A technique that can be implemented by the digital asset repository, and includes the steps of (1) receiving, from a first application executing on the first computing device, a request to access information associated with a second application managed by the digital asset repository, wherein the request: (i) is transmitted in response to a selection of a user interface that is displayed by the first application and that relates to the second application, and (ii) includes a set of parameters that is provided by a remote server and that specifies at least one utilization requirement pertaining to the second application; (2) receiving, from the second application, an indication that activity associated with the second application has been performed; (3) determining, based on the indication, that the at least one utilization requirement is satisfied; and (4) providing the set of parameters to a metrics manager executing on a second computing device.

Methods, apparatus, systems and articles of manufacture are disclosed to determine component lifts and synergy from overlapping stimuli. An example disclosed apparatus to allocate advertising campaign resources includes a vehicle segregator to segregate impression counts of an advertisement campaign into vehicle types and segregate measured lift values associated with the impression counts into respective ones of the vehicle types, the segregated measured lift values corresponding to respondents that viewed an advertisement corresponding to one of the respective ones of the vehicle types. The example apparatus further includes a correlation engine to establish correlations between the measured lift values and component lift values, the correlations based on a weighted average of the component lift values and segregated impression counts, the component lift values corresponding to respondents that viewed an advertisement corresponding to one of the respective ones of the vehicle types, a lift calculator to determine the component lift values based on the correlations and a campaign selector to modify computing resource allocation to at least one of the vehicle types of the advertising campaign based on a comparison of the determined component lift values.

A method of selecting an advertisement (ad) network for providing promotional content to be presented in an ad spot, comprising: monitoring the performance of response to ad requests for embedding ads in ad spots for each ad networks; assigning a performance score to each ad networks based on the monitoring; constructing a ranked set of data values of the ad networks for a bidding process according to the performance score of each ad network and bid responses received by each ad network; and selecting an ad network according to the ranked set of data values.

An artificial intelligence and machine learning infrastructure system, including: one or more storage systems comprising, respectively, one or more storage devices; and one or more graphical processing units, wherein the graphical processing units are configured to communicate with the one or more storage systems over a communication fabric; where the one or more storage systems, the one or more graphical processing units, and the communication fabric are implemented within a single chassis.

An automated advertisement selection system includes a computing platform having a hardware processor and a system memory storing a software code including a trained predictive model and a scoring module. The hardware processor executes the software code to receive an advertising query, the advertising query including a multiple parameters describing a target consumer group, and to identify, using the trained predictive model, candidate advertisements for the target consumer group based on the multiple parameters. The hardware processor also executes the software code to determine, using the scoring module, desirability scores for each one of the plurality of candidate advertisements, each of the desirability scores corresponding to a likelihood of each respective one of the plurality of candidate advertisements enticing the target consumer group, and to select one of the plurality of candidate advertisements based on the desirability scores for distribution to the target consumer group.

A method includes receiving, at a media device, overlay data associated with media content. The overlay data includes information indicating a time and a position at which a particular object is represented within the media content, and the overlay data includes information associating the particular object with supplemental information. The method further includes, during playback of the media content, receiving user input at the media device, and, responsive to the user input, generating an overlay display based on the overlay data, where the overlay display causes the particular object to be highlighted in a display of the media content.

An online system evaluates the quality of a content publisher displaying sponsored content items. To determine a likelihood of conversion actions associated with the sponsored content items, the online system uses information about users and their interactions with sponsored content items featured within the content publisher against interactions with sponsored content items featured within a benchmark system (e.g., online system). By determining a ratio of these interactions, the online system can determine a likelihood of conversion actions for the content publisher. The online system uses this likelihood of conversions to determine a publisher quality score that it uses to normalize third party value contributions toward placing sponsored content items on the content publisher. Thus, third party systems no longer need to be concerned about the intrinsic value of a given content publisher as third party value contributions are normalized based on the content publisher's conversion rates.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content items. In one aspect, a method includes receiving user interaction data specifying user interactions with a publisher resource. A heat map specifying levels of user interaction with various portions of the publisher resource is created. Content item slot performance information specifying one or more performance measures for content items presented in various candidate content item slot locations are identified. One of the candidate content item slot locations is selected based on the heat map and the one or more performance measures. Data that cause presentation of suggestion information that identify the one candidate content item slot location as a suggested content item slot location are generated and output.

An artificial intelligence and machine learning infrastructure system, including: one or more storage systems comprising, respectively, one or more storage devices; and one or more graphical processing units, wherein the graphical processing units are configured to communicate with the one or more storage systems over a communication fabric; where the one or more storage systems, the one or more graphical processing units, and the communication fabric are implemented within a single chassis.

The present disclosure provides enhanced techniques for dynamically monitoring and controlling user experiences on a website based on user activity of associated software applications. A system can offer a number of web pages to different user groups in an experiment. Each web page can describe respective configurations of an application, and each user group may receive a particular web page based on one or more criteria. An application installer and a resource identifier are transmitted to the client device in response to an installation request. A configuration file is also delivered to the client device based on the resource identifier. The configuration file causes the installation of a particular application configuration on the client device. The application configuration sends telemetry data indicating user retention data to a service. A usage report summarizing the telemetry data is generated and utilized to adjust the criteria for controlling one or more experiments.