Abstract: In some examples, a computing device may determine that an issue (e.g., crash, restart etc.) occurred, gather context data (e.g., logs, device profile, etc.) associated with the issue, and generate a contact address to technical support based on the context data. The computing device may upload the context data to a location accessible to a server. After a user of the computing device initiates a communication to technical support using the contact address, the server may automatically route the call, based on the contact address, to a particular technician that has experience addressing the issue. The server may retrieve the context data and use machine learning to determine recommendations to address the issue. The machine learning may prioritize the recommendations and provide the context data and the prioritized recommendations to enable the particular technician to quickly resolve the issue.

Abstract: In some examples, a device includes a charging circuit with a thermoelectric generator and a kinetic energy generator. An embedded controller (EC) monitors a level of a battery in the device. If the level falls below a threshold, the EC may determine, using an accelerometer, whether the device is in motion. If the device is in motion, the EC may use the kinetic energy generator to charge the battery. If the device is not in motion, the EC may determine, using a temperature sensor, whether there is a temperature difference between two portions of the device. If there is a temperature difference, then the EC may use the thermoelectric generator to charge the battery. If the EC determines that the device is not in motion and there is no temperature difference between the two portions, then the EC may instruct the user to charge the device.

Abstract: A method, system, and computer-usable medium are disclosed for acquiring and using audio detected during operation of a hard disk drive to determine the status of the hard disk drive. One general aspect of the disclosure is directed to a computer-implemented method that includes receiving analog audio detected by an audio transducer in proximity to moving mechanical components of a hard disk drive, converting the received analog audio to digital audio, and assigning a health classification status to the hard disk drive based on a classification of the digital audio.

Abstract: A system of one or more computers can be configured to facilitate the design of a service. The disclosed system may operate to add a process block to a service design structure for the service. The process block is provided to a trained AI/ML process prediction model. The trained AI/ML process prediction model suggests one or more further process blocks for addition to the service design structure based, at least in part, on the addition of the process block to the service design structure. In certain embodiments, a process block is selected from the suggested one or more further process blocks and added to the service design structure. Other embodiments of this aspect of the disclosure include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Abstract: A method comprises extracting data for one or more assets corresponding to a user, and analyzing the data using one or more machine learning models. The analyzing comprises predicting whether the one or more assets will require at least one of replacement and service. In the method, one or more entitlement recommendations for the user are generated based on the analysis, and the one or more entitlement recommendations are transmitted to the user.

Abstract: In some examples, a computing device may receive, from an email server, an email rule comprising conditions and actions and determine a subset of archived emails stored on the computing device that satisfy the conditions. The computing device may perform the actions to the subset of archived emails, such as placing a legal hold on the subset of archived emails, creating and sending copies of the subset of archived emails to the email server, or deleting, from the computing device, the subset of archived emails. After determining that a user is attempting to perform a prohibited action on (e.g., delete, edit, forward) an email of the subset of archived emails, the computing device may perform a protective action, such as logging the user out of an email account, preventing the user from logging in to the email account, automatically sending an email to an administrator or the like.

Abstract: The described technology is generally directed towards processing various customer input data to extract frequently recurring customer experience themes, including positive and negative sentiment regarding customer experiences. Natural language processing, image processing, speech recognition and/or computer vision techniques can be used on customer-related data to determine themes, tests and scenarios, as well as discover insights that can be used to improve customer experiences. The technology can be used to recreate a customer engagement, journey and overall experience by designing test scenarios around failure themes.

Abstract: Methods, apparatus, and processor-readable storage media for connecting configuration services using blockchain technology are provided herein. An example computer-implemented method includes obtaining at least one user request comprising configuration-related data pertaining to at least one item of hardware and at least one user network; encrypting at least a portion of the configuration-related data using one or more cryptographic hash functions; storing copies of the encrypted configuration-related data across multiple nodes within at least one distributed blockchain technology-based cloud storage system; and performing one or more automated actions, in connection with the at least one user request, using at least a portion of the stored data within the at least one distributed blockchain technology-based cloud storage system.

Abstract: A method includes retrieving information regarding a candidate from a plurality of sources, and analyzing the information regarding the candidate using one or more machine learning techniques. A plurality of questions for the candidate are generated based on the analysis. The method further includes receiving and analyzing a plurality of natural language responses to the plurality of questions from the candidate, and computing a plurality of confidence scores for the plurality of natural language responses using the one or more machine learning techniques. The plurality of questions and the plurality of confidence scores are provided to a user via a user interface.

Abstract: In some examples, a server may determine that a case, created to address an issue of a computing device, is closed and perform an analysis of steps in a process used to close the case. The analysis may determine a length of time of each step and determine that a time to close the case or complete a particular step was at least a predetermined amount faster than average. The server may use machine learning to create a survey question to determine a technique used to close the case or complete the particular step faster than average and to determine one or more incentives to provide a technician that closed the case. An answer from the technician to the survey question may include the technique used to close the case or complete the particular step faster than average. The technique may be shared with other technicians.

Abstract: The disclosed systems and methods are directed to a computer-implemented method for use in designing a service. In at least one embodiment, a method includes designing a service with one or more generic virtual network functions (VNFs), where the generic VNFs are defined independent of vendor sourcing information. One or more trained machine learning (ML) models are used to identify VNFs available from VNF vendors that may source one or more VNFs similar to the generic VNFs. The service is implemented using VNFs provided by one or more VNF vendors, where the VNFs provided by the one or more VNF vendors have network functionality generating similar to the one or generic VNFs.

Abstract: Techniques described herein relate to a method for managing nodes. The method may include sending, by a first node of nodes, a node information request to a social manager, where the node information request specifies a portion of a service to be provided to the first node; obtaining node information associated with a portion of the nodes from the social manager, where the portion of the plurality of nodes previously expressed node capability information and node configuration information associated with the portion of the service; identifying a second node of the portion of the nodes based on the node information to perform the portion of the service; and performing the service using the second node, where the second node performs the portion of the service.

Abstract: Methods, apparatus, and processor-readable storage media for automated issue detection and remediation across multiple user systems using healing-as-a-service techniques are provided herein. An example computer-implemented method includes obtaining system configuration data from at least a portion of multiple user systems within a network; obtaining an alert pertaining to an issue attributed to a first of the user systems; training a machine learning model related to user system issue detection using at least a portion of the system configuration data and data related to the alert; determining user system configuration adjustments related to remedying at least a portion of the issue, by processing the data related to the alert using the trained machine learning model; automatically performing the user system configuration adjustments in connection with the first user system; and sharing, using at least one healing-as-a-service component, the trained machine learning model with the user systems in the network.

Abstract: Systems and methods for assessing the skills of a customer support agent using one or more Artificial Intelligence/Machine Learning (AI/ML) models are disclosed. In at least one embodiment, one or more benchmarks against which the performance of the customer support agent is to be measured are established. The one or more benchmarks may be derived through direct and/or indirect analysis of historical customer service data by an AI/ML benchmark model. In at least one embodiment, data relating to performance of the customer support agent during a customer call is monitored. In at least one embodiment, the AI/ML benchmark model is used to determine one or more benchmark scores identifying whether the customer support agent is meeting the one or more benchmarks.

Abstract: In some examples, a server may receive a first order to acquire a product. The server may receive a request to cancel the first order and determine that the product has been shipped. The server may determine, based on sensor data received from a sensor in the container, that the container is unopened. After receiving a second order to ship the product to a second location, the server may instruct a courier to transport the product to the second location. For example, if the container is located at the first location, the server may instruct the courier to transport the container from the first location to the second location. If the server determines that the courier is currently transporting the container to the first location, the server may instruct the courier to transport the container to the second location instead of to the first location.

Abstract: In some examples, before saving a file, a device analyzes contents (e.g., text and images) of the file to create a bag of words. The device performs Latent Dirichlet Allocation of the bag of words to determine topics included in the file and orders the topics in descending order of frequency. The device generates a particular name of the file based on the ordered topics and automatically save (or suggest saving) the file with the particular name. The device determines, based on the ordered topics, a folder name of a folder in which to store the file. If an existing folder has the folder name, then the device saves the file in the existing folder. If not, then the device creates a new folder with the folder name and saves the file in the new folder.

Abstract: In some examples, a server may receive a first order to acquire a product. The server may receive a request to cancel the first order and determine that the product has shipped. The server may determine, based on sensor data received from a sensor of a circuit board in the container, that the container is unopened. After receiving a second order to ship the product to a second location, the server may instruct a courier to transport the product to the second location. For example, if the container is located at the first location, the server may instruct the courier to transport the container from the first location to the second location. If the server determines that the courier is currently transporting the container to the first location, the server may instruct the courier to transport the container to the second location instead of to the first location.

Abstract: In some examples, a server may receive an order from a customer to acquire a computing device. The server may determine a customer and a customer location associated with the order and determine a documentation specification based at least in part on the customer and the customer location. The server may determine content identifiers corresponding to content (e.g., documentation and software) to be provided with the order. The server may associate a device identifier that uniquely identifies the computing device with the content identifiers. The computing device may be shipped to the customer location without the plurality of content. When the computing device is booted at the customer location, the computing device may send the device identifier to the server, the server may determine the plurality of content identifiers associated with the device identifier, and send the plurality of content in a digital form for installation on the computing device.

Abstract: A drone-based product delivery mechanism in which power is transferred between the drone's battery and a product's battery while the product is in transit to its destination. For a short distance delivery, the drone battery may be used to charge the product battery so that the product is delivered with a fully-charged battery. On the other hand, for long distance deliveries, the power from a fully-charged product battery may be used to charge the drone's battery to extend the flight time/radius of the drone or to supplement the drone battery to conserve its power. The power transfer may be carried out using a wireless connection or a wired connection. The wireless connection may be a Qi interface, whereas the wired connection may be a Universal Serial Bus (USB) connection. The product packaging may be re-designed to allow the desired power transfer between the drone and the product inside the packaging.

Abstract: Methods, information handling systems and computer readable media are disclosed for determining a priority score for a pending support request document. According to one embodiment, a method includes receiving current support request information from within a pending support request document and accessing current additional information associated with the pending support request document. The method further includes associating a set of parameter values with the pending support request document, wherein the values within the set of parameter values are based on information within one or both of the current support request information or the current additional information.