Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a trajectory for the autonomous vehicle to traverse in order to follow a route to a destination may be generated. A first error value for a boundary of an object, a second error value for a location of the autonomous vehicle, a third error value for a predicted future location of the object may be received. An uncertainty value for the object may be determined by combining the first error value, the second error value, and the third error value. A lateral gap threshold for the object may be determined based on the uncertainty value. The autonomous vehicle may be controlled in an autonomous driving mode based on the lateral gap threshold for the object.

Abstract: The disclosure relates to testing software for operating an autonomous vehicle. For instance, a first simulation may be run. The simulation may be run using the software to control a simulated vehicle and at least one agent. During the running of the first simulation, whether a particular type of interaction between the simulated vehicle and the at least one agent has occurred may be determined. In response to this determination, a second simulation may be run using the log data by replacing the at least one agent with a model agent that simulates a road user capable of responding to actions performed by the simulated vehicle. The second simulation may be used to determine in order to determine whether the software is able to complete the second simulation without the particular type of interaction between a second simulated vehicle and the model agent occurring.

Abstract: The disclosure relate to testing software for operating an autonomous vehicle. For instance, a first simulation may be run. The simulation may be run using the software to control a simulated vehicle and at least one agent. During the running of the first simulation, whether a particular type of interaction between the simulated vehicle and the at least one agent has occurred may be determined. In response to this determination, a second simulation may be run using the log data by replacing the at least one agent with a model agent that simulates a road user capable of responding to actions performed by the simulated vehicle. The second simulation may be used to determine in order to determine whether the software is able to complete the second simulation without the particular type of interaction between a second simulated vehicle and the model agent occurring.

Abstract: A player model for a video game is generated based on inputs received from users who have played past versions of the game. The player model can be used to simulate user actions in a new version of the video game and make predictions about average user session length, average earnings per session, number of games played per day, etc. More than one player model may be generated for a game. Each player model for a game may represent one or more features, such as a user skill level, for a group of users.

Abstract: Systems, device and techniques are disclosed for receiving content based on a subscription to channel by a user. An indication of a user subscription, by a user, may be received. The subscription may be for a channel associated with a channel manager for the channel. An indication of a content to be provided via the channel may be received from the channel manager for the channel. A determination may be made that the content value associated with the content is below an available user subscription value. The content may be automatically provided to the user, based on the determination and the content value may be deducted from the available subscription value.

Abstract: Implementations disclosed herein related to apportioning revenue to a content-creating user if that user's content assisted in the fulfillment of a purchase opportunity. User-generated content may be selected based on criteria, for example, that will likely lead to consummation of a purchase opportunity. Some of the revenue generated from the sale may be sent to the user whose content was associated with the sale. In this way, the user may be encouraged to generate more such content and be rewarded for the advertising the content provided.

Abstract: A player model for a video game is generated based on inputs received from users who have played past versions of the game. The player model can be used to simulate user actions in a new version of the video game and make predictions about average user session length, average earnings per session, number of games played per day, etc. More than one player model may be generated for a game. Each player model for a game may represent one or more features, such as a user skill level, for a group of users.

Abstract: A player model for a video game is generated based on inputs received from users who have played past versions of the game. The player model can be used to simulate user actions in a new version of the video game and make predictions about average user session length, average earnings per session, number of games played per day, etc. More than one player model may be generated for a game. Each player model for a game may represent one or more features, such as a user skill level, for a group of users.

Abstract: A video clip may be automatically generated from a gameplay recording based on an interest metric. The interest metric may be determined from a variety of sources, such as developer provided signals, platform-based signals, and reception signal. A machine learning technique may be applied to each of the signals individually and/or in aggregate (e.g., the interest metric) to ascertain a weighting scheme, for example, for each individual signal or the interest metric to improve the selection of portions of video from a gameplay recording.

Abstract: Systems, device and techniques are disclosed for rating a multiplayer videogame active player based on the retention of one or more qualifying players after their interaction with the active player. An interaction event between an active player and a qualifying player may be detected and a retention value based on the qualifying player returning to the multiplayer videogame may be determined. The active player may be rated based at least on the retention value of the qualifying player.

Abstract: A video clip may be automatically generated from a gameplay recording based on an interest metric. The interest metric may be determined from a variety of sources, such as developer provided signals, platform-based signals, and reception signal. A machine learning technique may be applied to each of the signals individually and/or in aggregate (e.g., the interest metric) to ascertain a weighting scheme, for example, for each individual signal or the interest metric to improve the selection of portions of video from a gameplay recording.

Abstract: Techniques are provided for creating a game-aware compression algorithm for a specific gaming application. A method may include receiving a gaming application and selecting a video compression technique based on the gaming application. A video codec may be created for the gaming application based on the selected video compression technique. The video codec may be provided to a device on which the gaming application is installed. A compressed video of gameplay within the gaming application may be received from the device, and the video of gameplay may have been compressed using the video codec. Additionally, a method may include receiving, from a gaming application provider, a video codec based on a gaming application. A video of gameplay within the gaming application may be recorded. The recorded video of gameplay may be compressed using the video codec and the compressed video of gameplay may be provided to the gaming application provider.

Abstract: Systems, device and techniques are disclosed for receiving content based on a subscription to channel by a user. An indication of a user subscription, by a user, may be received. The subscription may be for a channel associated with a channel manager for the channel. An indication of a content to be provided via the channel may be received from the channel manager for the channel. A determination may be made that the content value associated with the content is below an available user subscription value. The content may be automatically provided to the user, based on the determination and the content value may be deducted from the available subscription value.

Abstract: Systems, device and techniques are disclosed for rating a multiplayer videogame active player based on the retention of one or more qualifying players after their interaction with the active player. An interaction event between an active player and a qualifying player may be detected and a retention value based on the qualifying player returning to the multiplayer videogame may be determined. The active player may be rated based at least on the retention value of the qualifying player.

Abstract: Implementations disclosed herein related to apportioning revenue to a content-creating user if that user's content assisted in the fulfillment of a purchase opportunity. User-generated content may be selected based on criteria, for example, that will likely lead to consummation of a purchase opportunity. Some of the revenue generated from the sale may be sent to the user whose content was associated with the sale. In this way, the user may be encouraged to generate more such content and be rewarded for the advertising the content provided.

Abstract: The present disclosure allows for automatic detection of an entity referenced in a video and presentation of a purchasable item associated with the identified entity to a user viewing the video. A method may include evaluating a video using one or more entity analysis techniques and identifying an entity associated with the video based on the evaluation. Next, one or more purchasable items associated with the entity may be identified. A first purchasable item may be selected from among the one or more purchasable items based on a user history associated with a user and the selected first purchasable item may be presented to the user during playback of the video.

Abstract: A video clip may be automatically generated from a gameplay recording based on an interest metric. The interest metric may be determined from a variety of sources, such as developer provided signals, platform-based signals, and reception signal. A machine learning technique may be applied to each of the signals individually and/or in aggregate (e.g., the interest metric) to ascertain a weighting scheme, for example, for each individual signal or the interest metric to improve the selection of portions of video from a gameplay recording.

Abstract: A player model for a video game is generated based on inputs received from users who have played past versions of the game. The player model can be used to simulate user actions in a new version of the video game and make predictions about average user session length, average earnings per session, number of games played per day, etc. More than one player model may be generated for a game. Each player model for a game may represent one or more features, such as a user skill level, for a group of users.