Abstract: Examples of the present disclosure provide apparatuses and methods for determining a vector population count in a memory. An example method comprises determining, using sensing circuitry, a vector population count of a number of fixed length elements of a vector stored in a memory array.

Abstract: A device may receive source code and a database to be migrated to a cloud computing environment, and may perform a first stage analysis of the source code to generate a first report. The device may cause a second stage analysis of the source code to be performed based on the first report and to generate refactored and rewritten code, and may perform a third stage analysis of the database to generate a second report. The device may cause a fourth stage analysis of the database to be performed and to generate a refactored and rewritten database, and may perform the first stage analysis of the refactored and rewritten code and the third stage analysis of the refactored and rewritten database to generate a final report. The device may generate a migration strategy based on the final report and may perform actions based on the migration strategy.

Abstract: Provided are systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning to identify, diagnose, and mitigate occurrences of network faults or incidents within a network. Historical network incidents may be used to generate a model that may be used to evaluate real-time occurring network incidents, such as to identify a cause of the network incident. Clustering algorithms may be used to identify portions of the model that share similarities with a network incident and then actions taken to resolve similar network incidents in the past may be identified and proposed as candidate actions that may be executed to resolve the cause of the network incident. Execution of the candidate actions may be performed under control of a user or automatically based on execution criteria and the configuration of the fault mitigation system.

Abstract: A system includes a memory device and a processing device coupled to the memory device. The memory processing device can perform operations including receiving data indicative of occurrence of a plurality of events. The processing device can perform operations including determining an event log type for each of the plurality of events. The processing device can perform operations including storing an identifier associated with each of the determined event log types. The processing device can perform operations including updating a counter value associated with each identifier in response to occurrence of an event associated with the respective identifier.

Abstract: Intelligent machine learning-based systems and methods of generating recommendations for individualized skill development. The system and method offer an automated framework by which organizations can easily pre-screen bulk profiles, hire based on region and projects, and provide employees with a skill upgrade program to enhance their capabilities. The system can use natural language processing techniques to ingest and process candidate and job data and machine learning techniques to identify the degree to which the skills of each candidate match the organization's available roles. In some embodiments, the framework facilitates a bench reduction program that helps optimize the workforce by identifying underutilized employees and help organizations build a strong, capable workforce that can achieve their current and future goals.

Abstract: A device may receive source code and a database to be migrated to a cloud computing environment, and may perform a first stage analysis of the source code to generate a first report. The device may cause a second stage analysis of the source code to be performed based on the first report and to generate refactored and rewritten code, and may perform a third stage analysis of the database to generate a second report. The device may cause a fourth stage analysis of the database to be performed and to generate a refactored and rewritten database, and may perform the first stage analysis of the refactored and rewritten code and the third stage analysis of the refactored and rewritten database to generate a final report. The device may generate a migration strategy based on the final report and may perform actions based on the migration strategy.

Abstract: A device may receive input data that includes demographic data, power demand data, power source data, power route data, technology data, industry data, and problem data associated with a geographic location, and may identify a section of the geographic location from the demographic data. The device may identify power sources of the section, and may estimate power generation and power demand for the section. The device may determine whether the power demand is greater than the power generation for the section. The device may utilize a quantum computer and a power optimizer model with the input data associated with the section to determine optimized power insights for the section based on determining that the power demand is greater than the power generation for the section, and may perform actions based on the optimized power insights for the section.

Abstract: Examples of the present disclosure provide apparatuses and methods for determining a vector population count in a memory. An example method comprises determining, using sensing circuitry, a vector population count of a number of fixed length elements of a vector stored in a memory array.

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning to identify, diagnose, and mitigate occurrences of network faults or incidents within a network. Historical network incidents may be used to generate a model that may be used to evaluate real-time occurring network incidents, such as to identify a cause of the network incident. Clustering algorithms may be used to identify portions of the model that share similarities with a network incident and then actions taken to resolve similar network incidents in the past may be identified and proposed as candidate actions that may be executed to resolve the cause of the network incident. Execution of the candidate actions may be performed under control of a user or automatically based on execution criteria and the configuration of the fault mitigation system.

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning to identify, diagnose, and mitigate occurrences of network faults or incidents within a network. Historical network incidents may be used to generate a model that may be used to evaluate real-time occurring network incidents, such as to identify a cause of the network incident. Clustering algorithms may be used to identify portions of the model that share similarities with a network incident and then actions taken to resolve similar network incidents in the past may be identified and proposed as candidate actions that may be executed to resolve the cause of the network incident. Execution of the candidate actions may be performed under control of a user or automatically based on execution criteria and the configuration of the fault mitigation system.

Abstract: A device may receive audio data identifying a plurality of speakers and may process the audio data, with a plurality of clustering models, to identify a plurality of speaker segments. The device may determine a plurality of diarization error rates for the plurality of speaker segments and may identify a plurality of errors in the plurality of speaker segments. The device may select rectification models to rectify the plurality of errors and may segment and/or re-segment the audio data with the rectification models to generate re-segmented audio data. The device may determine a plurality of modified diarization error rates for the plurality of speaker segments based on the re-segmented audio data and may select one of the plurality of speaker segments based on the plurality of modified diarization error rates. The device may calculate an empathy score based on the selected speaker segment and may perform actions based on the empathy score.

Abstract: Methods, systems, and apparatus for root cause analysis in a communication network. In one aspect, a method includes providing a quantum computer with data representing a topology of the communication network, the topology comprising a graph of vertices representing network devices and edges representing connections between network devices; receiving, from the quantum computer, data representing a first subset of network devices, wherein the first subset comprises a dominating set of vertices or a vertex cover for the graph; monitoring network devices in the first subset to generate alarm data representing triggered network device alarms; providing the alarm data to a quantum computer; receiving, from the quantum computer, data representing a second subset of network devices, wherein the second subset comprises a set cover for the alarm data and the network devices in the second subset comprise diagnosed sources of failures in the communication network.

Abstract: A device determines, from a network slice template associated with a network slice, a quality of service (QoS) profile for the network slice that includes performance metrics for corresponding QoS parameters associated with providing a service. The device monitors performance of the network slice in association with the QoS profile, and determines, based on the performance, that a performance indicator for a QoS parameter of the network slice is outside a threshold range of a performance metric. The device determines, based on the performance information and the QoS profile, a slice modification to the network slice template for the network slice, where the slice modification is configured to cause the performance indicator to be within the threshold range of the performance metric. The device causes a network slice orchestrator to update an instantiation of the network slice according to the slice modification and the network slice template.

Abstract: Examples of the present disclosure provide apparatuses and methods for determining a vector population count in a memory. An example method comprises determining, using sensing circuitry, a vector population count of a number of fixed length elements of a vector stored in a memory array.

Abstract: A system includes a memory device and a processing device coupled to the memory device. The memory processing device can perform operations including receiving data indicative of occurrence of a plurality of events. The processing device can perform operations including determining an event log type for each of the plurality of events. The processing device can perform operations including storing an identifier associated with each of the determined event log types. The processing device can perform operations including updating a counter value associated with each identifier in response to occurrence of an event associated with the respective identifier.

Abstract: Examples of the present disclosure provide apparatuses and methods for smallest value element or largest value element determination in memory. An example method comprises: storing an elements vector comprising a plurality of elements in a group of memory cells coupled to an access line of an array; performing, using sensing circuitry coupled to the array, a logical operation using a first vector and a second vector as inputs, with a result of the logical operation being stored in the array as a result vector; updating the result vector responsive to performing a plurality of subsequent logical operations using the sensing circuitry; and providing an indication of which of the plurality of elements have one of a smallest value and a largest value.

Abstract: A device may receive audio data identifying a plurality of speakers and may process the audio data, with a plurality of clustering models, to identify a plurality of speaker segments. The device may determine a plurality of diarization error rates for the plurality of speaker segments and may identify a plurality of errors in the plurality of speaker segments. The device may select rectification models to rectify the plurality of errors and may segment and/or re-segment the audio data with the rectification models to generate re-segmented audio data. The device may determine a plurality of modified diarization error rates for the plurality of speaker segments based on the re-segmented audio data and may select one of the plurality of speaker segments based on the plurality of modified diarization error rates. The device may calculate an empathy score based on the selected speaker segment and may perform actions based on the empathy score.

Abstract: This disclosure describes, in part, techniques for generating captions for audio content items. For instance, a system may store a user profile that is associated with audio content items. When a user associated with the user profile requests captions, the system may determine which audio content items have available captions and which audio content items do not have available captions. For the audio content items that do not have available captions, the system may determine priorities for the audio content items. The system may then cause the captions to be generated based on the priorities. When the captions are generated, the system may update statuses of the audio content items to indicate that the captions are available. The system may further store the captions in a database that is accessible to the user.

Abstract: A system includes a memory device and a processing device coupled to the memory device. The memory processing device can perform operations including receiving data indicative of occurrence of a plurality of events. The processing device can perform operations including determining an event log type for each of the plurality of events. The processing device can perform operations including storing an identifier associated with each of the determined event log types. The processing device can perform operations including updating a counter value associated with each identifier in response to occurrence of an event associated with the respective identifier.

Abstract: Examples of the present disclosure provide apparatuses and methods for span mask generation. An example method comprises creating, using sensing circuitry, a number of bit vectors, wherein each of the number of bit vectors includes a repeating pattern based on a size of the number of bit vectors and a particular mask depth.