Abstract: A campaign management system may include a data collection subsystem to collect and store data from different sources that may be related to different marketing channels. The system may also include a map generation subsystem to generate a marketing campaign map that includes a visual representation of performance of the marketing channels. A performance metric adjustment factor may be determined for one or more performance metrics to determine an actual value performance metric for each metric. The actual value performance metrics may be aggregated and compared to benchmarks to generate a visual representation of the entire campaign performance across the marketing channels.

Abstract: Data conversion circuitry receives structured records including normalized data and performs a data conversion process on the structured records to generate unstructured records including unstructured syntax. The data conversion circuitry performs the data conversion process according to an unstructured syntax requirement including a syntax field mapping between the structured records and the generated unstructured records.

Abstract: Augmented reality (AR) based component replacement and maintenance may include receiving a first wireless signal from a pair of AR glasses worn by a user. An image of a component viewed by the user may be analyzed and compared to a plurality of images of components stored in a database that includes information associated with the plurality of images of the components. Based on a match of the image of the component viewed by the user to one of the plurality of images of the components stored in the database, the component viewed by the user may be identified. An inventory of the identified component may be analyzed to determine whether a supplier includes the identified component in stock, and in response to a determination that the supplier includes the identified component in stock, an estimated time of delivery of the identified component to the user may be determined.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing deception networks. One of the systems includes a threat information server configured to monitor and control security threats, a management process orchestration server configured to receive one or more identified security threats from the threat information server and develop a response process applicable to each identified security threat, a network switching controller in communication with one or more network switching devices, a target computing device connected to one of the network switching devices, and an indicator analytics processor configured to generate threat intelligence based on activity observed on the target device and provide the observed threat intelligence to the threat information server. The threat information server can receive threat intelligence information, identify key indicators, and generate identified security threats.

Abstract: Resource visualization, evaluation, and selection is often a difficult, complex, technically challenging endeavor. This is particularly true when there the resource set is extensive, the resources have widely varying attributes and capabilities, and the resources are also widely disbursed geographically. A multi-dimensional resource evaluation and visualization system implements technical solutions to these technical challenges.

Abstract: Methods, systems, and apparatus for training a machine learning model to route received computational tasks in a system including at least one quantum computing resource. In one aspect, a method includes obtaining a first set of data, the first set of data comprising data representing multiple computational tasks previously performed by the system; obtaining input data for the multiple computational tasks previously performed by the system, comprising data representing a type of computing resource the task was routed to; obtaining a second set of data, the second set of data comprising data representing properties associated with using the one or more quantum computing resources to solve the multiple computational tasks; and training the machine learning model to route received data representing a computational task to be performed using the (i) first set of data, (ii) input data, and (iii) second set of data.

Abstract: Implementations include deploying portions of a model used in a cognitive computing process for execution on respective devices in a distributed system, and include processing a device list to provide a benchmark list that includes an inventory of devices across systems that provide data for execution of the model used in the cognitive computing process, each device being a candidate for executing at least a portion of the model, the benchmark list including the devices, and, for each device, accuracies of the device with respect to the at least a portion of the model, providing a deployment plan based on the device and benchmark lists, the deployment plan specifying tasks to be executed by each device, at least two devices included in respective systems, at least one device providing data that is to be processed based on the at least a portion of the model, and executing the deployment plan.

Abstract: Resource visualization, evaluation, and selection is often a difficult, complex, technically challenging endeavor. This is particularly true when there the resource set is extensive, the resources have widely varying attributes and capabilities, and the resources are also widely disbursed geographically. A multi-dimensional resource evaluation and visualization system implements technical solutions to these technical challenges.

Abstract: A machine-to-machine communication platform provides a flexible system for device control and solution hosting. In particular, the communication platform hosts and manages third party vertical solutions that interact with external devices. A third party gateway provides the third parties with access to the communication platform so that the third parties may define, configure, and monitor custom vertical solutions that are locally hosted in the communication platform. The communication platform provides a communication manager that implements a device independent communication facility for communicating with the external devices. As a result, the communication platform connects to, communicates with, and controls virtually any external device.

Abstract: A closed-loop natural language query pre-processor and response synthesizer architecture accepts natural language queries and dynamically synthesizes query results. The query results may be in the form of data stories. The architecture identifies, selects, and composes candidate response elements into a coherent and meaningful query result. The architecture also implements an adaptable delivery mechanism that is responsive to connection bandwidth, query source preferences, query source characteristics, and other factors. Feedback from multiple sources adapts the architecture for handling subsequent queries.

Abstract: In one implementation, a wearable device for providing non-visual guidance to users includes one or more wireless interfaces to obtain information about the wearable device's current surroundings; one or more processors to (i) determine whether to provide non-visual guidance to a user wearing the wearable device based on the information obtained by the one or more wireless interfaces, and (ii) identify particular non-visual guidance to output to the user based on the determination of whether to provide non-visual guidance and the information; a haptic feedback array including a plurality of haptic motors arranged across at least a portion of the wearable device so that each of the plurality of haptic motors, when activated, provides haptic feedback from a distinct location of the wearable device; and a haptic engine to control the haptic feedback array to provide particular patterns of pulses that correspond to the particular non-visual guidance.

Abstract: In some examples, artificial intelligence and machine learning based project management assistance may include ascertaining an inquiry by a user. The inquiry may be related to a project. An attribute associated with the user and an attribute associated with the project may be ascertained. The inquiry may be analyzed based on the ascertained attributes associated with the user and the project. A predictor category may be identified, based on the analyzed inquiry, from a plurality of predictor categories that include a performance predictor category, a quality predictor category, a retrospect predictor category, and a planning predictor category. A predictor from a plurality of predictors may be identified based on the identified predictor category. A response to the inquiry may be generated based on execution of the identified predictor. Further, a display responsive to the inquiry may be generated based on the generated response.

Abstract: A crowdsource assistant provides guidance to crowdsource resources navigating a crowdsource platform to bid for and be accepted to accomplish tasks. The crowdsource assistant utilizes machine learning to train similarity computation models that improve the crowdsource assistant's computing capability to generate more relevant recommendations to a resource in a faster and more efficient manner.

Abstract: A system for managing the operation of different components within a cloud system to accomplish various tasks, including the implementation of build features within the cloud system to achieve specific operational goals. The system may include a data defined infrastructure (DDI) tool installed within a data defined infrastructure (DDI) to manage certain features or tasks within the cloud system. The DDI may include an environment configuration database (ECDB), an orchestration engine, an automation engine, and/or other hardware and software components within the cloud system, such that the DDI tool installed on the DDI infrastructure may control operation of the ECDB, the orchestration engine, the automation engine, or other hardware and software components within the cloud system based on a set of data that fully describes the operational goal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying network security risks. One of the methods includes receiving organizational hierarchy data and receiving access privilege data for a network, generating an adjacency matrix that represents connections between individuals within the organizational hierarchy and various groups, and that represents connections between the individuals and various access privileges, selecting an analytic technique for analyzing the adjacency matrix, determining, for each individual, an individual score that represents a security risk associated with the individual's network account, and in response to determining that the individual score meets a threshold, applying security controls.

Abstract: A device may generate a transaction network associated with a plurality of accounts. The plurality of accounts may include a set of client accounts associated with a set of clients of an account manager, and a set of non-client accounts associated with a set of non-clients of the account manager. The transaction network may identify transactions among the set of client accounts and the set of non-client accounts. The device may identify, based on the transaction network, a community of accounts including a subset of client accounts for which transactions satisfy a threshold, and a non-client account that has transacted with one of the subset of client accounts. The device may determine target information, associated with the non-client account, including information associated with targeting a non-client, associated with the non-client account, by the account manager. The device may provide the target information and information associated with the community of accounts.

Abstract: A device may receive an alarm from a network and determine whether to process the alarm using a robotic process automation (RPA) engine or a machine learning automation (MLA) engine. Based on the determination, the device may selectively cause the alarm to be processed by the RPA engine or the MLA engine. The device may receive data associated with a network performance indicator and may provide the data to the MLA engine. The MLA engine may use a machine learning model to assign a score to the data and may determine whether to generate a trouble ticket based on the score.

Abstract: A browser and operating system (OS) compatibility system may include a user interface to select a first combination of a browser and OS for comparison to a second combination of a browser and OS. A download engine may capture source files for browsers for the first and second combinations. A parse engine may create Document Object Model (DOM) trees of objects of first and second website pages respectively for the browsers for the first and second combinations. A metric engine may read the DOM trees for attributes of the objects to capture metrics of the objects. An analysis metric engine may compare a metric of an object of the first website page to a metric of the same object of the second website page to determine a compatibility of the browser and the OS for the first combination to the browser and the OS for the second combination.

Abstract: A device may receive a plurality of data objects from a plurality of sources; identify text data, image data, and location data of the plurality of data objects; identify relevant data objects, of the plurality of data objects, based on the text data, and/or based on the image data, based on the location data, and/or based on comparing the text data, the image data, and the location data to a predefined element that identifies values relevant to a particular group or subject area; assign scores to the relevant data objects based on the text data, the image data, and the location data; aggregate the scores, as one or more aggregated scores, with regard to one or more users associated with the relevant data objects; and/or perform one or more actions based on the one or more aggregated scores associated with the one or more users.

Abstract: A device may generate a call plan for a set of testing calls. The device may initiate a testing call to a communication device associated with a target, of the set of targets, using a user profile of the set of user profiles. The device may initiate monitoring for the testing call to identify information associated with the target during the testing call. The device may generate one or more responses to one or more queries based on the user profile. The device may transmit the one or more responses to the one or more queries based on generating the one or more responses to the one or more queries. The device may process stored data regarding testing calls to generate a recommendation relating to the set of targets for the set of testing calls. The device may communicate with one or more other devices to implement the recommendation.