Abstract: Techniques are generally described for machine learning exampled-based annotation of image data. In some examples, a first machine learning model may receive a query image comprising a first depiction of an object-of-interest. In some examples, the first machine learning model may receive a target image representing a scene in which a second depiction of the object-of-interest is visually represented. In various examples, the first machine learning model may generate annotated output image data that identifies a location of the second depiction of the object-of-interest within the target image. In some examples, an object detection model may be trained based at least in part on the annotated output image data.

Abstract: Devices and techniques are generally described for content classification. In some examples, first item data representing a first item may be received. The first item data may include a plurality of prediction scores output by a machine learning model. Each prediction score of the plurality of prediction scores may be associated with a respective label of a plurality of labels. In some examples, a set of one or more labels among the plurality of labels may be predicted. The set of labels may be predicted as being applicable to the first item for classification of the first item. A determination may be made that the set of one or more labels represents a complete set of labels applicable to the first item. In some examples, the first item may be classified based on the set of one or more labels.

Abstract: Examples described herein relate to during a boot of a power supply unit (PSU) connected to a computer platform, circuitry to receive a firmware identifier and manufacturer identifier associated with the PSU and determine whether the PSU is approved to utilize. In some examples, based on, at least, authentication of the firmware identifier and manufacturer identifier of the PSU, the circuitry is to permit access to data and/or power from the PSU. In some examples, based on, at least, failure to authenticate the firmware identifier or manufacturer identifier of the PSU, the circuitry is to deny access to data and/or power from the PSU.

Abstract: A method and system for intelligent power distribution management. Specifically, the disclosed method and system propose allocating (and deallocating) reserve or supplemental electrical power to host devices dynamically based on intelligent analyses of host device telemetry including, but not limited to, workload criticality, workload computing resource utilization, hardware configuration metadata, various operational parameters describing host device state, and measurements (as well as other information) pertinent to electrical power usage.

Abstract: Methods, apparatus, and processor-readable storage media for automated device power conservation using machine learning techniques are provided herein. An example computer-implemented method includes obtaining usage-related data from one or more processing devices; determining at least one usage pattern for the one or more processing devices by processing the obtained usage-related data using one or more machine learning techniques; automatically generating, based at least in part on the at least one determined usage pattern, instructions pertaining to controlling one or more power states of the one or more processing devices; and performing at least one automated action based at least in part on the generated instructions.

Abstract: A method and system for intelligent power distribution management. Specifically, the disclosed method and system propose allocating (and deallocating) reserve or supplemental electrical power to host devices dynamically based on intelligent analyses of host device telemetry including, but not limited to, workload criticality, workload computing resource utilization, hardware configuration metadata, various operational parameters describing host device state, and measurements (as well as other information) pertinent to electrical power usage.

Abstract: Methods, apparatus, and processor-readable storage media for automated device power conservation using machine learning techniques are provided herein. An example computer-implemented method includes obtaining usage-related data from one or more processing devices; determining at least one usage pattern for the one or more processing devices by processing the obtained usage-related data using one or more machine learning techniques; automatically generating, based at least in part on the at least one determined usage pattern, instructions pertaining to controlling one or more power states of the one or more processing devices; and performing at least one automated action based at least in part on the generated instructions.

Abstract: An information handling system includes first and second power supplies, and a management controller. The power supplies are configured to operate in a first power mode to supply power to the information handling system and in a second power mode to shut down from supplying power to the information handling system. The management controller is configured in a normal operation mode to set the first power supply to the first power mode and set the second power supply in the second power mode. The management controller is configured in a test operation mode to set the second power supply to the first power mode, to set the first power supply to the second power mode, to determine whether the second power supply is operating within a first limit, and when the second power supply is not operating within the first limit, to provide a first indication that the second power supply is failing.

Abstract: An information handling system may include a first power supply for a first system, a second power supply for a second system, and a management controller. The management controller may detect that the first power supply has failed, receive first information from the first system related to the operation of the first power supply prior to the failure of the first power supply, receive second information from the second system associated with the second power supply, and determine a probability of failure of the second power supply based upon a comparison of the first information with the second information.

Abstract: An information handling system includes first and second power supplies, and a management controller. The power supplies are configured to operate in a first power mode to supply power to the information handling system and in a second power mode to shut down from supplying power to the information handling system. The management controller is configured in a normal operation mode to set the first power supply to the first power mode and set the second power supply in the second power mode. The management controller is configured in a test operation mode to set the second power supply to the first power mode, to set the first power supply to the second power mode, to determine whether the second power supply is operating within a first limit, and when the second power supply is not operating within the first limit, to provide a first indication that the second power supply is failing.

Abstract: An information handling system may include a first power supply for a first system, a second power supply for a second system, and a management controller. The management controller may detect that the first power supply has failed, receive first information from the first system related to the operation of the first power supply prior to the failure of the first power supply, receive second information from the second system associated with the second power supply, and determine a probability of failure of the second power supply based upon a comparison of the first information with the second information.

Abstract: Methods, systems and devices are provided for configuring an airflow cooling system shared by a plurality of IHSs (Information Handling Systems). An initial fan speed is set by a chassis manager that controls airflow cooling shared by the IHSs. The chassis manager broadcasts the initial fan speed to the plurality of IHSs. Each IHS receives the initial fan speed broadcast and determines its own fan speed requirements. If an IHS requires a fan speed greater than the initial fan speed, the IHS broadcasts a fan speed request. Each IHS continues to monitor fan speed broadcasts and broadcasts a request if its determined fan speed is greater than the most recent broadcast. The IHS that broadcasts the greatest fan speed request is designated as the dominant IHS. The chassis manager sets the airflow cooling system fan speed based on the fan speed requests broadcast by the dominant IHS.

Abstract: Methods, systems and devices are provided for configuring an airflow cooling system shared by a plurality of IHSs (Information Handling Systems). An initial fan speed is set by a chassis manager that controls airflow cooling shared by the IHSs. The chassis manager broadcasts the initial fan speed to the plurality of IHSs. Each IHS receives the initial fan speed broadcast and determines its own fan speed requirements. If an IHS requires a fan speed greater than the initial fan speed, the IHS broadcasts a fan speed request. Each IHS continues to monitor fan speed broadcasts and broadcasts a request if its determined fan speed is greater than the most recent broadcast. The IHS that broadcasts the greatest fan speed request is designated as the dominant IHS. The chassis manager sets the airflow cooling system fan speed based on the fan speed requests broadcast by the dominant IHS.