The persona system may then generate a player persona of the player based on the gameplay data associated with the gameplay of the player in the plurality of games, determine persona based content based at least in part on a portion of the player persona, and output the persona based content in response to the request.

Abstract: Some embodiments herein disclose intelligent priority evaluators configured to perform a method that prioritizes tasks submitted by various users, even if the tasks are similarly classified. The scheduling system can collect, calculate, and use various criteria to determine a reward score in order to prioritize one task over another, such as for dynamic scheduling purposes. This can be performed in addition to or as a replacement for receiving user designations of priority.

Abstract: A computer-implemented method is provided of allowing a user to automatically transform domain knowledge into a machine learning model to be used in real-time operation of video games. The method comprises providing a user interface which allows a user to define domain knowledge relating to a video game by specifying one or more labeling functions; transforming the labeling functions into executable code; labeling raw data relating to the video game using the executable code to obtain labeled data; and applying an automated machine learning module to the labeled data to obtain a machine learning model.

Abstract: Various aspects of the subject technology relate to systems, methods, and machine-readable media for granting access to a game. The method includes receiving a request to access the game. The method also includes causing to display a set of challenge options representing challenges of varying difficulty levels for a user to select. The method also includes receiving a selection of a challenge option from a user device. The method also includes causing to present a challenge to the user. The method also includes receiving challenge data from the user including interactions with and results of the challenge. The method also includes determining whether the user passed the challenge based on the challenge data. The method also includes executing or enabling execution of the game upon determining that the user passed the challenge. The method also includes providing the user rewards associated with the game for passing the challenge.

Abstract: A persona system determines a player persona for a player of a gaming system based on gameplay information for the user and, for example, performs dynamic content generation or additional product recommendations based on the player persona. The persona system may receive a request for content based on a persona of a player and receive gameplay data associated with gameplay of the player in a plurality of games. The persona system may then generate a player persona of the player based on the gameplay data associated with the gameplay of the player in the plurality of games, determine persona based content based at least in part on a portion of the player persona, and output the persona based content in response to the request.

Abstract: A persona system determines a player persona for a player of a gaming system based on gameplay information for the user and, for example, performs dynamic content generation or additional product recommendations based on the player persona. The persona system may receive a request for content based on a persona of a player and receive gameplay data associated with gameplay of the player in a plurality of games. The persona system may then generate a player persona of the player based on the gameplay data associated with the gameplay of the player in the plurality of games, determine persona based content based at least in part on a portion of the player persona, and output the persona based content in response to the request.

Abstract: A persona system determines a player persona for a player of a gaming system based on gameplay information for the user and, for example, performs dynamic content generation or additional product recommendations based on the player persona. The persona system may receive a request for content based on a persona of a player and receive gameplay data associated with gameplay of the player in a plurality of games. The persona system may then generate a player persona of the player based on the gameplay data associated with the gameplay of the player in the plurality of games, determine persona based content based at least in part on a portion of the player persona, and output the persona based content in response to the request.

Abstract: A computer-implemented method for providing video game content is provided. The method comprises monitoring a request rate of requests to provide video game content; and in response to the request rate exceeding a threshold request rate: initialising at least one instance of a first machine learning model, wherein the first machine learning model is configured to provide an output which is approximate to the output of a second machine learning model from which the first machine learning model is derived, the first machine learning model being produced by a model derivation process to have a faster response time compared to the second machine learning model; and providing video game content, wherein providing the video game content comprises generating an output responsive to the specified input using the at least one instance of the first machine learning model.

Abstract: A computer-implemented method is provided of allowing a user to automatically transform domain knowledge into a machine learning model to be used in real-time operation of video games. The method comprises providing a user interface which allows a user to define domain knowledge relating to a video game by specifying one or more labeling functions; transforming the labeling functions into executable code; labeling raw data relating to the video game using the executable code to obtain labeled data; and applying an automated machine learning module to the labeled data to obtain a machine learning model.

Abstract: A computer-implemented method for providing video game content is provided. The method comprises monitoring a request rate of requests to provide video game content; and in response to the request rate exceeding a threshold request rate: initialising at least one instance of a first machine learning model, wherein the first machine learning model is configured to provide an output which is approximate to the output of a second machine learning model from which the first machine learning model is derived, the first machine learning model being produced by a model derivation process to have a faster response time compared to the second machine learning model; and providing video game content, wherein providing the video game content comprises generating an output responsive to the specified input using the at least one instance of the first machine learning model.

Abstract: A computer-implemented method for providing video game content is provided. The method comprises maintaining a current machine learning model for each of a plurality of machine learning model branches; receiving a request to provide video game content responsive to specified input; in response to receiving the request, identifying a selected one of the machine learning model branches, wherein the machine learning model branch is selected based on an evaluation of the current machine learning model for each branch; and providing video game content responsive to the request, wherein providing the video game content comprises generating an output responsive to the specified input with the current machine learning model for the selected branch.

Abstract: Various aspects of the subject technology relate to systems, methods, and machine-readable media for granting access to a game. The method includes receiving a request to access the game. The method also includes causing to display a set of challenge options representing challenges of varying difficulty levels for a user to select. The method also includes receiving a selection of a challenge option from a user device. The method also includes causing to present a challenge to the user. The method also includes receiving challenge data from the user including interactions with and results of the challenge. The method also includes determining whether the user passed the challenge based on the challenge data. The method also includes executing or enabling execution of the game upon determining that the user passed the challenge. The method also includes providing the user rewards associated with the game for passing the challenge.