Abstract: Embodiments of the systems and methods described herein provide a terrain generation and population system that can determine terrain population rules for terrain population objects and features when placing objects and features in a three dimensional virtual space. As such, the terrain generation and population system can generate realistic terrain for use in game. The terrain generation and population system can receive an image, such as a satellite image, and utilize artificial intelligence to perform image segmentation at the pixel level to segment features and/or objects in the image. The game terrain system can automatically detect and apply feature and object masks based on the identified features and/or objects from the image segmentation. The game terrain system can place the features and/or objects in corresponding masks in the three dimensional space according to the application of terrain population rules.

Abstract: Embodiments of the systems and methods disclosed herein provide a request distribution system in which a request for resources may be executed by a plurality of workers. Upon receiving a request for resources from a user computing system, the request distribution system may select a subset of workers from the plurality of workers to execute the request within a time limit. Once the workers generate a plurality of outputs, each output associated with a quality level, the request distribution system may transmit the output associated with the highest quality level to the user computing system.

Abstract: Systems and methods are disclosed for training a machine learning model to control an in-game character or other entity in a video game in a manner that aims to imitate how a particular player would control the character or entity. A generic behavior model that is trained without respect to the particular player may be obtained and then customized based on observed gameplay of the particular player. The customization training process may include freezing at least a subset of layers or levels in the generic model, then generating one or more additional layers or levels that are trained using gameplay data for the particular player.

Abstract: Sequence predictors may be used to predict one or more entries in a musical sequence. The predicted entries in the musical sequence enable a virtual musician to continue playing a musical score based on the predicted entries when the occurrence of latency causes a first computing system hosting a first virtual musician to not receive entries or timing information for entries being performed in the musical sequence by a second computing system hosting a second virtual musician. The sequence predictors may be generated using a machine learning model generation system that uses historical performances of musical scores to generate the sequence predictor. Alternatively, or in addition, earlier portions of a musical score may be used to train the model generation system to obtain a prediction model that can predict later portions of the musical score.

Abstract: Sequence predictors may be used to predict one or more entries in a musical sequence. The predicted entries in the musical sequence enable a virtual musician to continue playing a musical score based on the predicted entries when the occurrence of latency causes a first computing system hosting a first virtual musician to not receive entries or timing information for entries being performed in the musical sequence by a second computing system hosting a second virtual musician. The sequence predictors may be generated using a machine learning model generation system that uses historical performances of musical scores to generate the sequence predictor. Alternatively, or in addition, earlier portions of a musical score may be used to train the model generation system to obtain a prediction model that can predict later portions of the musical score.

Abstract: Embodiments of the systems and methods described herein provide a virtual object aging system. The virtual object aging system can utilize artificial intelligence to modify virtual objects within a video game to age and/or deteriorate for a certain time period. The virtual object aging system can be used to determine erosion, melting ice, and/or other environmental effects on virtual objects within the game. The virtual object aging system can apply aging, rust, weathering, and/or other effects that cause persistent change to object meshes and textures.

Abstract: Systems and methods are provided for real-time audio generation for electronic games based on personalized music preferences. An example method includes requesting listening history information from one or more music streaming platforms, the listening history information indicating, at least, music playlists to which a user created or is subscribed. A style preference associated with the user is determined based on the listening history information. A musical cue associated with an electronic game is accessed, with the musical being associated with music to be output by the electronic game based on a game state of the electronic game. Personalized music is generated utilizing one or more machine learning models based on the musical cue and the style preference, wherein the system is configured to provide the personalized music for inclusion in the electronic game.

Abstract: Systems and methods are provided for real-time audio generation for electronic games based on personalized music preferences. An example method includes requesting listening history information from one or more music streaming platforms, the listening history information indicating, at least, music playlists to which a user created or is subscribed. A style preference associated with the user is determined based on the listening history information. A musical cue associated with an electronic game is accessed, with the musical being associated with music to be output by the electronic game based on a game state of the electronic game. Personalized music is generated utilizing one or more machine learning models based on the musical cue and the style preference, wherein the system is configured to provide the personalized music for inclusion in the electronic game.

Abstract: A video game includes a single player mode where completion of storyline objectives advances the single player storyline. The video game also includes a multiplayer mode where a plurality of players can play on an instance of a multiplayer map. Storyline objectives from the single player mode are selected and made available for completion to players in the multiplayer mode, and the single player storylines can be advanced by players completing respective storyline objectives while playing in the multiplayer mode. Combinations of storyline objectives are selected from pending storyline objectives for players connecting to a multiplayer game for compatibility with multiplayer maps. Constraints can be used to determine compatibility.

Abstract: Systems and methods for generating a customized virtual animal character are disclosed. A system may obtain video data or other media depicting a real animal, and then may provide the obtained media to one or more machine learning models configured to learn visual appearance and behavior information regarding the particular animal depicted in the video or other media. The system may then generate a custom visual appearance model and a custom behavior model corresponding to the real animal, which may subsequently be used to render, within a virtual environment of a video game, a virtual animal character that resembles the real animal in appearance and in-game behavior.

Abstract: Systems and methods are provided for personalized real-time audio generation based on user physiological response. An example method includes obtaining hearing information associated with a user's hearing capabilities, the hearing information indicating one or more constraints on the user's hearing, and the hearing information being determined based on one or more hearing tests performed by the user; requesting listening history information from one or more music streaming platforms, the listening history information indicating, at least, music playlists to which a user created or is subscribed; determining, based on the listening history information, a style preference associated with the user; generating, utilizing one or more machine learning models, personalized music based on the hearing information and the style preference, wherein the personalized music comports with the constraints, and wherein the system is configured to provide the personalized music for output via a user device of the user.

Abstract: Systems described herein may automatically and dynamically adjust the amount and type of computing resources usable to execute, process, or perform various tasks associated with a video game. Using one or more machine learning algorithms, a prediction model can be generated that uses the historical and/or current user interaction data obtained by monitoring the users playing the video game. Based on the historical and/or current user interaction data, future user interactions likely to be performed in the future can be predicted. Using the predictions of the users' future interactions, the amount and type of computing resources maintained in the systems can be adjusted such that a proper balance between reducing the consumption of computing resources and reducing the latency experienced by the users of the video game is achieved and maintained.

Abstract: Systems and methods for generating a customized virtual character are disclosed. A system may obtain video data or other media depicting a real person, and then may provide the obtained media to one or more machine learning models configured to learn visual appearance and behavior information regarding the particular person depicted in the video or other media. The system may then generate a custom visual appearance model and a custom behavior model corresponding to the real person, which may subsequently be used to render, within a virtual environment of a video game, a virtual character that resembles the real person in appearance and in-game behavior.

Abstract: Embodiments of the systems and methods described herein provide a virtual object aging system. The virtual object aging system can utilize artificial intelligence to modify virtual objects within a video game to age and/or deteriorate for a certain time period. The virtual object aging system can be used to determine erosion, melting ice, and/or other environmental effects on virtual objects within the game. The virtual object aging system can apply aging, rust, weathering, and/or other effects that cause persistent change to object meshes and textures.

Abstract: Systems and methods are provided for personalized real-time audio generation based on user physiological response. An example method includes obtaining hearing information associated with a user's hearing capabilities, the hearing information indicating one or more constraints on the user's hearing, and the hearing information being determined based on one or more hearing tests performed by the user; requesting listening history information from one or more music streaming platforms, the listening history information indicating, at least, music playlists to which a user created or is subscribed; determining, based on the listening history information, a style preference associated with the user; generating, utilizing one or more machine learning models, personalized music based on the hearing information and the style preference, wherein the personalized music comports with the constraints, and wherein the system is configured to provide the personalized music for output via a user device of the user.

Abstract: Systems and methods are provided for enhanced real-time audio generation via a virtualized orchestra. An example method includes receiving, from a user device, a request to generate output associated with a musical score. Actions associated with virtual musicians with respect to respective instruments are simulated based on one or more machine learning models, with the simulated actions being associated with a virtual musician and indicative of an expected playing style during performance of the musical score. Output audio to be provided to the user device is generated, with the output audio being generated based on the simulated actions.

Abstract: Systems and methods are provided for enhanced real-time audio generation via a virtualized orchestra. An example method includes receiving, from a user device, a request to generate output associated with a musical score. Actions associated with virtual musicians with respect to respective instruments are simulated based on one or more machine learning models, with the simulated actions being associated with a virtual musician and indicative of an expected playing style during performance of the musical score. Output audio to be provided to the user device is generated, with the output audio being generated based on the simulated actions.

Abstract: Systems and methods are provided for enhancements for musical composition applications. An example method includes receiving information identifying initiation of a music composition application, the music composition application being executed via a user device of a user, with the received information indicating a genre associated with a musical score being created via the music composition application. One or more constraints associated with the genre are determined, with the constraints indicating one or more features learned based on analyzing music associated with the genre. Musical elements specified by the user are received via the music composition application. Musical score updates are determined based on the musical elements and genre. The determined musical score updates are provided to the user device.

Abstract: Sequence predictors may be used to predict one or more entries in a musical sequence. The predicted entries in the musical sequence enable a virtual musician to continue playing a musical score based on the predicted entries when the occurrence of latency causes a first computing system hosting a first virtual musician to not receive entries or timing information for entries being performed in the musical sequence by a second computing system hosting a second virtual musician. The sequence predictors may be generated using a machine learning model generation system that uses historical performances of musical scores to generate the sequence predictor. Alternatively, or in addition, earlier portions of a musical score may be used to train the model generation system to obtain a prediction model that can predict later portions of the musical score.

Abstract: Embodiments of the systems and methods described herein provide game terrain generation system that can generate height field data from a sketch of graphical inputs from a user via a graphical user interface. The game terrain generation system can use a model, such as a trained neural network, to apply macro and micro topological features on top of the height field data to generate game terrain data. The game terrain generation system can identify boundaries between different styles of terrain and generate transitions between the styles to create a more realistic terrain boundary.