Dell Products Inc.

Dell & Products L.p.

Daniel Lawrence Hamlin

Vivek Viswanathan Iyer

Srikanth Kondapi

Charles D Robison

Todd Erick Swierk

Charles Delbert Robison, Jr

Ibrahim Sayyed

Suraj M Varma

Manuel Novoa

Travis Christian North

Nikhil Manohar Vichare

Minhaj Ahmed

Gokul Thiruchengode Vajravel

Yagiz Can Yildiz

Danilo Ong Tan

Keith M Alfano

Mandy Christina Phelps

Banu Alpay Waldman

Adolfo Sandor Montero

Shekar Babu Suryanarayana

Nicholas Diciurcio Grobelny

Balasingh Ponraj Samuel

Karun Palicherla Reddy

Yung-Sheng Lin

Hariprasad Janardana Iyer

Timothy Carlyle Shaw

Geroncio Ong Tan

Joseph Kozlowski

Amy Christine Nelson

Allen Brian McKittrick

Christian L Critz

James T Gillon

Warren Wade Robbins

Alan H Abdelhalim

Deeder M Aurongzeb

John Trevor Morrison

Jace William Files

Parminder Singh Sethi

Michiel Sebastiaan Emanuel Petrus Knoppert

Ricardo Luis Martinez

Andrew T Fausak

Srinivas Kamepalli

Ryan Nicholas Comer

Frank Howard Molsberry

James Damon Trim

Fernando L Guerrero

Joshua Alperin

Preeth Kartikeyan Srinivasan

Carrie Elaine Gates

Frank Quintanilla, Iii

Kenneth Wade Stufflebeam

Barry Paul Easter

Andelon Xuan Tra

Malathi R

Julia A Ogbevoen

Shun-Tang Hsu

Pradeep Gopal

Peng Lip Goh

Sumanth Vidyadhara

Anand Prakash Joshi

Stefan Peana

Abu Shaher Sanaullah

Lakshmi Saroja Nalam

Robert C Brooks

John Kelly

Richard William Schuckle

Girish S Dhoble

Kai Wang

Harpreet S Narula

Vivekanandh Narayanasamy Rajagopalan

Ankit Kumar

Marcin M Nowak

Malathi Ramakrishnan

Rohit Gosain

Jonathan C Giffen

Bryan James Thornley

Brijesh Kumar Mishra

Yao-Hsien Huang

Sinem Kockan

Justin Walter Johnson

Praveen Kumar

Maheshwar Dattatri

Venkata Rama Krishna Rao Atta

Chad Skipper

Allen B Mckittrick

Yao Hsien Huang

Alberto Nieves

Thippeswamy D R

Nathan Benjamin Buch

Juan C Agudelo

Jeffrey S Myers

Janardan Pradeep Gopal

Systems and methods for firmware-based Artificial Intelligence (AI) model authorization in heterogenous computing platforms are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a heterogeneous computing platform having a plurality of devices and a memory including a plurality of sets of firmware instructions, where the firmware instructions, upon execution by a respective device among the plurality of devices, enable the respective device to provide a firmware service, and at least one of the devices operates as an orchestrator configured to: receive a request for deployment, loading, extraction, launch, or release of AI model data; and at least one of: in response to a successful authentication of the request, allow the deployment, extraction, launch, or release of the AI model data; or in response to a failed authentication of the request, deny the deployment, extraction, launch, or release of the AI model data.

Firmware-based artificial intelligence (AI) model authorization in heterogeneous computing platforms

Embodiments of systems and methods are provided for provisioning a database of trusted users stored locally on one or more information handling systems. The systems and methods disclosed herein may utilize a database of trusted users (otherwise referred to as a trusted multi-user database, or TMU database), a database template and/or policy stored within a remote system (e.g., a cloud or backend server) to remotely manage and provision a TMU database stored locally within one or more information handling systems. In doing so, the systems and methods disclosed herein may be used to securely back-up and restore a TMU database stored locally with an IHS, remotely manage enrollment and provisioning of a TMU database stored locally within one or more information handling systems based on policy, and apply TMU configuration settings globally to the TMU databases stored locally within a plurality of information handling systems.

Systems and methods for provisioning a database of trusted users stored within one or more information handling systems

Systems and methods are provided for context-based docking of an IHS (Information Handling System) that includes a heterogeneous computing platform. In an illustrative, non-limiting embodiment, an IHS may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the IHS to: detect a docking station in proximity to the IHS based on a wireless signal generated by the docking station; determine context information for the proximity of the IHS to the docking station, wherein the context information comprises a strength of the wireless signal of the docking station and further comprises movement of the IHS; infer whether the user intends to dock the IHS based on the determined context for the proximity of the IHS to the docking station; and couple the IHS to the docking station in response to the inferred intent.

Systems and methods for context-based docking of information handling systems

Techniques determining a data migration strategy in an edge network including a plurality of edge nodes is described. One example method includes determining a configuration for each of the plurality of edge nodes in the edge network; predicting a future workload associated with each of the plurality of edge nodes in the edge network based on an observed past workload for each of the plurality of edge nodes; receiving a migration request for a particular edge node in the plurality of edge nodes; and identifying a target edge node in the plurality of edge nodes that is suitable for handling the predicted future workload of the particular edge node, wherein the identifying is based at least in part on the determined configuration of the particular edge node and the target edge node, and on the predicted future workload of the particular edge node and the target edge node.

Determining data migration strategy in heterogeneous edge networks

A security lock is provided for a mobile device. The security lock includes a pair of locking elements and a pair of electromechanical actuators. Each locking element has a profile configured to complement a profile of a locking tab of an external locking assembly. Each electromechanical actuator is configured to engage an associated one of the locking elements to lock the locking tab to the mobile device, and to disengage the associated locking element to unlock the locking tab.

Integrated security lock

An information handling system has a storage device including a telemetry log, a BIOS configured to provide BIOS status data and BIOS security data, an OS configured to provide OS status data and OS security data, and a security management module. The security management module determines whether the information handling system is in a low-threat state or a high-threat state. When the information handling system is in the low-threat state, the security management module directs the BIOS to store the BIOS status data to the telemetry log and the OS to store the OS status data to the telemetry log. When the information handling system is in the high-threat state, the security management module directs at least one of the BIOS to store the BIOS security data and the OS to store the OS security data.

Security context aware telemetry

An information handling system includes top and bottom housings, multiple fixed locking magnets secured within the bottom housing, multiple movable locking magnets located within the top housing, and a contracting wire in physical communication with each of the movable locking magnets. The contracting wire shrinks in length based on a voltage being applied to the contracting wire. The contracting wire exerts a force on each of the movable locking magnets as the length of the contracting wire shrinks. Each of the movable locking magnets transition from a locked position to an unlocked position based on the force exerted by the contracting wire. The top and bottom housings separate when each of the movable locking magnets are in the unlocked position.

Password encryption for servicing high security systems

Embodiments of systems and methods are provided for managing and operating a user presence detection (UPD) capable information handling system (IHS) within a multi-user environment. The systems and methods disclosed herein improve system security and reduce power loss in a UPD-capable IHS operated within a multi-user environment by continuously: (a) monitoring user presence within a field of view (FOV) of the UPD-capable IHS, (b) determining the identity of the user(s) present within the FOV by comparing biometric data obtained from the user(s) present within the FOV with biometric data contained within a database of trusted users, and (c) performing various actions, such as waking the IHS from a low power state or locking an active system session of the IHS, based on the identity of the user(s) present with FOV.

System and methods for waking and locking an information handling system in a multi-user environment

Embodiments of systems and methods are provided for provisioning a database of trusted users stored locally within an information handling system (IHS) based on location. The systems and methods disclosed herein may be used to identify a location of the IHS, and provision a database of trusted users (e.g., a TMU database) stored locally with the IHS based on the identified location. The TMU database is initially provisioned with a set of trusted users (and associated TMU information) expected for the identified location. If the IHS moves to a different location, the systems and methods disclosed herein may automatically reprovision the TMU database with a set of trusted users (and associated TMU information) expected for the new location. This reduces re-enrollment and enables the systems and methods disclosed herein to intelligently manage the TMU database stored locally with the IHS.

Systems and methods for provisioning a database of trusted users based on location

Systems and methods for enabling voice commands and managing voice command settings during collaboration sessions in heterogenous computing platforms are described. In an illustrative, 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 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 a voice command during a collaboration session and process the voice command.

Enabling voice commands and managing voice command settings during collaboration sessions in heterogenous computing platforms

Systems and methods for distribution and management of certificates in a firmware framework. In some embodiments, an Information Handling System (IHS) may include a controller, where the controller includes firmware that, upon execution by a processing core, causes the processing core to instantiate an orchestrator; and a plurality of devices coupled to the controller, where each device includes firmware that, upon execution by a corresponding processing core, causes the corresponding processing core to instantiate a node of a plurality of nodes of a firmware framework; and where the orchestrator is configured to: store certificates in a local storage of the controller; and distribute one or more other certificates to one or more of the plurality of nodes within the firmware framework, without any involvement by any Operating System (OS) of the IHS.

Distribution and management of certificates in a firmware framework

Systems and methods for post-accident health assurance in an Information Handling System (IHS) are described. In some embodiments, an IHS may include a processor and a memory coupled to the processor, where the memory comprises program instructions that, upon execution by the processor, cause a Basic Input/Output System (BIOS) to execute a diagnostics routine during a reboot in response to a determination that the IHS suffered an accident prior to the reboot.

Post-accident health assurance in an Information Handling System

Systems and methods for data backup and restore operations in response to accidents 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 an Operating System (OS) to receive an accident indication and change a data backup setting in response to the indication.

Data backup and restore operations in response to accidents

Systems and methods are provided for utilizing a heterogeneous computing platform of an IHS (Information Handling System) to identify an audio headset worn by a user of the IHS. An orchestrator device of the IHS uses resources of the heterogeneous computing platform to capture a plurality of images of a user of the IHS, such as using integrated and/or external cameras of the IHS. Based on the captured images of the user, a determination is made regarding whether the user is wearing an audio headset and the audio headset worn by the user is identified. The IHS is then configured for audio outputs to the identified audio headset worn by the user.

Systems and methods for headset identification

Systems and methods for thermal controls based on power adders in heterogenous computing platforms are described. 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 heterogeneous computing platform, where the memory includes a plurality of sets of firmware instructions, and where at least one of the plurality of devices operates as an orchestrator configured to: in response to detection of a power adder coupled to the IHS, change a sustained power limit usable by a selected one of the plurality of devices.

Thermal controls based on power adders in heterogeneous computing platforms

Growing community of inventors

Round Rock, TX, United States of America

Daniel Lawrence Hamlin