A system can determine a resolution to an issue with a computing device. The system can, based on the determining of the resolution and a root cause analysis document template, process data relevant to the resolution to the issue with the computing device with natural language processing, to produce a root cause analysis document. The system can store the root cause analysis document. The system can update a second document based on the root cause analysis document, wherein the second document differs from the root cause analysis document.
A system can determine that an issue with first computing equipment is resolved via developing a new feature. The system can, in response to the new feature being omitted from a future feature list, add an identification of the new feature to the list. The system can, in response to the new feature being identified in the list, increase a vote count for the new feature. The system can, in response to the new feature being offered as part of second computing equipment, increase a priority value of the new feature in the list. The system can, in response to the new feature not being offered as part of the second computing equipment, decrease the priority value of the new feature in the list. The system can determine that development of the new feature is to occur based on the vote count and the priority value.
A system can identify an issue with a computing device based on support call data obtained during a support call. The system can determine that a current configuration of the computing device omits a functionality, which prevents fixing the issue with the computing device using the current configuration of the computing device. The system can provide information about the functionality to a data store that comprises identifications of functionalities, to produce an identifier of a product that comprises the functionality, wherein the current configuration of the computing device omits the product, and wherein the computing device is determined to be able to install the product. The system can store the identifier of the product that comprises the functionality. The system can initiate installation of the product to the computing device.
Techniques are provided for selective machine learning (ML) model deployment using predicted adjustments to an item grouping. One method comprises accessing information characterizing an item grouping; applying portions of the accessed information to (i) a first score prediction model and (ii) a second score prediction model to obtain data characterizing respective predicted scores for the item grouping; applying portions of the obtained data to an item grouping adjustment prediction model to obtain respective predicted adjustments to parameters of the item grouping; applying portions of the respective predicted adjustments to a selective model deployment system to obtain a deployment decision, where the selective model deployment system evaluates a performance of (i) the first score prediction model and (ii) the second score prediction model, based on the respective predicted adjustments to the parameters of the item grouping, to determine the deployment decision; and initiating processing steps based on the deployment decision.
Methods, systems, and devices are provided for managing operation of a system. To manage the system, information regarding desired services may be obtained. The information may be used to identify an architecture usable to provide the services. The architecture may be used to select hardware components to support the architecture. The hardware components and architecture may be used to establish a system able to provide the desired services.
An information handling system may include a circuit board, a plurality of information handling resources electrically and mechanically coupled to the circuit board, a power system electrically coupled to the plurality of information handling resources and configured to provide electrical energy to the plurality of information handling resources, a first electronic circuit breaker electrically coupled between the power system and the plurality of information handling resources, and a second electronic circuit breaker electrically coupled between the power system and the plurality of information handling resources and arranged electrically in parallel with the first electronic circuit breaker. The first electronic circuit breaker and the second electronic circuit breaker may be arranged relative to one another and the circuit board such that functionally equivalent pins of the first electronic circuit breaker and the second electronic circuit breaker have a common footprint relative to mounting surfaces of the circuit board.
Systems and methods for firmware updates with health status checks in a firmware framework are described. In an illustrative, non-limiting embodiment, 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 of a firmware framework; 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 respective node, and where a given node is configured to communicate an indication of a health status to the orchestrator without any involvement by any host Operating System (OS).
Systems and methods for General-Purpose Input/Output (GPIO) management in a firmware framework are described. In an illustrative, non-limiting embodiment, 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 of a firmware framework; 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 respective node in the firmware framework, and where the orchestrator is configured to provide execute a GPIO command without any involvement by any host Operating System (OS).
An embodiment includes an information handling system. The information handling system includes a chassis comprising an active cooling inlet, the active cooling inlet comprising a plurality of air intake portions admitting airflow into the chassis. The apparatus includes a screen comprising a plurality of perforations allowing airflow through the screen, wherein each perforation in the plurality of perforations has an area smaller than an area of an air intake portion in the plurality of air intake portions. The apparatus includes a hinge coupling the chassis and the screen, the hinge allowing the screen to be moved. between a closed position and an open position, wherein in the closed position the screen allows airflow through the screen and the active cooling inlet.
Disclosed methods and systems leverage a multiservice framework to provision a host system with capabilities indicated in a platform capability manifest (PCM). Responsive to detecting an identification of a particular capability as a restricted capability updates of the restricted capability are blocked. The particular capability and a version of the capability may be identified within a restriction manifest, thereby ensuring that the specified version of the capability will not be altered by conventional OS and OEM update services. The restricted capability may be a hardware component of the host and the restriction may prevent updates to a device driver of the component. The restriction manifest may be created by an IT administrator and delivered to the multiservice framework. Exemplary implementations of software services enabling this managed restriction functionality is also disclosed.
An embodiment detects, in a system diagnostic service, that a system health status metric has a value in a failure range of values. An embodiment detects, in the system diagnostic service by comparing a fan speed setting to a fan speed reading, that a system fan fails to satisfy an operational criterion. An embodiment generates, in the system diagnostic service, responsive to detecting that the system health status metric has a value in the failure range of values and detecting that the system fan fails to satisfy the operational criterion, a dust filter maintenance notification.
A flow control subsystem for controlling fluid flows affecting an information handling system may include a chassis configured to house components of the liquid-cooled information handling system. The chassis includes at least one hydrophobic region on a surface of the chassis. The surface is a surface that is exposable to a fluid leak. One or more fluid flow channels traverse the hydrophobic region(s). The one or more fluid flow channels are configured to convey fluid away from a predetermined area adjacent to the hydrophobic region.
Methods and systems for managing service systems are disclosed. An occurrence of a load event for a computer-implemented service of computer-implemented services provided by the service systems may be identified. Based on the identification, new operating parameters for the service systems may be obtained based on dynamically identified limits of support systems that provide supporting services for the computer-implemented services. The new operating parameters may define allocation of computing resources for providing the computer-implemented service. Operation of the service systems may be modified based on the new operating parameters to increase a likelihood of the service systems providing the computer-implemented service as desired (e.g., while minimizing excess computing resource allocation to the computer-implemented service).
An information handling system includes a sensor hub and an embedded controller. The sensor hub collects sensing data associated with the information handling system. The embedded controller receives a power state for the information handling system. The system receives a trigger event notification from the sensor hub. In response to the trigger event notification, the system generates a contextual data set, wherein the contextual data set includes first data associated with the power state and the sensing data associated with a trigger event. The system also stores the contextual data set in a memory. The contextual data set is utilized during a no-post/no-video situation in the information handling system.
Techniques are provided for anomaly detection using processor-based machine learning (ML) models trained using cross-validation training datasets. One method comprises obtaining data characterizing a plurality of item groupings comprised of one or more items; in response to obtaining additional data corresponding to a given item grouping and associated with a given entity: identifying an ML model selected from a plurality of ML models trained using a cross-validation training process that processes data associated with entities having positive instances of a designated anomalous event, wherein training data for a given entity comprises data associated with positive instances of the designated anomalous event for one or more different entities than the given entity; applying feature values associated with the additional data to the selected ML model to obtain data characterizing an anomaly result; and initiating one or more processing steps based at least in part on the anomaly result.
A wicking mitigation chassis for housing components of a liquid-cooled information handling system includes one or more notches formed in an edge of a bottom of the chassis. The one or more notches are configured to disrupt a flow of fluid within the chassis caused by leakage from a liquid cooling subassembly housed within the chassis to slow wicking of the fluid. The wicking mitigation chassis includes one or more rises in an outer surface of the bottom of the chassis created by dimpling an opposing surface of the bottom of the chassis. The one or more rises are configured to concentrate at least a portion of the flow of fluid in regions of the outer surface surrounding the one or more rises.
Methods and systems for managing operation of a data processing system are disclosed. To manage operation of the data processing system, an issue impacting desired computer implemented services from being provided by the data processing system may be obtained. Based, at least in part, on the issue, at least one person to be notified of the issue may be identified and a classification for the issue may be obtained based on a trained classification model. A channel for the at least one person may be identified based on the classification and using the channel associations (e.g., association between the channel and classification for the issue). By doing so, information regarding the issue may be communicated to the at least one person to initiate remediation of the issue to facilitate continued provisioning of desired computer implemented services.
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
18.
SYSTEMS AND METHODS FOR PREVENTING DAMAGE DURING INSERTION OF INFORMATION HANDLING RESOURCE BY RESTRICTING ACCESS BETWEEN ADJACENT RECEPTACLE CONNECTORS
An information handling system may include a circuit board, a plurality of receptacle connectors electrically coupled to and mechanically mounted upon the circuit board, and a blocking feature located between a pair of adjacent receptacle connectors of the plurality of receptacle connectors and creating a mechanical interference that prevents insertion of an information handling resource into an empty volume of space between the pair of adjacent receptacle connectors.
H01R 13/645 - Means for preventing, inhibiting or avoiding incorrect coupling by exchangeable elements on case or base
H01R 12/72 - Coupling devices for rigid printing circuits or like structures coupling with the edge of the rigid printed circuits or like structures
H01R 12/73 - Coupling devices for rigid printing circuits or like structures coupling with the edge of the rigid printed circuits or like structures connecting to other rigid printed circuits or like structures
19.
STORAGE SYSTEM WITH DRIVE WRITES PER DAY BASED TIERING
A storage system includes multiple storage tiers implemented based at least in part on a drive writes per day metric, including at least a first storage tier associated with a first value of the drive writes per day metric and a second storage tier associated with a second value of the drive writes per day metric different than the first value of the drive writes per day metric, each of the storage tiers comprising one or more storage drives each having assigned thereto the value of the drive writes per day metric of that storage tier. Data is dynamically moved between the storage tiers of the storage system based at least in part on data access frequency in a manner that places more frequently accessed data on one of the storage tiers having a higher value of the drive writes per day metric than another of the storage tiers.
An embodiment detects, in a system diagnostic service, that a system resource usage metric is above a threshold value. An embodiment generates, in the system diagnostic service, responsive to detecting that the system resource usage metric is above the threshold value, a dust filter maintenance notification.
An apparatus comprises at least one processing device configured to obtain a natural language description of issues associated with an information technology infrastructure, to process, utilizing a machine learning model, the natural language description and data structures characterizing content of pre-built solution trees for historical issues, and to generate a solution tree for the issues utilizing at least one pre-built solution tree selected based on an output of the machine learning model as a template, the generated solution tree comprising a graphical representation of steps for achieving potential solutions to the issues. The at least one processing device is further configured to associate the generated solution tree with at least a subset of information technology assets of the information technology infrastructure, and to utilize the generated solution tree for diagnosing and remediating the issues on the subset of the information technology assets.
Methods and systems for managing service systems are disclosed. An occurrence of a future event for a primary system of the service systems may be predicted. The occurrence of the future event may be likely to reduce a quality of services provided by the primary system at a future point in time. Based on the predicting of the occurrence and prior to the future point in time, computing resources of a secondary system of the service systems may be allocated. A new load balancing policy for the service systems may be obtained and staged with a load balancer of the service systems. Based on a determination that the occurrence of the future event is imminent, the new load balancing policy may be enforced to cause the at least a secondary system to participate in provisioning of the services.
The technology described herein is directed towards using active qubits for quantum circuit execution, in which operations on active qubits are replicated onto spare qubits for purposes of quantum state measurement data integrity verification. Spare qubits are available qubits in a quantum system that are not actively used for executing quantum operations. Via the information measured from the spare qubits, state measurement data integrity can be verified with fewer repeated multiple executions (shots) that use only active qubits. Variable, known amounts of phase shift, rotation and/or delay can be applied to a spare qubit. When measured, the spare qubit measurement data can be evaluated for whether the applied phase shift, rotation and/or delay remained the same following quantum operations; if so, the probability of the measured data being correct is increased. Active qubits can be measured in the Z-basis; spare qubits can be measured in the X-basis and Y-basis.
The technology described herein is directed towards monitoring phase noise errors in quantum circuits via a classical (non-quantum) computing device, along with phase control based on the monitoring. A phase shifter, operating at cryogenic temperatures, is deployed between a microwave photon source and the qubits to ensure precise phase alignment. By placing the phase shifter in close proximity to the qubits, the system reduces thermal noise and increases coherence during quantum gate operations, thus improving overall quantum computation performance. The classical computing device monitors the phase of the qubits following qubit interaction with a microwave signal from the photon source, detecting any deviations or noise-induced errors. Based on the monitored phase, the computing device adjusts the phase of subsequent microwave signals in real time via control of the phase shifter to mitigate phase noise, thereby reducing phase drift and noise, which ensures better stability and fidelity of qubit operations.
An embodiment includes an information handling system. The information handling system includes a chassis comprising an active cooling inlet, the active cooling inlet comprising a plurality of air intake portions admitting airflow into the chassis. The apparatus includes a screen coupled to the chassis, the screen comprising a plurality of perforations allowing airflow through the screen and into the active cooling inlet, wherein each perforation in the plurality of perforations has an area smaller than an area of an air intake portion in the plurality of air intake portions.
Systems and methods for device management in a firmware framework are described. In an illustrative, non-limiting embodiment, 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 of a firmware framework; 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 respective node in the firmware framework, and where the orchestrator is configured to provide a device manager for the plurality of devices without any involvement by any host Operating System (OS) of the IHS.
Systems and methods for power monitoring in a firmware framework are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a controller having firmware that, upon execution by a processing core, causes the processing core to instantiate an orchestrator of a firmware framework; 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 respective node, and where the orchestrator is configured to: in response to an indication of a transition of the IHS into a sleep, hibernation, or modern standby mode, send a command to the plurality of devices to enter a selected low-power state; monitor power consumption of each of the plurality of devices; and based at least in part upon the power consumption, identify one or more power offenders, among the plurality of devices.
Systems and methods for health orchestration of modular platforms in a firmware framework are described. In an illustrative, non-limiting embodiment, 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 of a firmware framework; and a first plurality of devices coupled to the controller, where each device of the first plurality of devices includes firmware that, upon execution by a corresponding processing core, causes the corresponding processing core to instantiate a respective node in the firmware framework, where the orchestrator is coupled to a secondary orchestrator instantiated by another controller of a modular board coupled to the IHS, and where the secondary orchestrator is configured to communicate an indication of a health status to the orchestrator without any involvement by any host Operating System (OS) of the IHS.
A display unit, including a display panel including a static portion and a retractable portion; a tension bar coupled to the retractable portion of the display panel; a midframe coupled to the static portion of the display panel; a sync plate including curved slots extending from a first side to a second side of the sync plate, each of the curved slots including a respective first end and a respective second end, the sync plate moveably coupled to the midframe; counterweight springs each including a first end and a second end, the second ends each including a protrusion, the counterweight springs coupled between the midframe and the sync plate such that the protrusions of the second ends of each of the counterweight springs are movably coupled within a respective curved slot of the sync plate; torsion springs coupled between the tension bar and the second side of the sync plate.
Techniques are provided for processing machine learning (ML) models in an ML pipeline using virtual resources and vault-based credentials. One method comprises obtaining a request to process an ML model in a given stage of an ML pipeline; obtaining an ML pipeline template to configure a virtual computing resource; obtaining a namespace that comprises model code for the ML model, artifacts of the ML model and credentials of a user stored in a digital vault; configuring the virtual computing resource using the ML pipeline template and the artifacts; initiating an execution of the model code for the ML model by the configured virtual computing resource, wherein the execution of the model code comprises accessing a protected resource using the credentials obtained from the vault; and obtaining results from the execution of the model code by the configured virtual computing resource.
Methods and systems for managing operation of a data processing system are disclosed. To manage operation of the data processing system, a notification identifying an issue impacting desired computer implemented services from being provided by the data processing system may be obtained. Based at least in part on the notification, a person tasked with managing the issue identified by the notification may be identified and a device from various devices associated with the person may be selected. Agnostic schema for providing notifications to any types of devices may be used to convert the notification into an agnostic format interpretable by any device in order to display the notification to the person. By doing so, the notification may be appropriately displayed in a method invoked by the device, thereby removing the dependency on specific device architectures to notify the user.
A metasurface unit cell array of a plurality of metasurface unit cells to manipulate reflection of incoming radiofrequency (RF) signals comprising a microcontroller unit executing code instructions of a metasurface hardware geofencing system to identify an angle of arrival of the incoming RF signals from consecutive metasurface unit cells to determine an expected phase delay of the incoming RF signals and to compare it to a measured phase delay of the incoming RF signals from a reconfigurable delay detection network having plural fixed transmission line segments with known capacitance load to identify a phase delay deviation indicating compromised integrity of the incoming RF signals, where each metasurface unit cell includes a reflective pattern structure of conductive material on a substrate, a electromagnetically coupled RF signal probe to detect the incoming RF signals from a voltage line with a substrate integrated waveguide embedded in the substrate.
Methods and systems for managing operation of a data processing system are disclosed. To manage operation of the data processing system, a policy update specifying a change in operation of data processing system may be obtained. Based at least in part on the policy update and/or a period of time in which a data processing system is to obtain data from a data source used to perform the policy update, a data processing system impacted by the policy update may identify a point in time to attempt to obtain the data from the data source. By doing so, updating operation of the data processing system using the data to complete the policy update may be appropriately performed in a method to allow sufficient capacity of the data source to provide the copies of the data to each data processing systems impacted by the policy update during the period of time.
Techniques are provided for automated item assortment selection using processor-based objective function evaluation of designated goal scores. One method comprises obtaining information characterizing a plurality of items, a performance of the plurality of items and a plurality of designated attainment goals of an organization associated with the plurality of items; applying at least portions of the obtained information to at least one algorithm to obtain data characterizing a selected item assortment comprising a subset of the plurality of items, wherein the at least one algorithm evaluates a plurality of item assortments, each comprising a different assortment of the plurality of items, wherein the selected item assortment is selected using an objective function that evaluates an attainment score for the plurality of designated attainment goals of the organization; and initiating processing steps based on the selected item assortment.
A fluid removal subsystem to excise leaked coolant from an information handling system includes an electric self-priming pump. The electric self-priming pump is encased in a housing sized to fit entirely within a chassis of the information handling system. An intake port and an outtake port are formed in the housing. Intake tubing may be connected with the intake port, and outtake tubing connected with the outtake port. The electric self-priming pump is configured to draw fluid within the chassis into the intake tubing and discharge the fluid through the outtake tubing to thereby remove at least a portion of the fluid from the chassis.
Methods and systems for managing operation of a deployment are disclosed. The operation may be managed by using a proactive approach to perform a disaster recovery of the deployment. The proactive approach may include (i) obtaining information about a set of conditions to which the deployment may likely be exposed, (ii) determining whether and/or for how long the deployment may be unable to provide computer implemented services, and/or (iii) evaluating potential recovery sites based on available resources. The potential recovery sites may be ranked according to at least one quality of the available resources. A potential recovery site may be selected from the ranking. An infrastructure of the potential recovery site may be provisioned. Finally, the potential recovery site may continue to provide the computer implemented services.
Techniques are provided for cluster-based generation of instructional content using generative artificial intelligence (AI). One method comprises obtaining information characterizing an interaction between a first and second user; applying at least a portion of the obtained information to a generative AI model, wherein the generative AI model employs a language model that is tuned using labeled interaction data of an organization associated with the first user and domain-specific knowledge for the organization, wherein the generative AI model generates information characterizing instructional content, related to the interaction, for the first user based on a cluster assignment of the first user to a given user cluster of multiple user clusters, and wherein the multiple user clusters are generated by applying a supervised clustering algorithm to (i) attributes of users associated with the organization and (ii) a designated organization objective of the organization; and initiating an automated action based on the instructional content.
Methods and systems for managing a data processing system are disclosed. A first set of user actions performed by a user of the data processing system while the data processing system is providing computer-implemented services may be obtained. The first set of user actions may not accomplish any desired outcomes of the user. A desired outcome of the user may be identified based on the first set of user actions and a knowledge repository that stores information regarding historical sets of user actions that lead to the any desired outcomes. Using a trained machine learning model, a second set of user actions may be inferred based on the desired outcome and at least the first set of user actions. Performance of the second set of user actions may be automatically initiated to increase a likelihood of an occurrence of the desired outcome.
A fluid containment subsystem for containing fluid leaks within a liquid-cooled information handling system includes an expandable dam positioned within a chassis of the liquid-cooled information handling system. A casing partially encloses the expandable dam within the chassis of the liquid-cooled information handling system. The expandable dam provides a predetermined clearance between the expandable dam and an adjacent structure of the chassis. The expandable dam is capable of closing the predetermined clearance by expanding in response to contact between the expandable dam and a fluid within the chassis of the liquid-cooled information handling system. In response to the contact, the expandable dam at least partially absorbs the fluid.
The described technology is generally directed towards automatic virus scanning of a file while restoring the file. Virus scanning of a duplicate file of the file to be restored can be concurrently performed while the unavailable file is undergoing restoration. The unavailable file and the duplicate file can be located on one or more nodes of a node cluster forming a distributed file system. Upon determining that a first file is unavailable (e.g., as part of a file read operation), a second, duplicate copy can be identified based upon a common fingerprint of the first file and the second file. The first file can undergo restoration using a third file (backup copy of the first file) to generate a fourth, restored file. Hence, with the virus scan performed, the restored file can be immediately provided to a client.
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
41.
INTENSITY MODULATED DIRECT DETECTION (IMDD) OPTICAL TRANSCEIVER SYSTEM
An IMDD optical transceiver system includes first and second transceiver devices connected to an optical cable. The first transceiver device modulates light to generate first and second optical signals having the same data and respective 180-degree out-of-phase intensities, rotates a polarization of the second optical signal to provide an orthogonally polarized second optical signal, and combines the first and orthogonally polarized second optical signal while maintaining their relative polarization orthogonality to provide a combined optical signal that it transmits via the optical cable. The first optical receiver receives the combined optical signal via the optical cable, separates the first and orthogonally polarized second optical signal in the first combined optical signal, converts the first and orthogonally polarized second optical signal to first and second electrical signals, respectively, and combines them to provide a combined electrical signal, and transmits the combined electrical signal.
Systems and methods for device reset in a firmware framework are described. In an illustrative, non-limiting embodiment, 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 of a firmware framework; 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 respective node, and where a given node is configured to communicate an indication of a reset or re-enumeration capability to the orchestrator without any involvement by any host Operating System (OS).
A fluid flow control subsystem for controlling fluid flows within a liquid-cooled information handling system includes a structure that extends upward from a chassis base of the liquid-cooled information handling system. A capillary action-inducing flange extends outwardly from a bottom portion of the structure and forms a narrow gap above the chassis base. Responsive to a fluid leak within the liquid-cooled information handling system, the capillary action-inducing flange causes a capillary flow to draw leaked fluid in a predetermined direction.
A system can, prior to conducting a support communication session with a user account, generate a sentiment profile for the user account based on interaction data representative of interactions via communications by the user account, wherein the interactions comprise first data representative of first types of queries via the user account and second types of responses via the user account that satisfy a specified interactions criterion, second data representative of patterns in behavior associated with the user account, and third data representative of respective contexts of the interactions, wherein the sentiment profile indicates a communication style to use when interacting with the user profile. The system can conduct the support communication session using an artificial intelligence virtual agent, wherein the artificial intelligence virtual agent determines what to communicate with the user account based at least in part on the sentiment profile for the user account.
Techniques are provided for hierarchical data forecasting using processor-based Bayesian models and deep learning. One method comprises obtaining data characterizing a performance of hierarchical items, wherein the hierarchical items comprise one or more item families in an item family hierarchical level and multiple items in an item hierarchical level; applying at least portions of the obtained data to a processor-based Bayesian-based model to obtain output data characterizing an item family forecast for at least one item family and a first item-level forecast for one or more of the items; applying at least portions of the obtained output data to a processor-based deep learning model to obtain data characterizing a second item-level forecast for one or more of the items; and initiating one or more processing steps based at least in part on the at least one second item-level forecast.
A method for processing requests from edge devices includes receiving a read request from an edge device, wherein the read request comprises a search vector, identifying partitions of a plurality of partitions based on a comparison of centroids associated with each partition of the plurality of partitions and the search vector to obtain similar partitions, wherein each partition of the similar partitions comprises a plurality of read replicas. Further the method includes identifying, for each of the similar partitions, a read replica of the plurality of read replicas with a lowest load to obtain lowest load read replicas, identifying vectors in each of the lowest load read replicas that are above a similarity threshold when compared to the search vector, and sending the vectors to the edge device.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
An information handling system stores an artificial intelligence (AI) model hub, and receives a request to execute an AI model within an application. In response to the request, the system collects performance related data from a plurality of AI models. Based on the collected performance related data, the system determines a workflow for the application. Based on the workflow, the system outputs a recommended AI model to be executed within the application.
A storage drive having the largest total capacity within a set of storage drives is identified as the prime storage drive. For each virtual RAID group allocated from the set of storage drives, the number of storage slices that is required by each virtual RAID group is allocated to that virtual RAID group. If one of the storage slices that was allocated to the virtual RAID group was allocated from the prime storage drive, a spare storage slice is also allocated to that virtual RAID group. When a storage drive fails, degraded virtual RAID groups are repaired in an order that is based on the number of non-failed storage drives that can be used to repair each degraded virtual RAID group. Non-failed storage drives are selected for allocation of spare storage slices based on how many degraded virtual RAID groups can be repaired using each storage drive.
Methods, systems, and devices are provided for managing operation of a system. To manage the system, varying performance expectations may be used as a basis for identifying desirable from undesirable operation. The varying performance expectations may take into account the impacts of both time and changes in pipelines used by the system to provide desired services. By proactively taking into account potential changes in the pipeline, the operation of the pipeline may be less likely to be flagged as undesirable when the system is not actually operating in an undesirable manner.
Methods, systems, and devices are provided for managing operation of a system. To manage the system, operation of an artificial intelligence workflow pipeline may be monitored. If any components of the artificial intelligence workflow pipeline are identified as exhibiting unexpected behavior based on the monitoring, additional analysis may be performed to attempt to identify issues impacting the components. Remediations may then be performed to attempt to address the issues impacting the components.
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
53.
PRUNING SYNTHETIC DATA TO MANAGE RESOURCE COST FOR ARTIFICIAL INTELLIGENCE MODEL TRAINING
Methods, systems, and devices are provided for managing operation of a system. To manage the system, components of an artificial intelligence workflow pipeline may be evaluated for migration or replication. If positively evaluated, then alternative locations may be identified based on resources needed to operate the components or reduced cost versions of the components. The alternative locations and other locations for obtaining reduced cost versions of the components may be evaluated at least based on data transmission resource cost, and one of each location may be selected and used to update operation of the artificial intelligence workflow pipeline.
Methods, systems, and devices are provided for managing operation of a system. To manage the system, components of an artificial intelligence workflow pipeline may be evaluated for migration, replication, or tuning. If positively evaluated for tuning, then a model tuning process may be performed. Locations for the tuning process may be evaluated based on resource consumption estimates to select a tuning location and deployment location. Resource use limits for portions of the process may be enforced during location selection.
Methods, systems, and devices are provided for managing operation of a system. To manage the system, components of an artificial intelligence workflow pipeline may be evaluated for migration, replication, or tuning. If a new model instance is to be instantiated based on the evaluation, a selection process may be performed to identify a host location. The selection process may take into account resource costs for modifying the model for compatibility and useful life estimated for the new instance.
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 9/48 - Program initiatingProgram switching, e.g. by interrupt
G06Q 10/0637 - Strategic management or analysis, e.g. setting a goal or target of an organisationPlanning actions based on goalsAnalysis or evaluation of effectiveness of goals
56.
DETECTING MISSING SEGMENTS AND IDENTIFYING FILES IMPACTED BY THE MISSING SEGMENTS USING A SINGLE PASS DISTRIBUTED SCAN
A method for managing data in a storage system includes: partitioning segments to generate buckets; assigning a portion of the buckets to a first storage node; collecting a partition of the segments assigned as child segments; identifying: a first set of child segments that maps to the portion of the buckets, and a second set of child segments that maps to a bucket of a second storage node; storing: each of the first set of child segments to an LSM tree of the first storage node, the second set of child segments to a buffer; sending the second set of child segments to the second storage node; receiving a third set of child segments from the second storage node; comparing the first set of child segments and third set of child segments of the LSM tree against second child segments; and making a determination that a mismatch is occurred.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
57.
IDENTIFYING DUPLICATE SEGMENTS AND THE LATEST SEGMENT USING A LIVE INSTANCE FILTER
A method for managing data in a storage system includes: adding identifier information to fingerprints to obtain suffixed fingerprints; lexicographically sorting the suffixed fingerprints to obtain a sorted index; bucketizing the suffixed fingerprints in the sorted list to obtain a set of buckets; checking, for each bucket, if the suffixed fingerprint is live; determining if the container identification (CID) associated with the suffixed fingerprint is higher than a stored fingerprint in a live filter; and based on the determination, storing the suffixed fingerprint in a live instance filter and making available for garbage collection.
Methods, apparatus, and processor-readable storage media for generating spatial-temporal representations of digital files using artificial intelligence techniques are provided herein. An example computer-implemented method includes determining one or more spatial properties within at least a portion of at least one digital file and at least one sequential order of data within the at least a portion of the digital file(s); generating at least one graph representation of the at least a portion of the digital file(s) based on the one or more spatial properties and the sequential order(s) of data; encoding parts of the graph representation(s) using at least one graph neural network in conjunction with one or more spatial-temporal transformers; generating a spatial-temporal feature representation of the digital file(s) by aggregating a plurality of the encoded parts of the graph representation(s); and performing one or more automated actions based on the spatial-temporal feature representation of the digital file(s).
One example method includes receiving, as input, a basket of questions from a domain, LLM-generated answers to each of the questions, and a respective human-generated score for each of the LLM-generated answers, obtaining respective fitness measurements, based on the input, for each neural metric in a population of neural metrics usable to evaluate a performance of the LLM when responding to a user inquiry, using, by an evolutionary algorithm, the fitness measurements to generate evolved neural metrics based on the neural metrics for the domain of interest, and generating the evolved neural metrics comprises generating a respective new version for one or more of the neural metrics for the domain of interest, and outputting a ranking of the evolved neural metrics according to a respective quality of each of the evolved neural metrics.
An information handling stores machine learning (ML) models and quality of service (QoS) data. The system performs a registration operation for multiple model management frame (MMF) core contracts and multiple supporting MMF converted modules (MCMs). Each different one of the MMF core contracts is supported by a corresponding different one of the MCMs. The system receives an application programming interface (API) request. In response to the API request, the system performs a learn operation for a first ML model and determines that a first MCM is to be used to respond to the API request. The system determines that the first ML model is associated with the first MCM and executes the first ML model via the first MCM to generate output data for a response to the API request.
An information handling system launches an installer of a software package at an information handling system and the software package includes an artificial intelligence model plugin and a dependency. The information handling system also determines whether the artificial intelligence model plugin can be executed on the information handling system. In addition, the information handling system installs the artificial intelligence model plugin in response to a determination that the artificial intelligence model plugin can be executed on the information handling system. Further, the information handling system loads the artificial intelligence model plugin and the dependency in an isolated load environment of a model management framework at runtime.
A method for testing operations of a computing environment includes obtaining, by a universal simulator, a request for recording a scenario in the computing environment, in response to the request: initiating a recording session of interactions between computing components in the computing environment, storing recorded actions each associated with one of the interactions in a simulator database, performing a playback using the recorded actions, and performing a remediation of the operations based on results of performing the playback.
An information handling system converts an artificial intelligence model to be compatible with an endpoint management service and determine a dependency on the artificial intelligence model. The information handling system also generates a software package that includes a model management framework associated with the artificial intelligence model. The software package is compatible with the endpoint management service, and includes the converted artificial intelligence model and the dependency. In addition, the information handling system deploys the software package to a client device that is managed by the endpoint management service.
An information handling system may include a keyboard assembly, a display assembly rotatably coupled to the keyboard assembly, and a processor configured to, when the display assembly is in a closed position relative to the keyboard assembly, determine a context of the information handling system and selectively enable and disable one or more components of the information handling system while in the closed position based on the context.
Dependency compliance features for assessing software dependencies in a host information handling system and remediating dependency non-compliance exceptions are disclosed. Disclosed methods and systems obtain a platform capability manifest (PCM) including capability information for each of one or more supported capabilities and identify at least one enabled capability. The enabled capability may correspond to a software service installed and enabled on the host. A dependency compliance of the host is evaluated based, at least in part, on dependency information included in the PCM. If a dependency non-compliance is detected, the enabled capability may leverage the multiservice framework to remediate the applicable service to achieve dependency compliance. Dependency compliance may include version compliance wherein the dependency information may include version criteria for each software library and/or version criteria for the enabled software service.
An apparatus comprises at least one processing device configured to monitor a pattern of write operations in a write journal of a storage system, the write operations being directed to storage objects in the storage system, the write journal queueing the write operations prior to the write operations being flushed to one or more storage devices of the storage system. The at least one processing device is also configured to detect, based at least in part on the monitored pattern of write operations in the write journal of the storage system, an anomalous write pattern indicative of an attack on the storage system. The at least one processing device is further configured, responsive to detecting the anomalous write pattern, to prevent one or more of the write operations in the write journal of the storage system from being flushed to the one or more storage devices of the storage system.
An information handling system presents visual images with a curved display that are corrected for perceptions related to peripheral versus binocular vision of an end user viewing the display. A binocular vision range is defined and scaled with a first scaling factor. A peripheral vision range is defined and scaled with a second scaling factor that compensates for perceptions of movement in an end user's peripheral vision with variable scaling factors applied to adjust for end user head position and gaze based upon detection of the end user by a camera capturing visual images of a viewing area of the display.
G09G 3/00 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
G09G 3/20 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix
G09G 3/3208 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED] organic, e.g. using organic light-emitting diodes [OLED]
68.
LOGGENIE: TRANSFORMER-BASED AIOPS SOLUTION FOR CROSS-DOMAIN LOG ANOMALY DETECTION
Methods, system, and non-transitory processor-readable storage medium for a log anomaly detection system are provided herein. An example method includes receiving, by a log anomaly detection system, log event sequences from a source domain. The log anomaly detection system pretrains a model to learn common patterns and semantics from the source domain log sequences. The log anomaly detection system implements a Log-Attention Module to address information loss that occurs during log parsing. The log anomaly detection system performs adapter-based fine-tuning on the pretrained model using target domain log sequences. The log anomaly detection system detects anomalies in the target domain log sequences using the fine-tuned model.
An information handling system may include a memory and a processor communicatively coupled to the memory, and configured to: store information regarding a plurality of compute nodes, including artificial intelligence capabilities and artificial intelligence workload telemetry for each of the plurality of compute nodes, in an enterprise tenant registry; receive an artificial intelligence model session request from an application executing on a client; based on the information regarding the plurality of compute nodes, select one or more compute nodes of the plurality of compute nodes for execution of the artificial intelligence model session; and load a model for the artificial intelligence model session to the one or more compute nodes selected to establish a model session, wherein the model session receives streamed input from the application and returns streamed output to the application.
An information handling system presents content as visual images at an autostereoscopic three-dimensional display having adjustable depth of field by capturing visual images of an end user viewing the three dimensional content and analyzing the visual images of the end user to detect the impact of the three dimensional visual images on the end user. When the end user shows signs of stress from viewing the three dimensional visual images, the depth of field is decreased. When the end user indicates a positive impact by the three dimensional visual images, the depth of field is increased.
A rack ejection system of a server type information handling system. The rack ejection system of a server type information handling system includes a cam lever, the cam lever including a cam lever lock mechanism, the cam lock mechanism being configured to engage the cam lever with a chassis of the information handling system; and, an ejection device mounted on the cam lever, the ejection system being configured to manipulate the cam lever lock mechanism of the cam lever, manipulating the cam lever lock mechanism disengaging the cam lever from the chassis of the information handling system.
A latch system of an information handling system. The latch system includes a handle component and a latching mechanism attached to the handle component, the latching mechanism performing an auto-lock operation between the information handling system and a rack when the information handling system is installed on the rack.
A firmware management operation. The firmware management operation includes providing an information handling system with a distributed unified BIOS; identifying a processor environment installed on an information handling system from a plurality of processor environments, the processor environment comprising a processor architecture; and, performing a firmware component management operation, the firmware component management operation managing updating of a firmware component of the distributed unified BIOS with an updated firmware component.
Various embodiments relate to a method involving edge nodes within a federation receiving first machine learning (ML) models from a central node, which pertain to both locally known and unknown document classes. The edge nodes generate generative synthetic document samples for locally known document classes using these models and locally known document samples, and then provide these samples to the central node. Subsequently, the edge nodes receive second ML models from the central node, trained using the generative synthetic document samples, covering all document classes known to the federation. Additionally, the edge nodes receive representative generative synthetic document samples for locally unknown document classes. The edge nodes then perform document classification on received documents using the second ML models, along with the representative generative synthetic document samples and locally known document samples.
A firmware management operation. The firmware management operation includes providing an information handling system with a distributed unified BIOS; identifying a processor environment installed on an information handling system from a plurality of processor environments, the processor environment comprising a processor architecture; and, performing a dynamic workload management operation, the dynamic workload management operation managing a workload executing on the information handling system, the dynamic workload management operation being processor environment agnostic.
Methods, apparatus, and processor-readable storage media for determining configuration change impacts on data center devices using machine learning techniques are provided herein. An example computer-implemented method includes obtaining information pertaining to proposed configuration changes to a first set of devices within at least one data center; predicting a second set of devices, within the data center(s), which will be impacted in connection with the proposed configuration changes by processing the obtained information using machine learning techniques; processing the obtained information and the predicted second set of devices using at least one consensus mechanism associated with at least one blockchain; determining, using one or more smart contracts associated with the blockchain(s), whether to add at least one new block to the blockchain(s) in response to the processing using the consensus mechanism(s); and performing automated actions based on the determining of whether to add at least one new block to the blockchain(s).
H04L 41/08 - Configuration management of networks or network elements
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
77.
SYSTEM AND METHOD FOR DETECTING HUMAN PRESENCE USING A CHARGE DOMAIN IMAGING DEVICE AND RANGE SENSOR FOR AN INFORMATION HANDLING SYSTEM
A system and method to detect human presence near the information handling system having a charge domain imaging device and a range sensor working in tandem when the information handling system may be in a sleep mode or awake. The range sensor detects moving presence within a first detection range from the information handling system and provide this data to the charge domain imaging device to prompt context interface operations available to a user within the first detection range. The range sensor detect moving presence within a second, closer detection range from the information handling system and provide this data to the charge domain imaging device trigger a low resolution imager at charge domain imaging device to capture images within the closer range to determine facial identification, gaze detection and other operations with those images for waking the information handling system, authorization, or for interaction with the information handling system.
A distributed logging system for nodes in a cluster network system. A distributed log has a shared storage architecture and provides durability by maintaining multiple copies of the log data, and availability is facilitated through a sealing protocol that ensures that system failure results in reconfiguration with a new node. Logs generated by nodes are stored in a shared log that is segmented based on the logs and respective entries. A metastore maintained in one node contains a mapping of the logs with respective storage locations. The distributed log is fault tolerant so that a loss of a node will not lose data. Load balancing is also employed to redistribute loads among the nodes using the mapping.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
79.
SYSTEM AND METHOD FOR A WEARABLE THREE-DIMENSIONAL INPUT/OUTPUT (IO) AND AUTHENTICATOR DEVICE ACTING AS SECURITY AND IO DEVICE FOR INFORMATION HANDLING SYSTEMS WITHIN DETECTED RANGE
A wearable three-dimensional (3D) input/output (IO) and authenticator ring device comprising a ringed structure and interface platform curved for placement around a user's finger having a curved-surface high-sensitivity fingerprint and touchpad sensor configured to face a user's thumb for interaction and a user presence detector to determine that the user has donned the wearable 3D IO and authenticator ring device. The wearable 3D IO and authenticator ring device to operatively pair with an information handling system and one or more smart devices when located within a user-defined range to establish the wearable 3D IO and authenticator ring device as a controlling input device. The wearable 3D IO and authenticator ring device to tune user inputs with artificial intelligence and to detect and wirelessly transmit touch inputs, user hand movement inputs, gesture inputs, or finger press inputs correlating to input commands for the information handling system or smart devices.
Generalized network incident management is disclosed. When an incident in a network is detected, a request is generated and sent to a prompt generator. The prompt generator generates a prompt based on the request, key performance indicators of the network, and a semantic state of the network, which is generated by a first model. The prompt is input to a second model and the second model generates a recommended solution to the incident. An agent may evaluate the recommended solution and send a command to the network to resolve the incident. The prompt generator also generates the prompt using a graph neural network and/or a knowledge base. The network incident management can be automated and/or include a human-in-the-loop.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
H04L 41/046 - Network management architectures or arrangements comprising network management agents or mobile agents therefor
H04L 41/5006 - Creating or negotiating SLA contracts, guarantees or penalties
81.
SYSTEM AND METHOD OF EXECUTING A DIGITAL DISPLAY DEVICES AUDIO AND VIDEO CONTEXTUAL ENGINE SYSTEM TO OPERATE A UNIFIED VIRTUAL ADAPTIVE USER INTERFACE ACROSS PLURAL DIGITAL DISPLAY DEVICES
An information handling system comprising a network interface device to detect operatively coupling of plural standalone digital display devices to form a digital workspace and to automatically receive location data of plural standalone digital display devices relative to each other determined from detected exchange of sound, infrared, or other waves between them and a hardware processor executing machine readable code instructions of a digital display devices audio and visual contextual engine system to unify operation of digital workspace I/O devices including a first microphone and a first speaker at a first standalone digital display device and a second microphone and a second speaker at a second standalone digital display device to operate as a unified virtual adaptive user interface. The hardware processor to utilize the digital workspace I/O devices to detect a user location and to automatically adjust operation of the plural standalone digital display devices in the digital workspace.
H04R 1/40 - Arrangements for obtaining desired frequency or directional characteristics for obtaining desired directional characteristic only by combining a number of identical transducers
A model-based network digital twin for forecasting and scenario generation is disclosed. The network digital twin includes twin components that each include a component model and a component knowledge graph. Each twin component is associated with a corresponding network component. Data from the network is ingested into the network digital twin and used to update the knowledge graphs. Requests received through an orchestration model are input to the component models, which generate responses using the corresponding component knowledge graphs. The orchestration model generates a final response to the request for an operator. The request may be a forecast or what-if scenario.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
H04L 41/5009 - Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF]
One example method operates to configure and optimize a private communication network, and includes receiving, by a prompt generator, input comprising a KG (knowledge graph), and/or a base network configuration generated by a first LLM (large language model), using, by the prompt generator, the input to create an initial network design prompt, receiving, by a second LLM, the initial network design prompt, and using, by the second LLM, the initial network design prompt to create a site-specific network configuration, providing the site-specific network configuration to a network orchestrator, and orchestrating, by the network orchestrator, the site-specific network configuration to deployment site.
One example method includes generating an enhanced network graph (ENG) that is a representation of a physical RAN, providing the ENG as input to a GNN model, with the GNN model, using the ENG, to obtain network state embeddings of the physical RAN, providing the network state embeddings and a cluster of network task requests to a prompt generator, by the prompt generator, creating a prompt based on the network state embeddings and network task requests, transmitting the prompt to an AFM (agentic foundation model), based on the prompt, capturing, by the AFM, entity interdependencies of the physical RAN, transmitting the prompt, by the AFM, to a cluster of downstream tasks that each correspond to a respective one of the network task requests, and by the cluster of downstream tasks, generating respective control commands and transmitting the control commands to the physical RAN.
SYSTEM AND METHOD FOR A CUSTOMIZABLE UNIVERSAL DIGITAL DOCKING INPUT PAD OPERATING AS A PLURALITY OF INPUT/OUTPUT (IO) DEVICES FOR A NEARBY INFORMATION HANDLING SYSTEM
A customizable universal digital docking input pad may comprise a proximity sensor to detect nearby presence of an information handling system, a short distance radio to establish a wireless link with the information handling system, a grid of pressure sensors to detect location of a solid object placed by the user on the customizable universal input pad as an input/output (IO) device, the short distance radio to transmit the solid object location to the information handling system and receive back a user-selected identification of an IO device type for the solid object, the pressure sensors to detect downward force upon or movement of the solid object with respect to the customizable universal input pad, and a microprocessor to execute machine readable code instructions to associate the downward force or movement with IO code instructions formatted for the IO device type and transmit the IO commands to the information handling system.
Systems and methods for issuing comprehensive software identities for multiple compute domains configured in an IHS that creates a new software identity construct (CSWID), which can holistically represent some, most, or all unique attributes of software are disclosed. According to one embodiment, an Information Handling System (IHS) may include multiple processors each comprising a compute domain. A first of the processors includes program instructions to, using an Initial Device Identifier (IDEVID) associated with a first of the compute domains, generate a first key derivation function (KDF) associated with one or more software elements of a second of the compute domains, and issue the KDF to the second compute domain, wherein the second compute domain uses the KDF to attest one or more applications configured on the first compute domain.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
87.
SYSTEM AND METHOD FOR THE CONFIDENTIAL GENERATION AND ISSUANCE OF SOFTWARE IDENTITIES
Systems and methods for the confidential generation and issuance of software identities are disclosed. According to one embodiment, an Information Handling System (IHS) computer-executable program instructions to in response to a request from a workload, generate, using a Software Identity Service/Agent (VSISA), a Confidential Software Identity (CSWID) for the workload, and bind the CSWID to a Hardware Root-of-Trust (HW-ROT) in the IHS. During the runtime usage of the IHS, the instructions ensure proof of possession for the workload running on the IHS.
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
Updating fingerprints for deduplicated data segments in a cluster network utilizing data containers calculating new fingerprint hashes using a new hash process that replaces an old hash process that generated current fingerprint hash values. A new index mapping from the present hash process to the new hash process is created, with a new fingerprint index mapping from the updated hash process to the containers. New fingerprints are generated with the new fingerprint hash, the new hash process calculates the new fingerprint hash values of new data segments. To support writes during fingerprint updates, the system deduplicates data segments fingerprinted using the new hash process and stores the deduplicated data in storage. Both the old and new fingerprinted data segments can be deduplicated to reduce storage overhead.
G06F 16/174 - Redundancy elimination performed by the file system
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/13 - File access structures, e.g. distributed indices
89.
SYSTEM AND METHOD FOR A VIRTUAL LINE-OF-SIGHT WITH A NON-VOLATILE RECONFIGURABLE METASURFACE FOR WI-FI SENSING
A system and method for operating a reconfigurable metasurface unit cell array of a virtual line-of-sight (LoS) Wi-Fi sensing system having a reconfigurable metasurface unit cell array to establish a virtual LoS portion of a Wi-Fi wireless link between a transmitter device and receiver device and a reconfigurable metasurface microcontroller unit to receive a Wi-Fi sensing request from the transmitter device. The reconfigurable metasurface microcontroller unit executes to monitor for angle of arrival and time of flight of a target object present within the virtual LoS. The reconfigurable metasurface microcontroller unit to determine a direction and location of the target object within the virtual LoS based and create a beamforming pattern at the reconfigurable metasurface to increase signal propagation of the Wi-Fi wireless link with Wi-Fi sensing to the target object and to report the direction and location of the target object to the transmitter device.
H01Q 15/00 - Devices for reflection, refraction, diffraction or polarisation of waves radiated from an antenna, e.g. quasi-optical devices
G01S 13/534 - Discriminating between fixed and moving objects or between objects moving at different speeds using transmissions of interrupted pulse modulated waves based upon the phase or frequency shift resulting from movement of objects, with reference to the transmitted signals, e.g. coherent MTi based upon amplitude or phase shift resulting from movement of objects, with reference to the surrounding clutter echo signal, e.g. non-coherent MTi, clutter referenced MTi, externally coherent MTi
90.
Secure Searchable Encryption with Semi-Hidden Access Control
A system for secure searchable encryption with semi-hidden access control is disclosed. The system enhances data privacy and security by segregating attribute names from their encrypted values, allowing attribute names to remain in plaintext for search operations while keeping attribute values confidential. A trapdoor privacy module generates encrypted trapdoors using a secret cryptographic element and a hash function, ensuring keyword security even if trapdoors are intercepted. The system stores encrypted data and indices on a cloud server, facilitating secure search operations without exposing sensitive data. A ciphertext authenticity module verifies the integrity of ciphertexts using digital signatures, ensuring data authenticity and protection against unauthorized modifications. This approach enables data users to perform secure keyword searches on the cloud server, retrieving requested data without revealing search keywords, thereby providing a robust framework for secure searchable encryption.
Disclosed methods and systems for detecting a new resource on a host information handling system that encompasses multiple ecosystem layers including a hardware/firmware layer, an operating system layer, and a cloud layer. Responsive to detecting the new resource, a multilayer orchestration is performed. The multilevel orchestration includes detecting included components within each of two or more ecosystem layers, accessing a platform capability manifest (PCM) indicative of platform supported capabilities, and responsive to identifying one or more open dependencies based on the platform supported capabilities and the included components, installing or updating one or more included resources to resolve one or more of the open dependencies.
The technology described herein is directed towards a design and implementation of a reconfigurable surface that reflects an impinging electromagnetic signal, with a phase profile determined by the curvature of a flexible metallic ground plane beneath metallic resonating elements of the reconfigurable surface. The amount of curvature forms different gaps between portions of the flexible ground plane and the respective metallic resonating elements above those portions, thereby determining the shape of the reflected beam. In one implementation, four individually controllable linear actuators are mechanically coupled to the corners of the ground plane of a metasurface (panel). These actuators enable a curvature phase profile, by determining the amount of curvature of a flexible, metallic ground, which allows a reflected beam to be shaped. Compensation for unwanted flex resulting from one or more external stimuli (e.g., motion and/or vibration) is also provided.
H04B 7/04 - Diversity systemsMulti-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
93.
SYSTEMS AND METHODS FOR ARTIFICIAL INTELLIGENCE DISTRIBUTED AGENT ECOSYSTEM RESOURCE OPTIMIZATION
An information handling system may include a memory and a processor communicatively coupled to the memory, and configured to execute an agent system configured to collect and aggregate performance metrics from one or more artificial intelligence agents executing on one or more host systems and estimate parameters including resource requirements, performance targets, operating costs, and power usage associated with executing the one or more artificial intelligence agents on the one or more host systems.
Disclosed methods obtain, from a cloud licensing server, licensing information for an end user of a host system. The licensing information indicates valid end user licenses for accessing licensable capabilities. The licensing information may be provided to an intelligent installation service (IIS) running in the host operating system (OS). The IIS leverages a multiservice framework installer to provision the host system with capabilities, including licensable capabilities, in accordance with the licensing information. The licensable capabilities may include licensable capabilities pertaining to audio performance capabilities, including hardware and software coders/decoders (codecs), telemetry capabilities, and overclocking capabilities. The IIS may be configured to scan one or more file depositories to determine available software services and scan the host to determine capabilities available to the end user. In addition, the IIS may receive hardware capability inputs, IT policy inputs, and user selection inputs, that influence the capabilities provisioned on the host.
Optimizing filesystem recipes for VM backups using variable size segmenting (VSS) by identifying a region of a VM to be copied having an unchanged data area bounded by left and right regions of real changed data. A changed block tracking (CBT) process marks a CBT region as changed data, but this area is greater than the regions of real changed data. A process identifies areas within respective CBT regions that have unchanged data but that is marked as changed data by the CBT process. It extends a recipe specifying unchanged data of a base file for replication to include the identified areas so as to prevent replication of data that is actually unchanged but marked as changed by the CBT process.
A process for managing customer-specific endpoint upgrade images for FIDO Device Onboarding (FDO) systems is disclosed. This approach addresses the problem of securely delivering customized software updates to edge devices and ensuring that updates are applied only to intended devices to maintain confidentiality and compatibility. The solution involves embedding customer signatures into upgrade images that are verified using a customer public verification method and a hash generation algorithm stored on the device. This enhances security and reliability by restricting updates to specific customer devices, thereby preventing unauthorized access and potential operational issues. The endpoint device includes a processor and memory that execute instructions to verify the customer signature and allow or block upgrades based on hash matching.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
Systems and methods for delayed onboarding of information handling systems (IHS) to management systems are disclosed. The approach addresses the challenge of securely onboarding generic devices or white-box systems to a control plane without prior configuration. Embodiments comprise an out-of-band processor, such as a Baseboard Management Controller (BMC), executing an onboarding client that continuously attempts to connect to an onboarding service. This process allows devices to be attached to control planes in a zero-touch, secure manner, even after initial setup and operation of in-band components of the device.
Disclosed methods and systems leverage a multiservice framework to provision a host system based on platform supported capabilities indicated in a platform capability manifest (PCM). Upon receiving a candidate manifest, indicative of one or more requested capabilities, manifest conflict information, identifying the requested capabilities, is generated. After obtaining arbitration policy information for resolving capability conflicts and requests, a resolved manifest is generated based on the PCM, the manifest conflict information, and the arbitration policy. In this manner, the resolved manifest enables the host to deny or accommodate capability requests in accordance with the arbitration policy. The multiservice framework may be again leveraged to provision the host system in accordance with the resolved manifest. The candidate request can include a user capability manifest identifying a particular user and capabilities the user is permitted to request or an application initiated manifest identifying an application and one or more dependencies the application has.
Methods and systems for managing operation of a request processing pipeline are provided. To service requests, the request processing pipeline may accept unstructured text based requests. The unstructured text may be used to obtain prompts for evaluation by a trained generative machine learning model. The pairs may be evaluated to rank order them with respect to one another. A best ranked one of the pair may be used to service the request. The request may be serviced by providing the response of the best ranked one of the pairs, by initiating provisioning of computer implemented services using the response, and/or via other processes.
Methods and systems for managing operation of a request processing pipeline are provided. To service requests, the request processing pipeline may accept unstructured text based requests. The unstructured text may be used to obtain prompts for evaluation by a trained generative machine learning model. The pairs may be evaluated to rank order them with respect to one another. A best ranked one of the pair may be used to service the request. The request may be serviced by providing the response of the best ranked one of the pairs, by initiating provisioning of computer implemented services using the response, and/or via other processes.
