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: Embodiments of systems and methods for verification of software packages prior to deployment on an Information Handling System (IHS) are described. In an illustrative, non-limiting embodiment, an IHS may include a Baseboard Management Controller (BMC) having computer-executable instructions for creating a partition having a unique name in response to a request from the IHS. The BMC then transmits the unique name to the IHS, and exposes the created partition to the IHS in which a software upgrade package image is copied to the partition when the exposed partition becomes available to the IHS. The BMC may then deploy the software package on the BMC, wherein the software package comprises executable instructions for operating the BMC.

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 dynamic digital information retrieval are provided herein. An example computer-implemented method includes training a machine learning object detection model using server component images and one or more features of the server component images; determining a type of server device captured by at least one camera-derived input, wherein determining the type of server device comprises analyzing the at least one camera-derived input using the machine learning object detection model; identifying one or more server components captured by the at least one camera-derived input by analyzing, within a context of the determined type of server device, the at least one camera-derived input using the machine learning object detection model; and outputting, to at least one display, information pertaining to the identified server components, wherein the information is retrieved from a data source related to the determined type of server device.

Abstract: Methods, apparatus, and processor-readable storage media for dynamic digital information retrieval are provided herein. An example computer-implemented method includes training a machine learning object detection model using server component images and one or more features of the server component images; determining a type of server device captured by at least one camera-derived input, wherein determining the type of server device comprises analyzing the at least one camera-derived input using the machine learning object detection model; identifying one or more server components captured by the at least one camera-derived input by analyzing, within a context of the determined type of server device, the at least one camera-derived input using the machine learning object detection model; and outputting, to at least one display, information pertaining to the identified server components, wherein the information is retrieved from a data source related to the determined type of server device.