Systems and methods for adjusting a facility configuration based on detected conditions are disclosed. An example system may include an energy and compute facility having a compute resource, and an energy source or an energy utilization requirement. The system may also include a controller having a facility description circuit to interpret detected conditions, and a facility configuration circuit to operate an adaptive learning system. The adaptive learning system is configured to adjust a facility configuration based on the detected conditions, wherein adjusting the facility configuration includes adjusting a utilization of the compute resource and at least one additional facility resource.

Systems and methods for adjusting a facility configuration based on a set of parameters from a digital twin are disclosed. An example system may include an energy and compute facility having a compute task or resource, and an energy source utilization requirement. The system may include a controller having a facility model circuit to operate a digital twin for the facility, a facility description circuit to interpret a set of parameters from the digital twin, and a facility configuration circuit to operate an adaptive learning system. The adaptive learning system is configured to adjust a facility configuration based on the set of parameters from the digital twin and perform a purchase or sale transaction on an energy credit spot market or an energy credit forward market.

Systems and methods for adaptively improving an energy delivery are disclosed. An example system includes a machine having an associated regenerative energy facility, the machine having a requirement for a compute, networking, or energy consumption task. The example system includes a controller having an energy requirement circuit to determine an amount of energy for the machine to service the task in response to the requirement for the task. The controller also includes an energy distribution circuit to adaptively improve an energy delivery, of energy produced by the associated regenerative energy facility, between the tasks.

A campaign management system manages campaign datasets, wherein a campaign dataset corresponds to selections and instructions for executing an online campaign. A campaign dataset might be created by a human or a machine, or multiple humans and computers in a crowd-sourcing approach. Campaign datasets can be processed to determine an expected quality metric, a post-run quality metric, and a confidence level. A campaign comparator can compare campaign datasets to identify similar campaign datasets so that an expected quality metric, a post-run quality metric, and/or a confidence level from one campaign dataset can be imputed to another campaign dataset.

A computer-implemented method of generating, from an array of topic records, an output array of keywords for use in targeting online advertisements related to topics represented by the array of topic records, includes obtaining the array of topic records in computer-readable form, determining a relevancy value for words and topics, classifying the topic vectors in the plurality of topic vectors into a high-volume class or a low-volume class, generating and storing an array of seed keywords derived by sampling from an embedded space, ranking the seed keywords to form an array of ranked keywords, updating the array of ranked keywords based on keyword cost-per-click data, iterating the ranking and updating at least once, and evaluating an optimization improvement value for an iteration.

A transaction-enabling system including a controller is provided. The controller is configured to: access a distributed ledger comprising an aggregated data set; interpret an access request for the aggregated data set; and in response to the access request, provide a provable access to the aggregated data set. The provable access includes at least one of which parties have accessed the aggregated data set and how many parties have accessed the aggregated data set, the distributed ledger includes a block chain, and the aggregated data set includes one of a trade secret and proprietary information.

A method for enhanced digital content presentation is provided that includes assigning, to each member of members of a social network of a user, a respective knowledge score, the knowledge score being representative of accuracy in the member predicting positive impressions of the user. The members of the social network are surveyed for an indication of which one or more options for digital content are expected to have a positive impression on the user. Based on the surveying, selected digital content based on the one or more options that are expected to have a positive impression on the user, as indicated by the surveying, is selected. The selected digital content is presented to the user. An indication of whether the selected digital content had a positive impression on the user is received from the user.

A method and system receive consumer media consumption data and dynamically prioritize the allocation of marketing resources amongst a variety of media intellectual property (IP) assets and for a variety of media IP asset managers and owners to run automated targeted marketing campaigns. The system identifies patterns in consumer media consumption using a statistical model which detects media IP assets demonstrating a high likelihood of realizing an efficient marketing opportunity. The efficiency of a marketing opportunity is evaluated using a statistical model based on the identification of customers who are most likely to increase the frequency with which they stream the assets after being exposed to them via a marketing action in addition to the projected costs of reaching this audience. The system automatically constructs a marketing campaign. The campaign is presented to the asset manager/owner in a graphical user interface (GUI) which enables the option to purchase and execute the marketing actions. Conditional on the execution of the marketing actions, the system performs an analysis on the efficacy of the marketing actions.

A system and method identify and provide content using identification entries. Product identification information for a product listing is received, and a matching identification entry is selected from a set of identification entries using the product identification information. The matching identification entry is assigned to the product listing for use in selecting content regarding the product listing for presentation.

An online system optimizes for longer attribution window conversions with an additive decomposition model by predicting the probability that a predefined action happens given an impression/click. The online system receives a content item from a content provider for display to a target user, and predicts a probability that a target user will convert given an interaction with the content item by the target user. The online system computes, by a first trained model, a short-term conversion probability of a conversion event happening within a first conversion window after the interaction. The online system computes, by a second trained model, a long-term conversion probability of the a conversion event happening within a second conversion window after the interaction, the second conversion window being longer than the first conversion window. The online system computes the conversion probability given the interaction based on the short-term conversion probability and the long-term conversion probability.