Abstract: Techniques are disclosed for domain-driven intent-based feedback data analysis. For example, a method comprises obtaining a feedback data set, and classifying the feedback data set into at least one domain of a plurality of domains. The feedback data set is mapped to a domain data set corresponding to the at least one domain, and a root cause is computed for the feedback data set to enable one or more actions to be taken in response to the feedback data set based on the root cause. By way of further example, computing the root cause for the feedback data set may further comprise utilizing at least one computed intent attribute, at least one computed sentiment attribute, and the domain data set to compute a decision on the root cause for the feedback data set.

Abstract: Methods, apparatus, and processor-readable storage media for automated database operation classification using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining at least one query related to one or more database operations; obtaining information pertaining to a set of multiple storage resources; classifying the at least one query as associated with at least one of multiple subsets of storage resources among the set of multiple storage resources by processing at least a portion of the query and at least a portion of the information pertaining to the set of multiple storage resources using one or more artificial intelligence techniques; and performing one or more automated actions based at least in part on the classifying of the at least one query.

Abstract: A method comprises transmitting order data to at least one package configured for electronically receiving the order data and accommodating one or more items therein, wherein the at least one package is electronically locked. In the method, an access code for electronically unlocking the at least one package is generated and transmitted to a user device. The method also includes receiving a notification that the at least one package was unlocked, wherein the notification is received in response to electronically unlocking the at least one package with the access code.

Abstract: Embodiments of the present disclosure relate to systems, methods, and user interfaces for providing voice-activated ambulance booking. Initially, a non-medical user initiates a workflow, via a voice command, that enables the user to provide information about a patient that can be utilized to prioritize the booking of ambulances for patients. Upon providing the initial voice command, the workflow is provided, via a user interface of the user device. The workflow comprises a series of questions corresponding to a status of the patient that can easily be answered merely by observing the patient (e.g., is the patient conscious, is the patient breathing, is the patient bleeding). Based on responses provided by the user, an ambulance is requested for the patient. User device vitals including battery charge levels and signal strength can be used to resolve conflicts if multiple requests are made.

Abstract: Techniques are disclosed for hyper-segmented personalization using machine learning-based models in an information processing system. For example, a method obtains one or more product experience recommendation data sets respectively from one or more product entities, and one or more purchase experience recommendation data sets respectively from one or more commerce entities. The method applies a federated ensemble-based machine learning algorithm to at least one of the one or more purchase experience recommendation data sets and at least one of the one or more product experience recommendation data sets to generate a personalized model, and causes adaptation of a purchasing interface of at least one of the one or more commerce entities with respect to a given user based on the personalized model.

Abstract: A method comprises analyzing a plurality of natural language inputs associated with at least one user, and determining a plurality of contexts for the plurality of natural language inputs based, at least in part, on the analysis. In the method, a plurality of relationships linked to the at least one user are identified based, at least in part, on the analysis, and the at least one user is classified in one or more categories based, at least in part, on the plurality of contexts and the plurality of relationships. At least one of the analyzing, determining, identifying and classifying is performed using one or more machine learning models.

Abstract: Computing devices with dual computing architectures for use in a subscription model are disclosed. For example, a computing device comprises a first computing architecture comprising a first set of computing resources dedicated to executing one or more first computing tasks, wherein the one or more first computing tasks are associated with a subscription-based user of the computing device. The computing device further comprises a second computing architecture comprising a second set of computing resources dedicated to executing one or more second computing tasks, wherein the one or more second computing tasks are associated with a subscription-based provider of the computing device.

Abstract: Methods, systems, and apparatuses for configuring a device for a specific task or set of tasks thereby allowing the device to be used for more than one task or set of tasks while also enabling fine-grain control over how the device may be used. A device's file system can operate with a particular file system based on the task(s) that the device will perform. Further, the device can physically configure itself based on the task(s) that the device will perform.

Abstract: Methods, apparatus, and processor-readable storage media for application aware cache management are provided herein. An example computer-implemented method includes maintaining a data structure comprising at least one entry indicative of an importance of at least one of a plurality of applications associated with a storage system; and controlling whether or not a particular data item requested by one of the plurality of applications is cached in a cache memory of the storage system based at least in part on the at least one entry of the data structure.

Abstract: A method comprises receiving one or more inputs captured by a camera of a device, and determining, using one or more machine learning models, whether the one or more inputs depict at least one object configured to capture a visual representation of a screen of the device. A recommendation is generated responsive to an affirmative determination, the recommendation comprising at least one action to prevent the capture of the visual representation of the screen of the device.

Abstract: Embodiments herein relate to a computer which operates in a normal power mode, a full low power mode and a modified low power mode. A power supply unit (PSU) includes main power rails and a standby power rail. An intelligent decision is made as to when to turn on and off the main power rails based on the needs of connected devices such as USB Type-C devices. Power Delivery controllers communicate with the USB devices to determine their power consumption needs, and the total power consumption is aggregated at an embedded controller. If the total exceeds an available power budget, the PSU is controlled to allow for a modified low power mode in which full power is maintained at the main power rails while non-essential internal components are turned off.

Abstract: Embodiments include a method for object detection in a Light Detection And Ranging (LiDAR) point cloud, the method comprising: placing, by a navigation system, a plurality of anchor points in a two-dimensional Bird's Eye View (BEV) of spatial points represented in a segmented ground surface representation of objects detected by a LiDAR system; extracting, by the navigation system, one or more features from the two-dimensional BEV of the spatial points; proposing, by the navigation system, one or more regions of the two-dimensional BEV of the spatial points for object detection; and performing, by the navigation system, object detections on anchor points of the plurality of anchor points in the proposed one or more regions of the two-dimensional BEV of the spatial points.

Abstract: Techniques are provided for managing an end-to-end software development life cycle. A software development lifecycle management system performs a plurality of stages of work for developing a software application, and records transactions which result from performing the plurality of stages of work, in an immutable digital ledger. The immutable digital ledger can be a blockchain ledger.

Abstract: Techniques for managing containerized workloads in a container computing environment are disclosed. For example, a method comprises the following steps. In a first mode, the method learns resources and execution times needed to process incoming workloads of a first workload type and a second workload type in a set of one or more clusters in a container-based computing environment. In a second mode, based on the learning of resources and execution times in the first mode, the method determines whether a subsequent incoming workload of the second workload type can be executed by one of the set of one or more clusters or whether an additional cluster should be created to process the subsequent incoming workload and then removed after processing the subsequent incoming workload is completed.

Abstract: Methods, apparatus, and processor-readable storage media for automatically prioritizing supply chain-related demand using artificial intelligence techniques are provided herein.

Abstract: A method comprises receiving at least one natural language input, converting the at least one natural language input to a graphical input, retrieving relationship data from a graph database based at least in part on the graphical input, and generating at least one natural language response of a virtual assistant to the at least one natural language input based at least in part on the relationship data from the graph database. At least the generating is performed using one or more machine learning models.

Abstract: Techniques are provided for data size and time based replication. In an example, a first daemon monitors data changes that corresponds to a first replication policy, and a second daemon monitors an amount of time since performing a replication for the first replication policy. Where either a data modification threshold is met, or a time threshold is met, the daemons can perform a replication, and reset both a data counter and a timer that determine when next to perform a replication.

Abstract: Techniques are provided for tracking users modifying, writing, or editing a file. In an example, a file system maintains a first-in-first-out queue that logs a finite set of users that have most-recently modified a file. This queue can be maintained in an extended attribute of an Mode that corresponds to a file. Where a user modifies a file, and the user is currently identified in the queue, the user can be removed from the queue. Where the user modifies a file, is not currently identified in the queue, and the queue is full, an oldest user in the queue can be removed from the queue. Then, the user can be added to the back of the queue.

Abstract: Techniques are disclosed for enabling a multi-model and clustering database system. For example, a query from a client is received at a primary cluster in a clustering database system implemented over one or more processing platforms. The primary cluster analyzes the query to determine an intent of the query and, based on the intent of the query, to identify at least one secondary cluster from a plurality of secondary clusters in the clustering database system to execute the query. The primary cluster manages the plurality of secondary clusters, and one or more of the plurality of secondary clusters support a data model type that is different than a data model type of one or more others of the plurality of secondary clusters.

Abstract: Techniques are disclosed for data management in an information processing system. For example, a method comprises analyzing one or more data sources, wherein each of the one or more data sources comprise a set of metadata and usage information associated with the set of metadata. The method then determines at least one of data definitions and data classifications for the one or more sets of metadata across the one or more data sources, and stores the at least one of data definitions and data classifications for the one or more sets of metadata in a repository.