Abstract: In various examples, an interactive agent platform that hosts development and/or deployment of an interactive agent may use a GUI service to execute interactive visual content actions and generate corresponding GUIs. An interaction modeling API may use an interaction categorization schema that defines a standardized format for specifying (e.g., visual information scene, visual choice, or visual form actions) events that instruct an overlay of visual content supplementing a conversation with the interactive agent. The GUI service may translate a standardized representation of a GUI specified by an interaction modeling API event into a modular GUI configuration defining blocks of visual content specified by the event, and may use these blocks to populate a (e.g., template or shell) visual layout for a GUI overlay layout. As such, a visual layout representing a GUI specified by an interaction modeling API event may be generated and presented (e.g., via a user interface server).

Abstract: Embodiments of the present disclosure relate to workload-based dynamic throttling of video processing functions. Systems and methods are disclosed that dynamically throttle video processing and/or streaming based on a workload. Live video is captured from one or more sources (e.g., cameras) and stored. The video is then provided to a video processing engine and a video streaming engine. The video processing engine may perform one or more operations such as object detection, object tracking, and object classification to produce characterization data (e.g., bounding boxes, object trajectories, alerts, object labels, object counts, boundary crossings, intersection highlighting, etc.). System resource usage and performance of the video processing and streaming are monitored to produce workload data (e.g., metrics). Based on the policies and the workload data, the video streaming and/or processing is dynamically reconfigured by adjusting parameters provided to the video streaming and processing engines.

Abstract: Embodiments of the present disclosure relate to workload-based dynamic throttling of video processing functions. Systems and methods are disclosed that dynamically throttle video processing and/or streaming based on a workload. Live video is captured from one or more sources (e.g., cameras) and stored. The video is then provided to a video processing engine and a video streaming engine. The video processing engine may perform one or more operations such as object detection, object tracking, and object classification to produce characterization data (e.g., bounding boxes, object trajectories, alerts, object labels, object counts, boundary crossings, intersection highlighting, etc.). System resource usage and performance of the video processing and streaming are monitored to produce workload data (e.g., metrics). Based on the policies and the workload data, the video streaming and/or processing is dynamically reconfigured by adjusting parameters provided to the video streaming and processing engines.