Abstract: Methods and systems are described for efficient communication of content. A user device may request content from a content device. The content device may determine a browsing context of the user device. A user model based on machine learning may be determined based on the browsing context. The user model may be used to predicted additional content that might be requested by the user device. The additional content or a portion thereof may be sent to the user device in parallel with the originally requested content. As the user device rejects, accepts, or further requests the additional content, the user model may be further refined.

Abstract: Systems, apparatuses, and methods are described for generating tokens for user devices to request content items from one or more content delivery networks via networks provided by a network service provider. The tokens may be generated based on rules provided by the network service provider and may indicate whether the content delivery networks have permission to send targeted content items to the user device. Tokens provided to a user device may prevent repeated delivery of the same content item to the user device.

Abstract: Methods and systems are described for efficient communication of content. A user device may request content from a content device. The content device may determine a browsing context of the user device. A user model based on machine learning may be determined based on the browsing context. The user model may be used to predicted additional content that might be requested by the user device. The additional content or a portion thereof may be sent to the user device in parallel with the originally requested content. As the user device rejects, accepts, or further requests the additional content, the user model may be further refined.

Abstract: Methods and systems are described for efficient communication of content. A user device may request content from a content device. The content device may determine a browsing context of the user device. A user model based on machine learning may be determined based on the browsing context. The user model may be used to predicted additional content that might be requested by the user device. The additional content or a portion thereof may be sent to the user device in parallel with the originally requested content. As the user device rejects, accepts, or further requests the additional content, the user model may be further refined.

Abstract: Methods and systems are described for efficient communication of content. A user device may request content from a content device. The content device may determine a browsing context of the user device. A user model based on machine learning may be determined based on the browsing context. The user model may be used to predicted additional content that might be requested by the user device. The additional content or a portion thereof may be sent to the user device in parallel with the originally requested content. As the user device rejects, accepts, or further requests the additional content, the user model may be further refined.

Abstract: Systems, apparatuses, and methods are described for causing output of content via an output device such as a casting device. The output device may be associated with a device identity token indicating an identity for the output device. Another computing device may obtain, based on the device identity token, an output authorization token indicating a content item and the identity of the output device. The output device may, based on the output authorization token, obtain authorization data for output of the content item.

Abstract: Methods and systems are described for efficient communication of content. A user device may request content from a content device. The content device may determine a browsing context of the user device. A user model based on machine learning may be determined based on the browsing context. The user model may be used to predicted additional content that might be requested by the user device. The additional content or a portion thereof may be sent to the user device in parallel with the originally requested content. As the user device rejects, accepts, or further requests the additional content, the user model may be further refined.