Abstract: An information handling system includes a battery, an embedded controller, and a processor. The embedded controller collects a battery charge status for the battery, and provides the battery charge status to the processor. The processor also receives data indicating a current battery discharge rate. The processor determines a second battery discharge rate based on operations to be performed during a period of time. The processor also determines a needed battery charge level at a start of the period of time. Based on the battery charge status, the current battery discharge rate, the second battery discharge rate, and the needed battery charge level, the processor sets the information handling system in a state to achieve the battery charge level.

Abstract: Embodiments of systems and methods for platform framework configuration state management are described. A platform framework of an IHS (Information Handling System) generates a resource dependency graph based on registrations of a plurality of platform framework participants, wherein the registrations of the participants specify use of resources accessed via the platform framework. A change in context of operation of the IHS is determined. Based on the context change, a change is determined in the availability of resources accessed via the platform framework. Based on the resource dependency graph, registered participants are identified that are affected by the change in platform framework resource availability. The affected participants are notified of the change in platform framework resource availability. In some embodiments, the registrations of the participants may specify a communication handle for notifying the participant of changes in the resource dependency graph.

Abstract: Systems and methods for managing network controllers in heterogenous computing platforms of IHSs (Information Handling Systems) are described. In an illustrative, non-limiting embodiment, a heterogeneous computing platform includes devices and a memory storing firmware instructions. Based on execution of these firmware instructions by a respective device, a corresponding firmware service is provided such that one of the devices operates as an orchestrator. The orchestrator receives reports of changes in context of operation of the IHS by a user and determines network controller settings that are mapped to the reported user context, where the network controller settings modify operations by one or more network controllers of the IHS. The orchestrator configures the network controllers of the IHS using the network controller settings, and thus adjusts the network controller of the IHS in response to the change in user context.

Abstract: Embodiments of systems and methods for platform framework authentication are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: receive, via an authentication provider registered with a platform framework via an Application Programming Interface (API), an authentication credential; and send the authentication credential to a plurality of applications registered with the platform framework.

Abstract: Systems and methods for managing consumption of alternating-current (AC) power by an Information Handling System (IHS). In a non-limiting embodiment, an IHS may include: a heterogeneous computing platform comprising a plurality of devices and a memory, the memory having a plurality of sets of firmware instructions, where each of the sets, upon execution by a respective device, enables that device to provide a corresponding firmware service, and where at least one of the devices operates as an orchestrator configured to: execute or instruct one or more devices to execute one or more Artificial Intelligence models usable to characterize usage profiles based, at least in part, upon context or telemetry data received from at least a subset of the plurality of devices; and, based upon the usage profiles, determine whether to allow a battery to power the IHS at least partially while the IHS is coupled to an AC power source.

Abstract: Systems and methods for battery management in heterogenous computing platforms. In a non-limiting embodiment, an Information Handling System may include a heterogeneous computing platform having a plurality of devices and a memory coupled to the platform, where the memory includes a plurality of sets of firmware instructions, each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and at least one of the plurality of devices operates as an orchestrator configured to: receive context or telemetry data from at least a subset of the plurality of devices; and execute or instruct one or more selected devices among the plurality of devices to execute one or more Artificial Intelligence models usable to manage a charging or discharging operation of a battery based, at least in part, upon the context or telemetry data.

Abstract: Systems and methods for enabling contextual privacy controls in heterogenous computing platforms are described. In a non-limiting embodiment, an Information Handling System (IHS) may include a heterogeneous computing platform having a plurality of devices and a memory coupled to the platform, the memory including a plurality of sets of firmware instructions that, upon execution by a respective device among the plurality of devices, enable the respective device to provide a corresponding firmware service, where at least one of the plurality of devices operates as an orchestrator configured to: execute or instruct a device to execute an Artificial Intelligence model usable to identify one of a plurality of privacy modes to be applied to the IHS based, at least in part, upon context data received from at least a subset of the plurality of devices; and, based upon the identified privacy mode, modify one or more IHS settings.

Abstract: Systems and methods for firmware-based switching between user profiles in a heterogenous computing platform. In an illustrative, non-limiting embodiment, an Information Handling System may include: a heterogeneous computing platform comprising a plurality of devices, and a memory coupled to the platform having a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device, enables the respective device to provide a firmware service, and at least one of the devices operates as an orchestrator configured to: execute or instruct a device to execute an Artificial Intelligence model configured to produce an inference result based, at least in part, upon context or telemetry data received from a subset of the plurality of devices; select one of a plurality of user profiles based upon the inference result; and apply a setting associated with the selected user profile to a selected device.

Abstract: Systems and methods for enabling localized image enhancements in heterogenous computing platforms are described. In an illustrative, non-limiting embodiment, an Information Handling System may include a heterogeneous computing platform having a plurality of devices and a memory coupled to the heterogeneous computing platform, where the memory includes a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to: receive context or telemetry data from a subset of one or more of the plurality of devices; and instruct a selected device among the plurality of devices to execute an Artificial Intelligence model configured to produce a localized image based, at least in part, upon the context or telemetry data.

Abstract: Systems and methods for enabling collaboration session migration in heterogenous computing platforms. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a heterogeneous computing platform including a plurality of devices and a memory coupled to the platform, the memory having a plurality of sets of firmware instructions that, upon execution by a respective device among the plurality of devices, enable the respective device to provide a corresponding firmware service, and at least one of the plurality of devices operates as an orchestrator configured to: execute or instruct a device selected among the plurality of devices to execute an AI model usable to identify a migration opportunity for an ongoing collaboration session based, at least in part, upon context or telemetry data received from at least a subset of the plurality of devices, and notify another IHS to handle at least a portion of the ongoing collaboration session.

Abstract: Systems and methods for firmware-based user persona discovery in a heterogenous computing platform. In a non-limiting embodiment, an Information Handling System may include: a heterogeneous computing platform having a plurality of devices, and a memory coupled to the heterogeneous computing platform, where the memory includes a plurality of sets of firmware instructions, each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and at least one of the plurality of devices operates as an orchestrator configured to: receive context or telemetry data from at least a subset of the plurality of devices, and instruct one or more selected devices to execute one or more Artificial Intelligence models configured to discover a user persona associated with a user of the IHS based, at least in part, upon the context or telemetry data.

Abstract: Systems and methods for detecting video gaming sessions in heterogenous computing platforms are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include a heterogeneous computing platform comprising a plurality of devices and a memory coupled to the heterogeneous computing platform, where the memory comprises a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to: receive context or telemetry data from at least a subset of the plurality of devices, and instruct a device among the plurality of devices to execute an Artificial Intelligence (AI) model configured to detect a video gaming session based, at least in part, upon the context or telemetry data.

Abstract: Systems and methods for voice-assisted wireless docking in heterogenous computing platforms are described. In an illustrative, non-limiting embodiment, an Information Handling System may include a heterogeneous computing platform having a plurality of devices, and a memory coupled to the heterogeneous computing platform, where the memory includes a plurality of sets of firmware instructions, each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and at least one of the plurality of devices operates as an orchestrator configured to: detect a predetermined utterance or direct a first one of the plurality of devices to detect the predetermined utterance; and, in response to the detection, direct a second one of the plurality of devices to: (a) connect the IHS to a wireless dock, or (b) disconnect the IHS from the wireless dock.

Abstract: Systems and methods for managing embedded Subscriber Identity Module (eSIM) credentials in heterogenous computing platforms. In a non-limiting embodiment, an Information Handling System may include: a heterogeneous computing platform having a plurality of devices and a memory coupled to the platform, where the memory includes firmware instructions that, upon execution by a respective device among the plurality of devices, enable a respective device to provide a corresponding firmware service, and at least one of the devices operates as an orchestrator configured to: deploy or instruct another device to deploy an AI model configured to produce an inference result based, at least in part, upon context or telemetry data received from a subset of the devices; select an eSIM profile based upon the inference result; and transmit a credential within the selected eSIM profile to a wireless controller configured to authenticate the credential.

Abstract: Systems and methods for deploying instances of Artificial Intelligence (AI) models having different levels of complexity in a heterogenous computing platform are described. In an embodiment, an Information Handling System (IHS), may include a heterogeneous computing platform comprising a plurality of devices and a memory having a plurality of sets of firmware instructions that, upon execution by a respective device, enable the respective device to provide a corresponding service, and where at least one of the devices operates as an orchestrator configured to: select an instance of an AI model among a plurality of instances of the AI model based, at least in part, upon context or telemetry data received from at least a subset of the plurality of devices, where each of the plurality of instances of the AI model has a different level of complexity, and instruct a device to execute the selected instance of the AI model.

Abstract: Systems and methods for usage detection and notification in a heterogenous computing platform are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include a heterogeneous computing platform comprising a plurality of devices and a memory coupled to the platform, where the memory comprises a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to: receive context or telemetry data from at least a subset of the plurality of devices and instruct one or more selected devices to execute one or more Artificial Intelligence (AI) models configured to characterize one or more workloads executed by the IHS based, at least in part, upon the context or telemetry data.

Abstract: Systems and methods for Artificial Intelligence (AI) model characterization and offloading in a heterogenous computing platform are described. In an embodiment, an Information Handling System (IHS) may include: a heterogeneous computing platform including a plurality of devices and a memory, where the memory includes a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device, enables it to provide a corresponding service, and where at least one of the devices operates as an orchestrator configured to: receive a characterization result from a first device, where the first device is configured to execute a first AI model configured to characterize a second AI model executed by a second device, and, prior to a subsequent execution of the second AI model, assign the second AI model to a third device based, at least in part, upon the characterization result.

Abstract: Systems and methods for runtime control of Artificial Intelligence (AI) model parameters in a heterogenous computing platform are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include a heterogeneous computing platform comprising a plurality of devices and a memory coupled to the platform, where the memory comprises a plurality of sets of firmware instructions, where each of the sets of firmware instructions, upon execution by a respective device among the plurality of devices, enables the respective device to provide a corresponding firmware service, and where at least one of the devices operates as an orchestrator configured to: receive context or telemetry data from at least a subset of the plurality of devices, and instruct a device among the plurality of devices to modify a parameter of an AI model executed by the device based, at least in part, upon the context or telemetry data.

Abstract: Systems and methods for detecting collaboration sessions and other workloads in a heterogeneous computing platform are described. In some embodiments, an Information Handling System (IHS) may include a heterogeneous computing platform having a plurality of devices and a memory coupled to the heterogeneous computing platform, where the memory includes a plurality of sets of firmware instructions, where each set of firmware instructions, upon execution by a respective device, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to collect telemetry from the plurality of devices and detect a collaboration session based, at least in part, upon the telemetry.

Abstract: Systems and methods for managing performance during collaboration sessions in heterogenous computing platforms are described. In some embodiments, an Information Handling System (IHS) may include a heterogeneous computing platform comprising a plurality of devices and a memory coupled to the heterogeneous computing platform, where the memory includes a plurality of sets of firmware instructions, where each set of firmware instructions, upon execution by a respective device, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to: receive, during a collaboration session, contextual data usable to identify at least one of: user presence, or user engagement; and modify an IHS performance setting based, at least in part, upon the contextual data.