Abstract: Various methods and processes, apparatuses/systems, and media for automatically generating robust data driven decisions based on attendance data are disclosed. A processor receives, via a user interface, attendance data and population data. The population data indicates which team a given employee belongs to. The processor implements an AI system that includes an AI module and an AI planner; and causes the AI system to automatically calculate the plurality of teams' attendance on any given date which is present in the attendance data; receives input data from a user indicating whether the user wants to invoke a first process or a second process; invokes the AI module, in response to receiving the input data, that automatically generates a solution according to an AI model and configurable constraints; and causes the AI planner to automatically generate robust data driven decisions report in accordance with the solution.

Abstract: Systems and methods for matching a client with a stylist using a machine-learning model. Determining, based on the requested service, one or more candidate stylists with a minimal wait time, maximum compatibility, and maximum revenue by determining, using the machine-learning model, an estimated completion time of respective services based on historical times of completing the respective services that are calendared for respective candidate stylists. Determining an estimate completion time of the requested service based on the machine-learning model, wherein the machine-learning model uses a neural network model to make predictions about the estimate completion time based on client features and service expertise of respective candidate stylists.

Abstract: Described are techniques for establishing a multi-cloud environment. A multi-cloud environment is modeled using a game theoretic model. Furthermore, a probability distribution over information technology costs for both the cloud buyers and cloud providers is created. Additionally, an estimate of the expected utility (measure of how much benefit a party receives or is expected to receive) for each party in a single-cloud environment is calculated. A mechanism (centralized broker) for the multi-cloud environment is then created that collects payments from the cloud buyers and makes payments to the cloud providers using the expected utility for each party in the single-cloud environment and the probability distribution over information technology costs for both the cloud buyers and the cloud providers as parameters for the game theoretic model, such as by applying an automated mechanism design approach to the game theoretic model.

Abstract: A method and a system are disclosed for providing an Artificial Intelligence (AI) based recruitment management, the method comprising. An AI-based tracker module having a graphical user interface is configured for receiving a plurality of job applications from a plurality of candidates via respective user devices. The tracker is configured to predict the hiring probability of a candidate based on: a compensation viability score, a speed score, a skill sets of the candidate. The tracker is further configured to predict time to fill a position by the candidate, based on one or more parameters including location, salary, and skill set.

Abstract: A system and method for detecting changes in an agricultural field uses a time series of target images of the agricultural field in which a vegetation index value is calculated for each target image. A target trend line is calculated from the time series of the vegetation index values. A time series of candidate images of one or more candidate fields having one or more attributes that correspond to one or more attributes of the agricultural field is also acquired in which an expected trend line can be determined from calculated vegetation index values representative of respective candidate images. An alert is generated in response to a deviation of the target trend line from the expected trend line that meets alert criteria.

Abstract: Features are disclosed for identifying an operation for an object of a pool of objects to improve a pool characteristic of the object pool. For example, a system can identify an operation or task for a particular business loan of a pool of business loans to improve a rating of the pool of business loans. The system can monitor data associated with each of the objects to automatically identify particular objects. For example, the system can identify particular objects to be improved or particular objects to be removed from the pool of objects. The system can identify particular operations to improve the pool characteristic of the pool of objects and cause performance of the operations without modifying private data of the object pool by which the objects can be defined.

Abstract: In an example method, a system accesses a first data set representing parameters for implementing and operating a Power-to-X plant, and determines one or more configurations of the Power-to-X plant based on the first data set and a Bayesian optimization process. The configurations are determined by parsing the first data set to identify fields in the first data set, each representing a respective parameter; generating a plurality of data vectors representing respective first candidate configurations of the Power-to-X plant; inputting the data vectors and the first data set into a computer model; predicting, based on the computer model, a performance of the Power-to-X plant according to each of the first candidate configurations; and generating, using the Bayesian optimization process, one or more second candidate configurations based on the predicted performance. Further, the system generates and stores a second data set representing the one or more configurations of the Power-to-X plant.

Abstract: In an exemplary embodiment, software made in accordance with the present invention displays a marketplace interface, which displays at least a portion of a CAD model and a set of marketplace tool selectors to a user such that the user can manipulate the tool selectors to interact with an electronic marketplace. The marketplace interface may include a spectrum interface designed and configured to allow the user to selectively augment the marketplace interface with additional functionality. Various corresponding and related systems, methods, and software are described.

Abstract: A decision management technique comprises obtaining, for a set of items, data indicative of a previous percentage division between a first item type and a second item type for each item in the set of items. The technique further comprises classifying each item in the set of items into one of a plurality of clusters, based on the obtained data, wherein each cluster represents a different percentage division range between the first item type and the second item type. The technique further comprises identifying any items in each cluster that deviate from the percentage division range for the cluster, and then applying weights to any identified items based on the deviation from the percentage division range. The technique further comprises re-classifying any identified items to another cluster in the plurality of clusters based on the applied weights.

Abstract: In an electric power supply-demand adjustment system for performing electric power supply-demand adjustment by causing, by using a computer including a processor and memory, customers to control power consumption in accordance with an instruction issued by an aggregator, the processor, on the basis of demand response (DR) event information stored in the memory and including a scheduled event regarding the electric power supply-demand adjustment, and customer profile information stored in the memory and indicating a feature of a time-shiftable process performed by the customers consuming electric power, obtains a combination of processes shifted within an acceptable range, in which combination a power reduction amount fulfills a requested adjustment amount, to generate, for each of the customers, DR request information including a request for supply-demand adjustment of a power adjustment amount determined by the scheduled DR event, and determines a width of the shift to carry out electric power supply-demand

Abstract: Provided herein are systems and methods for matching and assigning drivers and various logistical agencies to food delivery tasks. The systems and methods increase the efficiency and effectiveness of delivering excess and/or unwanted food from donors to recipients who are in need of food. The systems and methods increase the efficiency and effectiveness by automatically matching each food delivery task to a driver who is able to pick up food from a donor and drop-off food at a recipient.

Abstract: Systems, computer program products, and methods are described herein for detecting attrition in a distributed network using artificial intelligence. Some embodiments are directed to a system including a first artificial intelligence engine configured to determine indicators of relationships between users and entities and a second artificial intelligence engine configured to determine statuses of relationships between the users and the entities. The system may determine, using the first artificial intelligence engine, and based on data associated with interactions between a user and an entity, a plurality of indicators of a relationship between the user and the entity. The system may determine, based on the plurality of indicators, based on the data associated with the interactions between the user and the entity, and using the second artificial intelligence engine, a status of the relationship between the user and the entity.

Abstract: Techniques for predicting marketing outcomes using contrastive learning are disclosed, including: obtaining historical marketing messages; obtaining historical open rates associated respectively with the historical marketing messages; based on the historical marketing messages, generating latent space representations associated respectively with the historical marketing messages; based on the latent space representations and respective contents of the historical marketing messages, training a first machine learning model to map contents of marketing messages to corresponding latent space representations of the marketing messages; based at least on the latent space representations and the historical open rates, training a second machine learning model to map latent space representations of marketing messages to predicted open rates of the marketing messages.

Abstract: A method for conducting an oilfield operation includes obtaining a plan for conducting an oilfield operation, the plan including a planned value for a metric, receiving data collected while performing one or more oilfield activities using the plan, at least a portion of the data representing an actual value for the metric, determining that one or more deviations from the plan occurred based on a difference between the actual value and the planned value, identifying one or more unplanned events of the one or more oilfield activities that are not in the plan that caused the one or more deviations, calculating a contribution to the difference between the actual value and the planned value caused by the one or more unplanned events, and modifying the plan to account for the one or more unplanned events.

Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for extraction of actionable insights in a computing environment. A server executes a machine learning classification model on text messages exchanged between users to classify each text message according to a disposition and a theme. The server analyzes the classified messages to generate candidate work items, each associated with software applications and skills requirements. The server filters the candidate items to remove extraneous items based upon a work item backlog or a prioritization. The server determines team members to assign to each remaining candidate item by comparing the software applications and the skills requirements for the work item to a profile for each team member. The server creates a task for each remaining candidate item, the task including the assigned team members. The server generates a notification for each task for transmission to the assigned team members.

Abstract: Systems and methods for providing an individualized map highlighting undiscovered areas of a locale. In particular, systems and methods are provided for providing a map that visually differentiates areas a user has visited from areas a user has yet to explore. In some implementations, generalized maps are displayed with highlighted and lowlighted areas representing unexplored and explored areas of the map. A generalized map can show popular tourist destinations or other features of each area. In some examples, specific map details of a particular area are revealed when a user selects the particular map area. In some examples, unexplored areas are revealed when a user elects to visit the unexplored area.

Abstract: A brand protection tool for managing risk to a brand is disclosed. The brand protection tool may provide a survey to a user. The survey may include a plurality of questions related to intellectual property. Based at least in part on the survey responses, the brand protection tool may determine a risk score, a protection score, and a net protection score. The brand protection tool may automatically generate a report including the net protection score and a visualization including a representation of the risk score and protection score. The brand protection tool may provide the report to a user or downstream system.

Abstract: A computer system, computer-implemented method and non-transitory computer-readable medium to predict transaction activity for a cyclical time period. A predictive transaction model is developed for individual user accounts, where the transaction model incorporates a cyclical data structure representation to detect and analyze transactions.

Abstract: A method and system for updating a graphical user interface (GUI) based on self-identified user intents.

Abstract: Embodiments described herein generate a first set of prompts, the first set of prompts configured to prompt a vehicle owner for a first set of answers used to learn preferred vehicle renter characteristics; receive the first set of answers; generate, based upon the first set of answers, a second set of prompts, the second set of prompts configured to prompt the owner for a second set of answers used to learn additional preferred vehicle renter characteristics; receive the second set of answers; predict user preference value(s) of a profile of the owner based upon the second set of answers, wherein the user preference value(s) define criteria for sharing a vehicle associated with the profile with vehicle renters who satisfy the criteria; apply the criteria to potential vehicle renters; and cause an indication of the vehicle to be displayed only to the potential vehicle renters who satisfy the criteria.