Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.

Abstract: A video reenactment system and method analyze a video clip that a video game player wishes to reenact and maps objects and actions within the video clip to virtual objects and virtual actions within the video game. A reenactment script indicating a sequence of virtual objects and virtual actions as mapped to objects and actions in the video clip is generated using a video translation model and stored for use in reenacting the video clip. The reenactment script can be used within the video game to reenact the objects and actions of the video clip. The reenactment of the video clip may be interactive, where a player may assume control within the reenactment and when the player relinquishes control, the reenactment will continue at an appropriate part of the sequence of actions by skipping actions corresponding to the ones played by the player.

Abstract: Various aspects of the subject technology relate to systems, methods, and machine-readable media for user matchmaking. The method includes training a quality model and an embedding model based on historical data and user control options. The method also includes receiving user control options and matchmaking requests from users. The method also includes embedding, through the embedding model, user data regarding the users into an embedded space based on the received user control options and the matchmaking requests. The method also includes determining, based on the embedded user data, that a distance between two users satisfies a distance threshold. The method also includes matching the two users when the determined distance satisfies the distance threshold.

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: 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: 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: 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 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: A system and method for providing live gameplay updates receives a modification for a videogame, the modification affecting a gameplay aspect of the videogame during execution of the videogame. The system and method determine a target group for deploying the modification. The target group includes first one or more live instances of the videogame. The system and method deploy the modification to the target group and receive gameplay data associated with the gameplay aspect from the target group. The system and method deploy the modification to second one or more live instances of the videogame based at least in part on an analysis of the received gameplay data.

Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.

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: 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: Various aspects of the subject technology relate to systems, methods, and machine-readable media for game state synchronization. The method includes recording game state changes in a distributed queue. The method also includes updating a global state based on the recorded game state changes in the distributed queue. The method also includes recording a snapshot of the global state, the snapshot comprising an offset from a latest game state change recorded in the distributed queue. The method also includes updating at least one in-sync service of a plurality of in-sync services based on the game state changes and the snapshot of the global state.

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: 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 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: 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: 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.