Abstract: Example embodiments of the present disclosure provide for an example method. The example method includes generating an initial user interface including a content assistant component. The example method include obtaining user input data. The example method includes processing, by a machine learned model interfacing with the content assistant component, the data indicative of the input received from the user. The method includes obtaining output data, from the machine learned model interfacing with the content assistant component, indicative of one or more content item components. The method includes transmitting data which causes the content item components to be provided for display via an updated user interface. The method includes obtaining data indicative of user selection of approval of the content item components. The method includes generating, in response to obtaining the data indicative of the user selection of the approval of the content item components, content items.

Abstract: Example embodiments of the present disclosure provide for an example method. The example method includes generating an initial user interface including a content assistant component. The example method include obtaining user input data. The example method includes processing, by a machine learned model interfacing with the content assistant component, the data indicative of the input received from the user. The method includes obtaining output data, from the machine learned model interfacing with the content assistant component, indicative of one or more content item components. The method includes transmitting data which causes the content item components to be provided for display via an updated user interface. The method includes obtaining data indicative of user selection of approval of the content item components. The method includes generating, in response to obtaining the data indicative of the user selection of the approval of the content item components, content items.

Abstract: Example embodiments of the present disclosure provide for an example method that includes obtaining via a conversational campaign assistant interface, by a custom language model, natural language input. The method includes generating, by the custom language model, an output comprising a predicted user intent. The method includes determining actions to perform and determining a natural language response. The method includes transmitting, to an action component, the action data structure comprising executable instructions that cause the action component to automatically perform operations associated with completing the action. The method includes transmitting to the conversation campaign assistant interface, the response data structure comprising the natural language response to be provided for display to a user via the conversational campaign assistant interface.

Abstract: Systems and methods are disclosed for dynamically analyzing and providing the quality of one or more content items at the time, or substantially close to the time, they are received by a data processing system. The systems and methods described herein can maintain and update the quality score for improving previously created content items after they have been published. The one or more content items can include one or more assets (e.g., one or more headlines, one or more descriptions, images, video, etc.). The data processing system can use numerical analysis methods to determine an overall quality (e.g., estimated clicks) of the content items received by the data processing system using a trained model.

Abstract: Systems and methods are disclosed for dynamically analyzing and providing the quality of one or more content items at the time, or substantially close to the time, they are received by a data processing system. The systems and methods described herein can maintain and update the quality score for improving previously created content items after they have been published. The one or more content items can include one or more assets (e.g., one or more headlines, one or more descriptions, images, video, etc.). The data processing system can use numerical analysis methods to determine an overall quality (e.g., estimated clicks) of the content items received by the data processing system using a trained model.