Abstract: An on-demand learning system provides an enhanced leaning environment capable of delivering relevant content on virtually any topic to specific learners. The learning system implements technical features that facilitate curation and subject matter validation of many different types of content. The technical architecture of the learning system also supports intelligent matching of learners to subject matter areas, creation of specific subject matter boards, and resilient maintenance of the boards.

Abstract: A device identifies training data and scoring data for a model, and removes bias from the training data to generate unbiased training data. The device trains the model with the unbiased training data to generate trained models, and processes the trained models, with the scoring data, to generate scores for the trained models. The device selects a trained model, from the trained models, based on model metrics and the scores, and processes a training sample, with the trained model, to generate first results, wherein the training sample is created based on the unbiased training data and production data. The device processes a production sample, with the trained model, to generate second results, wherein the production sample is created based on the production data and the training sample. The device provides the trained model for use in a production environment based on the first results and the second results.

Abstract: A device may detect a trigger to perform a benchmarking task. The benchmarking task may include a first benchmarking of a first resource utilization associated with one or more tasks completed via an automated procedure. The benchmarking task may include a second benchmarking of a second resource utilization associated with the one or more tasks completed via a manual procedure. The device may determine project data relating to a project platform based on detecting the trigger to perform the benchmarking task. The device may process the project data relating to the project platform to benchmark the project. The device may generate a recommendation relating to completion of the one or more tasks using the automated procedure or the manual procedure. The device may communicate with one or more other devices to perform a response action based on the recommendation.

Abstract: A device may provide a user interface for receiving project information for a software implementation project. The project information may be associated with a set of requirements defining the software implementation project. The project information may be associated with a set of deliverables describing results of the software implementation project. The device may generate an initial project plan based on the project information. The device may receive information regarding the initial project plan during fulfillment of the project plan. The device may selectively provide an alert associated with the initial project plan based on receiving the information regarding the initial project plan. The device may selectively generate a modified project plan based on receiving the information regarding the project plan.

Abstract: In some examples, natural language unification based robotic agent control may include ascertaining, by a robotic agent, an image of an object or an environment, and ascertaining a plurality of natural language insights for the image. A semantic relatedness may be determined between each insight of the plurality of insights, and a semantic relatedness graph may be generated for the plurality of insights. For each insight of the plurality of insights, at least one central concept may be identified. Based on the semantic relatedness graph and the identified at least one central concept, the plurality of insights may be clustered to generate at least one insights cluster. For insights included in the least one insights cluster, a unified insight may be generated. Further, an operation associated with the robotic agent, the object, or the environment may be controlled by the robotic agent and based on the unified insight.

Abstract: In some examples, natural language eminence based robotic agent control may include ascertaining, by a robotic agent, an image of an object or an environment, and ascertaining a plurality of natural language insights for the image. For each insight of the plurality of insights, an eminence score may be generated, and each insight of the plurality of insights may be ranked according to the eminence scores. An operation associated with the robotic agent, the object, or the environment may be controlled by the robotic agent and based on a highest ranked insight.

Abstract: A device receive data regarding a project. The device may automatically evaluate the data using a set of analytics tools. The device may communicate with a client device to provide a virtual agent user interface component based on evaluating the data using the set of analytics tools. The virtual agent user interface component may include information identifying a set of alerts relating to the project and a set of recommendations relating to the set of alerts. The device may receive information indicating that a particular recommendation, of the set of recommendations is to be implemented. The device may communicate with one or more other devices to implement the particular recommendation.

Abstract: A device may receive information associated with a work request. The device may identify a work profile, associated with a group of tasks to perform, and a group of task profiles, associated with estimating a resource demand for performing the group of tasks by a group of resources. The device may generate, based on the work profile and the group of task profiles, a plan identifying the group of tasks, an order for performing the group of tasks, and an estimated resource demand associated with performing the tasks. The device may provide, to a resource device associated with the group of resources, an assignment identifying a task from the group of tasks; may receive, from the resource device, a completion update identifying a completion status associated with the task; may update status information based on the completion update; and may output a status update based on the status information.

Abstract: One or more computing resources, of a project management platform, may implement a delivery tool layer to provide one or more tools associated with managing portions of a project. The one or more computing resources may implement an integration layer to integrate the one or more tools into the project management platform for the project. The one or more computing resources may implement a data acquisition layer to obtain data regarding the project. The one or more computing resources may implement an automation layer to automate tasks associated with the project. The automation layer may be associated with automating a set of development operations, a set of maintenance operations, a set of management operations, a set of testing operations, or the like. The one or more computing resources may implement an artificial intelligence (AI) layer to process data relating to the project using one or more AI integrations.

Abstract: A method of maintaining a data store is disclosed. The data store is distributed across a plurality of storage provider instances, including a master storage provider instance and a plurality of additional storage provider instances. A master data log is updated to reflect a change to the data store. The master data log is synchronized with a plurality of replicas of the master data log. The change is propagated across the plurality of additional storage provider instances based on an analysis of the replicas.

Abstract: A device may identify a ticket associated with an issue, a user associated with resolving the issue, and a particular business process including a particular business process step associated with the issue. The device may present information regarding a particular business process workflow, corresponding to the particular business process, associated with a business process steps. The device may identify the particular business process step from the business process steps, and may identify a particular technical solution corresponding to the particular business process step. The device may present information regarding a particular technical solution workflow, corresponding to the particular technical solution, associated with technical solution steps. The device may identify a particular technical solution step, from the technical solution steps, associated with resolving the issue.

Abstract: A device may provide a user interface for receiving project information for a software implementation project. The project information may be associated with a set of requirements defining the software implementation project. The project information may be associated with a set of deliverables describing results of the software implementation project. The device may generate an initial project plan based on the project information. The device may receive information regarding the initial project plan during fulfillment of the project plan. The device may selectively provide an alert associated with the initial project plan based on receiving the information regarding the initial project plan.

Abstract: A device may receive information associated with a work request. The device may identify a work profile, associated with a group of tasks to perform, and a group of task profiles, associated with estimating a resource demand for performing the group of tasks by a group of resources. The device may generate, based on the work profile and the group of task profiles, a plan identifying the group of tasks, an order for performing the group of tasks, and an estimated resource demand associated with performing the tasks. The device may provide, to a resource device associated with the group of resources, an assignment identifying a task from the group of tasks; may receive, from the resource device, a completion update identifying a completion status associated with the task; may update status information based on the completion update; and may output a status update based on the status information.

Abstract: An on-demand learning system provides an enhanced leaning environment capable of delivering relevant content on virtually any topic to specific learners. The learning system implements technical features that facilitate curation and subject matter validation of many different types of content. The technical architecture of the learning system also supports intelligent matching of learners to subject matter areas, creation of specific subject matter boards, and resilient maintenance of the boards.

Abstract: A device may receive ticket information associated with one or more service tickets. The ticket information may include a ticket category and ticket data associated with the one or more service tickets. The ticket data may be associated with the ticket category. The ticket data may describe information related to resolving the one or more service tickets. The device may identify, based on the ticket category or the ticket data, an association between the ticket category and an analysis category. The analysis category may be used to analyze the ticket information. The device may generate categorized ticket information based on the analysis category and the ticket information. The categorized ticket information may include the ticket data, and the ticket data may be associated with the analysis category. The device may provide the categorized ticket information.

Abstract: A computer-readable medium, computer-implemented method, and apparatus are provided. In one embodiment, financial data is extracted from a financial manager, and the financial data is mapped to compliance data from a compliance manager. One or more controls of one or more accounts from compliance data is selected to be in scope, and an assessment plan is created for the selected one or more controls within scope.

Abstract: One or more computers retrieve records of transactions to be analyzed together. Each record identifies a date of a transaction, an amount of the transaction, a person associated with the transaction, and a category into which the transaction is classified. The one or more computers automatically prepare in computer memory, a set of tuples (also called “vectors”) corresponding to a set of persons identified in the retrieved records. Each tuple corresponds to one person, and each tuple includes at least one number representing a count within each category, of transactions classified therein, e.g. total number of cash transactions in category X. Then, the one or more computers automatically identify a subset of outliers, e.g. by grouping the tuples into clusters using k-means clustering, followed by marking in memory an indication of inappropriateness of any transaction that had been included in the count of a tuple now identified to be outlier.

Abstract: Techniques are described for parallelizing qualifying window functions without reliance on partitioning criteria specified in the command that includes the qualifying window functions. Because the techniques do not rely on partitioning criteria specified in the command, the techniques may be used on commands in which no partitioning criteria is specified. In general, the techniques involve partitioning the work of a qualified window function into ranges, and sharing precomputed aggregate values between computational elements to calculate the value for the window functions.

Abstract: A method of maintaining a data store is disclosed. The data store is distributed across a plurality of storage provider instances, including a master storage provider instance and a plurality of additional storage provider instances. A master data log is updated to reflect a change to the data store. The master data log is synchronized with a plurality of replicas of the master data log. The change is propagated across the plurality of additional storage provider instances based on an analysis of the replicas.

Abstract: Techniques are provided for executing query statements, or portions thereof, in parallel without using slave SQL to communicate to each slave the operations to be performed by the slave. Instead of generating one cursor for the query coordinator (QC) based on the original statement, and separate cursors for each DFO based on the slave SQL, the techniques involve sharing the cursor that is generated from the original statement among the various participants involved in the parallel execution of the operations specified in the original statement.