Abstract: Systems and methods provide adaptive collection of telemetry. A telemetry orchestrator of a IHS (Information Handling System) collects telemetry related to a session used by the IHS to access a protected resource of a zero-trust environment, where the telemetry is collected based on a telemetry definition received from a policy decision point of the zero-trust environment. The telemetry orchestrator of the IHS monitors for updates to the telemetry definition, where the updates are generated by the policy decision point of the zero-trust environment. The telemetry orchestrator adjusts measurements by one or more of the sensors of the IHS based on updates to the telemetry definition received from the policy decision point. Telemetry that is generated based on the adjusted measurements is transmitted by the telemetry orchestrator to one or more destinations specified in the update telemetry definition.

Abstract: Systems and methods provided adaptive collection of telemetry. A policy decision point of a zero-trust computing environment receives an indication of a change in risk posture within the environment. The policy decision point identifies a telemetry definition specifying telemetry being collected by one or more IHSs that are currently accessing a protected resource of the zero-trust computing environment. The telemetry definition is updated to specify adjusted telemetry to be collected by an IHS that is currently accessing the protected resource and the updated telemetry definition is transmitted to the IHS. Based on the updated telemetry definition received from the policy decision point, the IHS adjust measurements by one or more of the sensors of the IHS. Telemetry generated based on the adjusted measurements is transmitted by the IHS to one or more destinations specified in the updated telemetry definition.

Abstract: An information handling system includes a hardware processor executing code instructions of an artificial intelligence (AI) productivity tool subagent to gather system/component context telemetry data and to invoke a telemetry data-to-vectorized telemetry intent machine learning (ML) model algorithm to vectorize the system/component context telemetry data and normalize each dimension in the vectorized system/component context telemetry data to a telemetry intent value using a hardware-specific normalization factor. The hardware processor executes code instructions of a query input-to-intent ML model algorithm to generate a query intent value for received user query input and concatenate the telemetry intent value with the query intent value to produce a unified telemetry and query intent value.

Abstract: A system and method for operating an on the box (OTB) artificial intelligence (AI) productivity tool comprising an embedded controller executing code instructions of a platform level capability gathering module to receive a notice of functional adjustment for a hardware component communicating with the embedded controller using one of several available communication protocols and the embedded controller to transmit an updated firmware capability to the OTB AI productivity tool pursuant to the notice of functional adjustment.

Abstract: A system and method of providing an intent action feedback summary at an information handling system comprising a hardware processor executing computer-readable program code instructions of an artificial intelligence (AI) productivity tool software module to receive a user query input and identify a plurality of responsive capabilities associated with AI productivity tool-enablable software applications and execute a transaction software module to determine that a capability intent action responsive to one of the identified plurality of responsive capabilities requires user approval or additional user chat input.

Abstract: An information handling system executing computer readable code instructions for an on the box artificial intelligence productivity tool comprising a hardware processor receiving a user query input within a current chat session with a user, executing computer-readable code instructions to perform a semantic similarity search at a main operating system (OS) level comparing a generated query input intent value to capability intent values generated from natural language descriptions of secondary OS capabilities and other software capabilities to identify a best match capability for the received user query input having a highest semantic similarity search score, storing the best match secondary OS capability in a non-volatile shared memory mailbox location, rebooting into a secondary lightweight OS with a secondary OS AI productivity tool retrieving the best match secondary OS capability for execution by a secondary lightweight OS and continuing the current chat session with a secondary OS conversational interfac

Abstract: A system and method comprising a hardware processor to execute computer-readable program code instructions of a diagnostic subagent to detect damage to a first port at the information handling system via port testing and generate diagnostic port data describing the first port that is damaged among a plurality of ports at the information handling system and execute a port identification and guidance module to gather baseline port mapping data describing mapping of hardware components including the ports within the information handling system and capabilities of those hardware components and the plurality of ports. Execute the port identification and guidance module to input the diagnostic port data and baseline port mapping data into a baseline mapping-to-text machine learning (ML) to generate user-guided text, audio, or image describing which port to use in lieu of the first port that is damaged.

Abstract: An information handling system executing computer readable code instructions for an on the box artificial intelligence (AI) productivity tool comprising a hardware processor receiving a user query input requesting erasing a drive memory of the information handling system, executing computer-readable code instructions to perform a semantic similarity search at a main operating system (OS) level comparing a generated query input intent value to capability intent values generated from natural language descriptions of secondary OS capabilities and other software capabilities to identify a best match secondary OS capability for the received user query input having a highest semantic similarity search score, storing the best match secondary OS capability in a non-volatile shared memory mailbox location, rebooting into a secondary lightweight OS executing a secondary OS AI productivity tool to retrieve the best match secondary capability for execution by the secondary lightweight OS to erase the drive memory.

Abstract: An information handling system includes a hardware processor to execute computer-readable program code instructions of an information technology decision maker (ITDM) capability management system to receive assigned artificial intelligence (AI) productivity scores correlated to how executed capability intent actions at a subset of a plurality of node information handling systems in an enterprise have improved user productivity at those plurality of node information handling systems based on detected changes resource telemetry data. The ITDM capability management system to generate a ranked listing of the plurality of responsive capability intent actions based on the assigned AI productivity scores and determine an action payload comprising one or more highest AI productivity score responsive capability intent actions and propagate that action payload to each of the plurality of node information handling systems within the enterprise for implementation.

Abstract: An information handling system operating an on-the-box artificial intelligence (AI) productivity tool comprising a hardware processor executing machine readable code instructions to receive an initial application capabilities list for AI productivity tool enableable software applications at a capabilities database and receive a general issued configuration policy with alternate settings from a management server dictating controlled operational modes of the information handling system.

Abstract: An information handling system managed by an enterprise management system and operating an on-the-box artificial intelligence productivity tool may comprise a hardware processor executing machine readable code instructions to generate vectorized capability intent values from natural language descriptions of capabilities including a capability-with-reboot requiring reboot to a basic input/output system (BIOS) and a vectorized query input intent value for a user query input requesting action from information handling system, compare the query input intent value to the capability intent values to identify a best match responsive capability-with-reboot for the received user query input having a capability intent value that generates a highest semantic similarity search score and requiring authorization for execution of pre-boot machine readable code instructions for the best match capability-with-reboot received from the enterprise management system, store it in a pre-boot memory partition, reboot, and execute th

Abstract: An information handling system executing computer readable code instructions for an on the box artificial intelligence (AI) productivity tool may comprise a hardware processor executing computer-readable program code instructions for generating a recommendation or query intent value for a recommendation intervention action or user query input requesting a capability action to be taken by an AI productivity tool-enableable software application executing on the information handling system, performing a semantic similarity search comparing capability intent values for capability intent actions to the recommendation or query intent value to identify a best match capability for the received user query input or recommendation intervention action having a capability intent value that meets a threshold semantic similarity search score, determining that execution of the best match capability requires assistance from an information technology decision maker (ITDM) for an enterprise, and automatically generating and tra

Abstract: An information handling system executing computer readable code instructions for an on the box (OTB) artificial intelligence (AI) productivity tool may comprise a hardware processor executing computer-readable code instructions to access gathered natural language descriptions of application, firmware, and hardware capabilities, receive an error indicating a software, firmware, or hardware failure or malfunction, determine, via a trained neural network of an automatic predictive capability adjustment system, an adjustment to an adjustable hardware, firmware, or software configuration associated with the error. The OTB AI productivity tool to generate a natural language description of a recommendation intervention action to perform the determined adjustment and generate an intervention recommendation input intent value for semantic similarity matching to responsive capability intent values, and execute a best match responsive capability in response to prompted user query input notification or approval.

Abstract: A system and method of executing code instructions for an artificial intelligence (AI) productivity tool software module comprising a hardware processor receiving user-query input and receiving location data describing a current location and identification of personal area network (PAN) devices at a workspace. With historic information handling system usage data, identification of the PAN devices and the user query input, the hardware processor executing code instructions of a PAN device preferences AI software application to identify a capability intent semantically matched with the user-query input, the identification of the PAN devices, and the historic information handling system usage patterns to identify a responsive capability to automatically select and operably couple the information handling system and one or more of the identified PAN devices in response to the user query input, including meeting security communication policies for the information handling system and the PAN devices.

Abstract: An information handling system executing computer readable code instructions for an on the box (OTB) artificial intelligence (AI) productivity tool may comprise a hardware processor executing computer-readable code instructions to access gathered natural language descriptions of application, firmware, and hardware capabilities, receive an error indicating a software, firmware, or hardware failure or malfunction, determine, via a trained neural network, determine that the error indicates imminent failure of a hard disk drive (HDD), generate a natural language description of a recommendation to replace the HDD, generate an intervention recommendation input intent value for the natural language description, and identify and execute a best match responsive capability for the received natural language description having a capability intent value that generates a highest semantic similarity search score generated through comparison of the intervention recommendation input intent value and a plurality of capability

Abstract: A system and method of prioritizing among built-in and plug-in capabilities executed at the information handling system includes a hardware processing device and a data storage device, where the hardware processor executes computer-readable program code instructions of plural artificial intelligence (AI) productivity tool software modules from a manufacturer and a software vendor to receive a user query input and invoke a plurality of machine learning model algorithms to identify a plurality of responsive capabilities from built-in AI productivity tool-enablable software and plug-in AI productivity tool-enablable software.

Abstract: An information handling system includes a hardware processor with the hardware processor executing an AI productivity tool software module to invoke a plurality of ML model algorithms to identify a responsive capability intent action based on received user-query input, a system environment component discovery software application to gather runtime telemetry data describing a current consumption state of a plurality of available in-band, side-band, and networked ML model algorithm execution provider hardware processors, and a workload orchestrator to receive the runtime telemetry data and determine when the workload orchestrator switches from a first ML model algorithm execution provider hardware processor used to execute at least one of the plurality of ML model algorithms to a second ML model algorithm execution provider hardware processor having less active processing and that is capable.

Abstract: An information handling system comprising a hardware processor to execute computer-readable program code instructions of a first unprivileged artificial intelligence (AI) productivity-tool software process for operations of an AI productivity tool software module to detect receipt of audio/video user query input data and generate a first encryption key for transmission to an audio/video encryption driver and a second unprivileged AI productivity-tool software process.

Abstract: Systems and methods for contextual camera controls during a collaboration session 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 coupled to the heterogeneous computing platform, where the memory comprises 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: determine a location of the IHS during a collaboration session, and in response to the determination, change a camera setting.

Abstract: Systems and methods for remotely provisioning facial recognition data are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) shareable among a plurality of users in a hoteling environment may include: a heterogeneous computing platform; 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 a plurality of devices of the heterogeneous computing platform, 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: transmit a request to a server to receive facial recognition data associated with a given one of the plurality of users assigned to the IHS, and receive the facial recognition data.