The disclosed concepts relate to automatically identifying conditions in a video game to trigger a help session. When a help session is triggered, another video game player or machine learning model can temporarily take over for the current video game player until an ending condition is reached. Help session triggering can be designated by evaluation of prior gameplay data of other video game players to identify in-game conditions that may tend to cause user disengagement, such as in-game conditions that are associated with difficult in-game goals or negative in-game consequences.
A63F 13/5375 - Commande des signaux de sortie en fonction de la progression du jeu incluant des informations visuelles supplémentaires fournies à la scène de jeu, p. ex. en surimpression pour simuler un affichage tête haute [HUD] ou pour afficher une visée laser dans un jeu de tir utilisant des indicateurs, p. ex. en montrant l’état physique d’un personnage de jeu sur l’écran pour suggérer graphiquement ou textuellement une action, p. ex. en affichant une flèche indiquant un tournant dans un jeu de conduite
A63F 13/79 - Aspects de sécurité ou de gestion du jeu incluant des données sur les joueurs, p. ex. leurs identités, leurs comptes, leurs préférences ou leurs historiques de jeu
A63F 13/87 - Communiquer avec d’autres joueurs, p. ex. par courrier électronique ou messagerie instantanée
G06F 40/40 - Traitement ou traduction du langage naturel
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
G06V 20/62 - Texte, p. ex. plaques d’immatriculation, textes superposés ou légendes des images de télévision
An adaptive user representation (AUR) system for use with generative artificial intelligence (AI) receives queries meant for the generative AI and utilizes one or more AI models to process each query to determine query context and to identify user information from a user information repository which is relevant to the query. The system generates instructions based on the query, query context, and the relevant user information for causing the generative AI to generate a response to the query which is personalized to the user. The AUR system transforms the raw data of the query and relevant user information into a set of instructions for the generative AI which describe how to personalize the response or required searches to ensure the final response is personalized.
Examples are disclosed relating to a method for calibrating a depth camera without requiring an external target. In one example, an environment is illuminated using an illumination source of the depth camera. The illumination source is configured to output modulated structured light comprising a pattern of dots. A raw depth image of illumination reflected from the environment is acquired via an optical sensor of the depth camera. Observed locations of dots in the pattern of dots are identified in the raw depth image. An objective function is applied to the observed locations of the dots in the pattern of dots in the raw image to generate a set of distortion correction parameters. A distortion corrected depth image generated based at least on translating pixel locations of pixels of the raw depth image according to the set of distortion correction parameters is output.
Described are examples for providing access to an on-premises resource executing via a cloud-computing environment. A client-side proxy executing on a centralized node in the cloud-computing environment can receive, from a client resource provider (RP) that communicates with the client-side proxy via a client RP virtual network established in the cloud-computing environment, a request by a requesting node to access the on-premises resource. The client-side proxy can provide, based on the request, access to the on-premises resource for the requesting node.
H04L 67/563 - Redirection de flux de réseau de données
H04L 61/59 - Utilisation de mandataires pour l’adressage
H04L 67/289 - Traitement intermédiaire fonctionnellement situé à proximité de l'application consommatrice de données, p. ex. dans la même machine, dans le même domicile ou dans le même sous-réseau
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
5.
AI-BASED DIGITAL 3D ENGRAVING BASED ON A USER-UPLOADED IMAGE
A data processing system implements receiving, via a user interface of a client device, an image; constructing, via a prompt construction unit, a first prompt by appending the image to a first instruction string including instructions to a generative model; providing the first prompt to the generative model; generating, by the generative model and according to the first prompt, a depth map using an intensity of darkness of each pixel of the image as a respective depth of the pixel in a digital three-dimensional (3D) transparent object; digitally engraving, by the generative model and according to the first prompt, each pixel of the image in the 3D transparent object based on the respective depth in the depth map into a digital 3D engraved object; receiving the digital 3D engraved object from the generative model; and providing the digital 3D engraved object to display on the user interface of the client device.
Systems and techniques for facilitating unified multichannel communication are provided. The described systems and techniques improve communication technology through an encompassing, channel-agnostic approach which unifies disparate communication modes into a singular coherent thread. A unified multichannel communication (“UMC”) service of a UMC platform can initialize a UMC thread for a UMC session, where the UMC thread can be used to facilitate unified multichannel communication. The UMC session can involve multiple participants, including human users and software agents (e.g., conversational bots, virtual agents, digital assistants, and other dialog interfaces). The UMC platform can facilitate creating and interacting with a digital assistant providing unified multichannel communication.
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
H04L 69/14 - Protocoles multicanaux ou multi-liaisons
H04L 69/18 - Gestionnaires multi-protocoles, p. ex. dispositifs uniques capables de gérer plusieurs protocoles
7.
AUTOMATIC PARALLEL EXECUTION OF ARTIFICIAL INTELLIGENCE WORKLOADS
A computer-implemented method can receive an internal representation of a transformer model, an internal representation of a device cluster, and an internal representation of a workload for execution of the transformer model on the device cluster. The method can generate a plurality of candidate execution plans based on the internal representation of the transformer model and the internal representation of the device cluster. Each candidate execution plan represents a unique parallel schedule for partitioning devices in the device cluster for parallel execution of the transformer model. The method can determine an optimal execution plan, including evaluating resource usage of the plurality of candidate execution plans based on the internal representation of the workload, and selecting, among the plurality of candidate execution plans, the optimal execution plan which yields the lowest resource usage. The evaluating includes simulating execution of the transformer model on the device cluster to process the workload.
Embodiments disclosed herein are directed to computing technology for programmatically sanitizing unwanted content that is shared in a meeting. The unwanted content may be sanitized in real-time and in a meeting presentation. In an implementation, the unwanted content is detected, and a determining a sensitivity mitigation action is determined for the unwanted content. The sensitivity mitigation action is applied to generate a modified presentation of a live meeting presentation such that aspects of the unwanted content are removed. A graphical user interface (GUI) tool is disclosed to enable users to control application of a sensitivity mitigation action. In this manner, embodiments disclosed herein facilitate complying with a privacy policy.
The disclosed concepts relate to training a machine learning model to provide help sessions during a video game. For instance, prior video game data from help sessions provided by human users can be filtered to obtain training data. Then, a machine learning model can be trained using approaches such as imitation learning, reinforcement learning, and/or tuning of a generative model to perform help sessions. Then, the trained machine learning model can be employed at inference time to provide help sessions to video game players.
A63F 13/5375 - Commande des signaux de sortie en fonction de la progression du jeu incluant des informations visuelles supplémentaires fournies à la scène de jeu, p. ex. en surimpression pour simuler un affichage tête haute [HUD] ou pour afficher une visée laser dans un jeu de tir utilisant des indicateurs, p. ex. en montrant l’état physique d’un personnage de jeu sur l’écran pour suggérer graphiquement ou textuellement une action, p. ex. en affichant une flèche indiquant un tournant dans un jeu de conduite
A63F 13/67 - Création ou modification du contenu du jeu avant ou pendant l’exécution du programme de jeu, p. ex. au moyen d’outils spécialement adaptés au développement du jeu ou d’un éditeur de niveau intégré au jeu en s’adaptant à ou par apprentissage des actions de joueurs, p. ex. modification du niveau de compétences ou stockage de séquences de combats réussies en vue de leur réutilisation
A63F 13/87 - Communiquer avec d’autres joueurs, p. ex. par courrier électronique ou messagerie instantanée
A computer-implemented method can generate a parallel schedule for partitioning devices included in a device cluster for parallel execution of a transformer model. The transformer model is represented by a chain of cells. Each cell includes a set of tasks of the transformer model. Generating the parallel schedule includes dividing the chain of cells into one or more sequential stages, creating one or more replicas of the transformer model or some of the cells, and mapping the set of tasks included in a cell to one or more devices of the device cluster. For a given workload, the method can execute the transformer model on the device cluster according to the parallel schedule.
The disclosed concepts relate to managing help sessions within a video game based on age information associated with a video game player. For example, systems and associated methods scan perform age-based restriction of a help session using a variety of techniques. For instance, automated helpers can be selected for help sessions involving children, or messaging between a human helper and a child can be restricted using a range of communication techniques described herein.
A63F 13/79 - Aspects de sécurité ou de gestion du jeu incluant des données sur les joueurs, p. ex. leurs identités, leurs comptes, leurs préférences ou leurs historiques de jeu
A63F 13/5375 - Commande des signaux de sortie en fonction de la progression du jeu incluant des informations visuelles supplémentaires fournies à la scène de jeu, p. ex. en surimpression pour simuler un affichage tête haute [HUD] ou pour afficher une visée laser dans un jeu de tir utilisant des indicateurs, p. ex. en montrant l’état physique d’un personnage de jeu sur l’écran pour suggérer graphiquement ou textuellement une action, p. ex. en affichant une flèche indiquant un tournant dans un jeu de conduite
A63F 13/87 - Communiquer avec d’autres joueurs, p. ex. par courrier électronique ou messagerie instantanée
G06F 40/40 - Traitement ou traduction du langage naturel
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
12.
EXTENSIBLE DATA PLATFORM WITH DATABASE DOMAIN EXTENSIONS
A computing system that includes one or more server computing devices including one or more processors configured to execute instructions for a domain extensibility module that provides software development tools for building domain extensions for a database platform, and a data ingestion module that provides software development tools for defining a metadata schema for extracting metadata from data files. The one or more processors are configured to receive a set of data from a user computing device, define a target metadata schema that includes one or more metadata fields that will be populated during a data ingestion process, define a target domain extension that defines one or more data types for storing the received set of data after performing the data ingestion process, and ingest the received set of data using a metadata extraction pipeline to generate metadata files based on the target metadata schema.
Providing arbitration for resource sharing using channel priority differences in processor-based devices is disclosed herein. In one exemplary embodiment, a processor-based device comprises a data allocation circuit that is communicatively coupled to one or more ingress channels and one or more egress channels. The data allocation circuit assigns an ingress channel priority to each ingress channel, and assigns an egress channel priority to each egress channel. The data allocation circuit generates one or more channel pairs by iteratively identifying an unpaired egress channel having a highest egress channel priority, calculating absolute differences between each ingress channel priority of each unpaired ingress channel and the egress channel priority of the unpaired egress channel, and allocating the unpaired egress channel to an unpaired ingress channel that corresponds to the smallest absolute difference as a channel pair. The data allocation circuit then performs one or more transactions using the corresponding one or more channel pairs.
H04L 47/6275 - Ordonnancement des files d’attente caractérisé par des critères d’ordonnancement pour des créneaux de service ou des commandes de service basé sur la priorité
14.
TECHNIQUES FOR COLLISION HANDLING IN GATEWAY SESSIONS IN WIRELESS COMMUNICATIONS
Described are examples for modifying a packet data network (PDN) gateway used for a session in wireless communications where the PDN gateway can receive, for a mobility management entity (MME) or evolved packet data gateway (ePDG), a request to restore an existing session with the first PDN gateway, receive, from a database, and based on attempting to restore the existing session for the MME or ePDG, a read lock failure based on a restoration of the existing session established for the MME or ePDG and a second PDN gateway, and send, for the MME or ePDG, a rejection message in response to the request, where the rejection message includes a cause code indicating to restore the existing session with the second PDN gateway. Other examples relate to the MME or ePDG receiving the rejection message and sending the request to restore the existing session with the second PDN gateway.
The disclosed concepts relate to providing help sessions for video game players. For instance, a help session starting state can be obtained from a video game session by a particular video game player. The help session starting state can be loaded into a help session. During the help session, inputs received from a client device of a video game helper can be directed to the help session. After the help session, an updated help session state can be obtained. In some cases, the particular video game player can choose to accept the updated help session state and proceed with video game play from that state. In other cases, the particular video game player can choose to reject that state and return back to the help session starting state.
According to examples, an apparatus includes processing units that execute threads using a hybrid locking/queuing operation for efficient processing of work units with mutual exclusion of the work units. Under the hybrid locking/queuing operation, a processing unit determines that a first thread is to process a first work unit, in which the first work unit is under protection of a hybrid exclusion object (HEO), and in which the HEO includes an HEO queue. In addition, the processing unit places a lock on the HEO, determines whether the HEO is owned by a thread, and based on a determination that the HEO is owned by a second thread, adds the first work unit to the HEO queue, and releases the lock on the HEO. The second thread assigns ownership of the HEO to the first work unit when the first work unit reaches a top of the HEO queue.
A computer-implemented method is described which comprises generating a representation of a digital space and a representation of the physical space using an audiovisual feed received from a camera proximate to a display located in the physical space. The representation of the digital space is generated using user information identifying a remote user associated with the display and presence information relating to the remote user and the digital representation comprises an avatar of the remote user. The representation of the digital space is output to the display located in the physical space and the representation of the physical space it output to a computing device associated with the remote user. The method further comprises dynamically updating the representation of the digital space and/or physical space in response to changes in the user information and presence information.
Methods and systems for tracing forwards of an electronic message. One method includes storing, for each of a plurality of forwarded messages sent via an electronic messaging application, a record in a data store, each record including a link to an original message for the forwarded message and calculating, with an electronic processor, a statistic for an electronic message based on records stored in the data store, wherein the statistic includes at least one selected from a group consisting of a number of forwards of the electronic message, a number of recipients of the electronic message including all forwards of the electronic message, and a number of requests to revoke the electronic message. The statistic is then output for display to a user via at least one user interface.
Techniques are described herein that are capable of performing a security action with regard to an access token based on clustering of access requests. Subsets of access requests are clustered into respective clusters, which correspond to respective requestor types, based at least on the access requests in the subsets having respective attributes that indicate the respective requestor types. The access requests request access to cloud resources. Access behavior(s) associated with the access requests that are included in respective cluster(s) are identified. A security action is performed with regard to an access token based at least on at least one of the access behavior(s).
Methods, systems, and computer storage media for providing blended settings management using a blended remote-local settings management engine are described. The blended remote-local settings management engine integrates different settings controllers into blended settings management via remote clients. In operation, an indication to initiate settings configuration is accessed at a remote client. The indication is processed using a blended remote-local settings management engine that integrates management of remote settings of remote clients and local settings of local clients. Based on the indication, a request for a local setting of a local client associated with the remote client is generated. The request is communicated to the local client using a dynamic virtual channel between the remote client and the local client. Based on the request, the local setting of the local client is retrieved. Display of the local setting is caused on a blended remote-local settings interface associated with blended settings management.
H04L 41/0806 - Réglages de configuration pour la configuration initiale ou l’approvisionnement, p. ex. prêt à l’emploi [plug-and-play]
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
21.
TRACKING AND REPRESENTING VIDEO GAME HELP SESSIONS
The disclosed concepts relate to tracking and representing help sessions for video games where video game players are assisted by a helper, e.g., another video game player and/or a trained machine learning model. For instance, the disclosed implementations can graphically modify a controllable entity, such as a character or vehicle, to convey that the current video game player is being assisted by a helper. As another example, the disclosed implementations can graphically modify game achievements to indicate when a given achievement was earned with assistance from a helper.
A63F 13/5375 - Commande des signaux de sortie en fonction de la progression du jeu incluant des informations visuelles supplémentaires fournies à la scène de jeu, p. ex. en surimpression pour simuler un affichage tête haute [HUD] ou pour afficher une visée laser dans un jeu de tir utilisant des indicateurs, p. ex. en montrant l’état physique d’un personnage de jeu sur l’écran pour suggérer graphiquement ou textuellement une action, p. ex. en affichant une flèche indiquant un tournant dans un jeu de conduite
A63F 13/493 - Reprise du jeu, p. ex. après une pause, un dysfonctionnement ou une panne de courant
A63F 13/69 - Création ou modification du contenu du jeu avant ou pendant l’exécution du programme de jeu, p. ex. au moyen d’outils spécialement adaptés au développement du jeu ou d’un éditeur de niveau intégré au jeu en permettant l'utilisation ou la mise à jour d'éléments spécifiques du jeu, p. ex. déblocage d’options, d’éléments, de niveaux ou de versions cachés
A63F 13/79 - Aspects de sécurité ou de gestion du jeu incluant des données sur les joueurs, p. ex. leurs identités, leurs comptes, leurs préférences ou leurs historiques de jeu
A63F 13/87 - Communiquer avec d’autres joueurs, p. ex. par courrier électronique ou messagerie instantanée
The disclosed concepts relate to managing help sessions in video games. A system or method receives control inputs from a helper during a help session in a video game. The system or method obtains a game state of the video game and determines whether to provide the control inputs to the video game based on the game state. In at least one instance, the system or method at least temporarily prevents the video game from receiving a particular control input.
A computer-implemented method can receive an internal representation of a transformer model which defines one or more repeating blocks, each block including a sequence of cells, and each cell including a set of tasks of the transformer model. The method can search for a plurality of parallel schedules for partitioning devices included in a device cluster for parallel execution of the transformer model. The searching includes determining a number of model replicas, determining a number of stages that divide the one or more repeating blocks, determining a number of cell replicas for each cell in a block, and for each cell replica of a cell, generating a task mapping which maps the set of tasks included in the cell to devices partitioned into the cell replica.
Embodiments of the present disclosure include techniques for managing dirty data. An agent receives a request for data. If the data is dirty data, the agent may use a replacement policy to determine if the data should be passed clean or dirty to the requestor. The replacement policy may correspond to how long the dirty data being stored in a cache line is to be maintained. In one embodiment, the replacement policy is a circuit, such as an SRAM and a logic circuit, for example.
G06F 12/0891 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p. ex. mémoires cache utilisant des moyens d’effacement, d’invalidation ou de réinitialisation
G06F 12/0864 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p. ex. mémoires cache utilisant des moyens pseudo-associatifs, p. ex. associatifs d’ensemble ou de hachage
G06F 12/123 - Commande de remplacement utilisant des algorithmes de remplacement avec listes d’âge, p. ex. file d’attente, liste du type le plus récemment utilisé [MRU] ou liste du type le moins récemment utilisé [LRU]
25.
AUTHENTICATION AND AUTHORIZATION OF REQUESTER APPARATUSES IN NETWORK SYSTEMS
According to examples, an apparatus includes a processor that receives a request from a requester apparatus to access a target apparatus. The processor may provide a token valid to the requester apparatus upon determining that the requester apparatus is authenticated to access the target apparatus, in which the token complies with and is sent via a centralized authentication and authorization protocol. The processor may also receive an access check message from the target apparatus, in which the access check message includes the token and the identity of the requester apparatus. In addition, the processor may enable the target apparatus to control access to the requester apparatus. The apparatus disclosed herein enable for the retrofitting of secure multi-factor or one-time password authentication into systems that rely on a centralized authentication and authorization protocol, such as the TACACS+ or the RADIUS protocol.
Systems, methods, and computer readable storage media described herein for dynamically routing jobs to job service architectures and consolidating data. In an aspect, a job request associated with a user account is received. A migration status of the user account is determined to indicate the user account is migrating from a first job service architecture to a second job service architecture. A determination of whether or not the migration state is enabled is made. If the migration state is enabled, the job request is routed to the second job service architecture, causing the second job service architecture to schedule a corresponding job. If the migration state is not, the job request is routed to the first job service architecture, causing the first job service architecture to schedule the job. In a further aspect, the job request comprises a script and the job comprises a step to execute the script.
Processor-based system supporting in-field testing using external dynamic random access memory (DRAM) for storing and accessing test scan data. The processor-based system includes a processor that includes one or more central processing units (CPUs) that each have access to resources, such as cache memory, a memory controller to access system memory (e.g., DRAM), interfaces circuits, to perform tasks by executing of program code. The processing-based system includes an internal, built-in testing system that allows the processor-based system to be placed into test mode to perform in-field testing of the processor-based system. To support larger-sized scan data, the processor-based system is configured for the built-in-test system to access test scan data stored in DRAM in the processor-based system in a test mode. In this manner, the DRAM supports storing larger-sized test scan data so that greater in-field test coverage can be performed in the processor-based system.
A computing device including a hardware accelerator. The hardware accelerator includes a generalized matrix-vector multiplication (GEMV) circuit configured to compute a product vector over a plurality of streaming iterations. At each of the streaming iterations, the GEMV circuit receives an input vector element and an input matrix row. The GEMV circuit multiplies the input vector element by input matrix elements included in the input matrix row to obtain an intermediate product row. The GEMV circuit adds the intermediate product row to a current-iteration row sum. The product vector is equal to the current-iteration row sum computed in a final streaming iteration. The GEMV circuit transmits the product vector as a streaming output to a post-processing circuit included in the hardware accelerator. The post-processing circuit performs a vector processing operation on the product vector to compute vector processing result, and outputs the vector processing result.
A data processing system implements receiving, via a user interface, report context and a request to generate insights of a data report; constructing a first prompt by appending the request a default system prompt, the report context, and the data report as a first instruction string; validating the first prompt using a second generative model by checking whether the first prompt is structured according to sections that contain one or more predetermined purposes and whether the default system prompt is responsive to the report context; when the first prompt is validated by the second generative model, providing the first prompt to the first generative model; generating, by the first generative model and according to the first prompt, an insight output; receiving the insight output from the first generative model; and providing the insight output to display on the user interface.
The techniques disclosed herein provide promotion of meeting engagement by transitioning viewing perspectives to a temporary viewing perspective showing group activity. A system can show each person a view of a large virtual environment, e.g., in a stadium full of representations of meeting attendees. Each person sees the virtual environment from a point of view originating from each person's representation, e.g., a first-person avatar view. When a group activity meets one or more conditions, the system generates a new virtual environment model that shows detailed view of all people in a group, without showing members of other teams that may be intermingled with the group in an original environment. The system may transition each group member's view from the first-person view to a temporary view of the newly generated model that only includes group members. The temporary view can remain until the group activity drops below a threshold.
Systems and methods are provided that introduce an approach for executing a multi-query workload that leverages live execution feedback from nodes to detect resourcing issues and anomalies, and deploy real-time corrective measures for the multi-query workload. Leveraging live execution feedback from the nodes as the queries are executing make it possible to detect various resourcing issues and anomalies, and enable the system to perform corrective actions “live” or in “real-time” during an execution of a query, and more specifically during execution of the tasks within a query.
Semiconductor-superconductor hybrid devices with a horizontally-confined channel and methods of forming the same are described. An example semiconductor-superconductor hybrid device includes a semiconductor heterostructure formed over a substrate. The semiconductor-superconductor hybrid device may further include a superconducting layer formed over the semiconductor heterostructure. The semiconductor-superconductor hybrid device may further include a first gate, having a first top surface, formed adjacent to a first side of the semiconductor heterostructure. The semiconductor-superconductor hybrid device may further include a second gate, having a second top surface, formed adjacent to a second side, opposite to the first side, of the semiconductor heterostructure, where each of the first top surface of the first gate and the second top surface of the second gate is offset vertically from a selected surface of the semiconductor heterostructure by a predetermined offset amount.
The disclosure herein describes training a text processing model to generate model output text data using input text data and a sentence count. A training data entry including input text data and output text data is obtained. A sentence count of the output text data is determined, and the output text data is labeled with a sentence count label and a sentence number label. Model output text data is generated with a text processing model using the input text data and determined sentence count as input data. Loss data associated with a difference between the generated model output text data and the labeled output text data is determined and the text processing model is adjusted using the determined loss data. The use of labeled output text data enables the model to be trained to produce output text data with a target sentence count in a computationally efficient manner.
Some embodiments provide proxies or other servers in a computing network with independent certificate chains which facilitate mitigation of certificate problems. Independence criteria are enforced against two or more installed certificate chains on a given server, identifying and avoiding dependencies such as cross-certification, shared certificate authorities, shared revocation lists, or shared certificate status protocol endpoints between the certificate chains. Some embodiments serve independent certificates concurrently in an active-active certificate server configuration. The certificate chains' coexistence and their independence from one another facilitates transitioning the network from a failing issuer or a failed chain to a chain that works better, thereby improving network resilience and limiting damage from certificate problems. By dynamically updating certificate bindings, some embodiments also facilitate safe deployment of new certificates during migration from one issuer to another. Certificate distributions are computed from issuer ratios, network topology, or both.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A multiplex assay for nucleic acid detection includes a substrate, a sample, and a fluorophore-labeled oligonucleotide. The substrate has a plurality of physically separated assay locations, each of which includes a nucleotide-targeting enzyme configured to cleave nucleic acids, a guide ribonucleic acid (gRNA), and a quencher-labeled oligonucleotide. A portion of the sample is distributed to each assay location. The gRNA recognizes target nucleic acid in the sample, thereby activating the nucleotide-targeting enzyme to cleave nucleic acids, including the quencher-labeled oligonucleotide. The fluorophore-labeled oligonucleotide is subsequently added to each assay location, which facilitates identification of a presence of the target nucleic acid in the sample via detection of unquenched light emitted by the fluorophore in one or more of the plurality of assay locations.
Approaches to classifying text-based content are described herein. For example, a classification system performs operations that include receiving text-based content comprising a plurality of characters, generating a plurality of character category sequences using the plurality of characters and based on a plurality of predefined character categories, calculating a frequency distribution of the plurality of character category sequences, and classifying the text-based content based on the calculated frequency distribution. The classifying uses a machine learning model that has been trained using a plurality of examples of text-based content. Responsive to the classification, the system can take appropriate actions. For example, responsive to classifying the text-based content as unsolicited, the system can restrict distribution of the text-based content or generate an alert for the text-based content.
Techniques for managing user presence based on an operation state of an external peripheral device connected to a computing device are described. The method determines whether the external peripheral device is being utilized when performing an activity relating to a first software application executing on the computing device. In response to determining utilization, state information for the user is updated to indicate an active state based on the activity performed on the computing device or with respect to a user identity associated with the first software application. During activity performance, a second software application obtains the state information and updates a user presence status to indicate that the user is currently in an active operation state according to the state information indicating the active state. The method enables cross-application presence management by leveraging peripheral device usage patterns to maintain accurate user availability status across multiple software applications and computing environments.
Embodiments of the disclosed technologies are capable of generating, using a machine learning model and a prompt, first content recommendations. The prompt comprises a search query and historic information associated with an entity. The first content recommendations are presented. The embodiments describe receiving a selection of a content recommendation of the first content recommendations. The embodiments describe generating, using the machine learning model and a second prompt, second content recommendations. The second prompt comprises a second search query and second historic information associated with the entity. The embodiments describe generating a ranked order of the second content recommendations using a history of entity interactions including the selection of the content recommendation of the first content recommendations. The embodiments describe determining context-aware recommendations by optimizing a permutation of the ranked order of the second content recommendations. The embodiments describe causing the context-aware recommendations to be presented.
Passive devices may be embedded into a cavity in a package substrate, with electrical contacts of the passive device on a contact surface orthogonal to a surface of the package substrate and extending through the package substrate. The electrical contacts of the passive device may be coupled to vias coupled to a power supply to provide capacitive decoupling. One or more through-hole vias (THVs), which provide current to ICs on the package substrate, may be excluded from the package substrate to accommodate the passive device. Embedding the passive devices in the cavity of the package substrate with the contact surface orthogonal to, rather than parallel to, the surface of the package substrate, reduces an area occupied by the passive device. In this manner, a number of the THVs excluded from the package substrate is reduced, which results in a smaller impact to the resistance of the power supply network.
H01L 23/522 - Dispositions pour conduire le courant électrique à l'intérieur du dispositif pendant son fonctionnement, d'un composant à un autre comprenant des interconnexions externes formées d'une structure multicouche de couches conductrices et isolantes inséparables du corps semi-conducteur sur lequel elles ont été déposées
H01L 23/528 - Configuration de la structure d'interconnexion
40.
CONTROLLING COMPLEXITY OF CAPTIONING THAT USES A VISION LANGUAGE MODEL
A vision language model (“VLM”) generates text captions from video content. Innovations in controlling the complexity of captioning that uses a VLM are described. For example, a training tool updates a training set so that text captions are more concise, then fine-tunes a VLM using the updated training set. Or, as another example, a generative artificial intelligence model such as a VLM dynamically adjusts the probability of an end-of-sentence (“EOS”) token so that the probability of the EOS token increases in successive iterations of output token generation, which tends to make generated text captions more concise. Or, as another example, a captioning tool identifies and ranks representative units (such as keyframes) of video, then selectively applies captioning (using a VLM) to representative units of the video based on ranking information. Together or individually, the innovations can improve the computational efficiency and accuracy of captioning that uses a VLM.
A lattice-based cryptography engine includes an interface configured to receive a lattice-based cryptographic operation request including corresponding operands. A register map is configured to store the operands and response to the request. A controller is coupled to receive the operands and output a sequence of instructions responsive to the request. A plurality of hardware units is coupled to receive and execute the instructions to generate the response. Each instruction is designated for one of the plurality of hardware units. A memory is coupled to the hardware units.
A lattice-based cryptographic engine includes a MakeHint unit to generate hints for polynomial coefficients. Logic hardware is coupled to the MakeHint unit and includes a hint sum unit configured to add hints for coefficients of a polynomial, compare a hint sum to a threshold, and generate an invalid signal in response to the hint sum exceeding the threshold. The logic hardware also includes a sample buffer configured to receive the hints, a hint bitpack coupled to store indices of non-zero hints, and a controller coupled to control transfer of hints to output registers.
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
This disclosure describes a framework for performing user-requested tasks automatically across an interactive interface using various types of machine learning models. Specifically, this disclosure outlines and describes a task execution system that utilizes a generative artificial intelligence (AI) action model and retrieval-augmented generation (RAG) to complete user-requested actions across an interactive interface. The task execution system solves many of the current limitations of LAMs by using a generative AI action model to determine a session plan, which includes a set of actions for accomplishing stages of the actionable task across the interactive interface, obtaining visual context information of each interactive interface segment, integrates RAG results to improve the accuracy of both the session plan and individual actions, and self-corrects when faced with unexpected obstacles.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
44.
CONJOINED MEMORY SYSTEMS SUPPORTING DATA STORAGE IN LARGER MEMORY SYSTEM WHEN SMALLER MEMORY SYSTEM IS UNAVAILABLE AND WITH SMALLER MEMORY SYSTEM READ LATENCY, AND RELATED PROCESSOR-BASED SYSTEMS AND METHODS
Conjoined memory system that includes a larger memory system conjoined with a smaller memory system to support data storage in the larger memory system when the smaller memory system is unavailable, and related methods of performing memory accesses and computer-readable media are also disclosed. The conjoined memory system is configured to selectively direct new, incoming memory write requests for incoming data (e.g., incoming data packets to be stored) through a bypass data path to be written to memory entries in the smaller memory system if available for data storage (e.g., memory entry(ies) are free). Memory access latency and dynamic power expended for such memory accesses is reduced. However, if the smaller memory system is not available for data storage (e.g., memory entries are full), the conjoined memory system can selectively direct new, incoming memory write requests instead to the larger memory system to be stored in memory entries therein.
A vision language model (“VLM”) generates text captions from video content. Innovations in controlling the complexity of captioning that uses a VLM are described. For example, a training tool updates a training set so that text captions are more concise, then fine-tunes a VLM using the updated training set. Or, as another example, a generative artificial intelligence model such as a VLM dynamically adjusts the probability of an end-of-sentence (“EOS”) token so that the probability of the EOS token increases in successive iterations of output token generation, which tends to make generated text captions more concise. Or, as another example, a captioning tool identifies and ranks representative units (such as keyframes) of video, then selectively applies captioning (using a VLM) to representative units of the video based on ranking information. Together or individually, the innovations can improve the computational efficiency and accuracy of captioning that uses a VLM.
Enabling efficient hash-based signature verification in processor-based devices is disclosed herein. In one exemplary embodiment, a processor-based device includes a processor device and a hash compute core circuit. The hash compute core circuit receives, from a process executing on the processor device, a digit of a plurality of digits of a message digest, a signature value corresponding to the digit, and an initialized context value. The hash compute core circuit generates a hash chain by being configured to, for Y times wherein Y is an integer value calculated using a value of the digit, update the context value, and perform a hash operation on the signature value. The hash compute core circuit then transmits an ending value of the hash chain to the process, which stores the ending value of the hash chain.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
47.
PERFORMING TRANSFORMER-BASED DESIGN VERIFICATION FOR COVERAGE CLOSURE IN PROCESSOR DEVICES
Performing transformer-based design verification for coverage closure in processor devices is disclosed herein. In one exemplary embodiment, a processor device trains an online decision transformer (ODT) using initial trajectories based on regression testing of a Design-Under-Test (DUT). The processor device then performs an online learning phase using the ODT by first generating a plurality of new trajectories. For each new trajectory, the processor device uses the ODT to generate a sequence of actions based on maximizing coverage, transmits the sequence of actions to a testbench environment, receives a corresponding sequence of observed states and a corresponding sequence of coverage metrics from the testbench environment, and generates the new trajectory. The processor device identifies a subset of the new trajectories having a final coverage metric that exceeds a coverage threshold, adds the subset to a replay buffer of the ODT, and retrains the ODT using the replay buffer.
The techniques disclosed herein provide a system for constructing an automated telecommunications network operation model prior to deployment in a telecommunications network for completing downstream tasks. In general, the performance of artificial intelligence agents such as large language models can degrade when applied to highly specific and/or complex domains such as telecommunications network operations resulting in erroneous outputs and potentially leading to network outages. As such, the present techniques finetune a large language model using a domain specific dataset to establish a specialized context directed to telecommunications network operations. That is, the large language model is pre-trained to establish the specialized context prior to deployment in the operation of a telecommunications network. In this way, the automated telecommunications network operation model can support a broad range of tasks within the context of a telecommunications network such as generating network configurations and question answering while also achieving strong performance.
A system may generate embedded subsets by projecting each subset of the subsets into a vector space to generate a corresponding embedded subset. A system may encode the embedded subsets into an encoded image using a dataset encoder including a gated spectral state space model, the gated spectral state space model being a gated neural network that includes a spectral state space model, the spectral state space model being a state space model that represents features of the input dataset using at least a spectral transformation of each embedded subset of the embedded subsets. A system may predict a classification for the input dataset using the encoded image.
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
Devices, systems, and methods for reconfigurable butterfly architectures are provided. A reconfigurable butterfly operator circuit includes a single multiplier configured to receive a first variable and a twiddle factor and produce a product, first and second modular subtractors coupled to the multiplier, the first modular subtractor coupled to receive input coefficients and provide a modular difference, and the second modular subtractor coupled to receive the product, a modular adder coupled to receive the input coefficients and provide a modular sum, and multiplexers coupled to (i) provide the input coefficients to the modular adder, (ii) provide the first variable and the twiddle factor to the multiplier, (iii) and receive the modular difference from the first modular subtractor, respectively, each of the multiplexers coupled to receive a control signal that selects whether the circuit is configured as a Gentleman-Sande butterfly operator circuit or a Cooley-Tukey butterfly operator circuit.
The disclosed techniques pertain to training large language models (“LLMs”) using table data. Specifically, the disclosed techniques pertain to training LLMs for table-related tasks using two models, each model reserved for different functions. A first model is reserved for generator functions and a second model is reserved for validator functions. The first model receives table data and generates training data. The training data is fed to the second model, which identifies instances of training data meeting or exceeding at least one validity threshold. Instances of training data meeting or exceeding the at least one validity threshold are output as validated training data. The validated training data is used to iteratively fine-tune the two models by increasing or decreasing one or more numeric weight parameters in each of the models that control how the models process input data and produce outputs.
Technologies are disclosed for performing imaging operations via a direct secure wireless connection to an imaging device. An imaging device, such as a printer or scanner, obtains a signed certificate defining a security policy from an identity and access management (“IAM”) service. A computing device, such as a laptop or smartphone, obtains a signed certificate from the IAM service that defines access rights associated with the computing device. The imaging device and the computing device exchange the signed certificates. The imaging device approves or denies a request from the computing device to perform imaging operations by way of a direct secure wireless communication channel between the imaging device and the computing device based on the security policy and the access rights.
A plurality of training examples is accessed, each training example comprising an image of a scene and a pose of a viewpoint from which the image was captured. A neural radiance field is trained using the training examples. A plurality of generated images is computed, by, for each of a plurality of randomly selected viewpoints, generating a color image and a depth image of the scene from the neural radiance field. A neural network is trained using the generated images.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
A computing system including memory storing a table including a plurality of entries arranged in a plurality of rows and a plurality of columns. The memory may further store a knowledge graph in which semantic data is stored. The computing system may further include a processor configured to, at a metadata inference machine learning model, generate inferred table metadata based at least in part on the entries included in the table and the semantic data included in the knowledge graph. The inferred table metadata may include one or more row type classifications of one or more respective rows or one or more column type classifications of one or more respective columns. The processor may be further configured to generate a metadata display interface element that visually represents the inferred table metadata and output the metadata display interface element for display at a graphical user interface (GUI).
Some storage systems are configured with VDL (valid data length) type controls that are implemented on a per cluster basis and, in some instances, on a sub-cluster basis, rather than simply a per file basis. In some instances, per-cluster VDL metadata for the storage clusters is stored and referenced at the edge data volume nodes of a distributed network for the storage system rather than, and/or without, storing or synchronizing the per-cluster VDL metadata at a master node that manages the corresponding storage clusters for the different data volume nodes. Sequence controls are also provided and managed by the master node and synchronized with the edge data volume nodes to further control access to data contained in the storage clusters.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
A method, computer program product, and computing system for estimating noise spectrum from a target audio signal segment. An acoustic neural embedding is generated from the target audio signal segment. An augmented audio signal segment is generated with background acoustic properties of the target audio signal segment by processing an input audio signal segment with the noise spectrum and the acoustic neural embedding using a neural network.
G10L 21/0264 - Filtration du bruit caractérisée par le type de mesure du paramètre, p. ex. techniques de corrélation, techniques de passage par zéro ou techniques prédictives
G10L 25/18 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande
G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux
According to examples, an apparatus may include a memory on which is stored machine-readable instructions that may cause a processor to determine, for each of a plurality of members in a group, a respective least privilege level for a resource and determine, based on the determined respective least privilege levels, a privilege level to be assigned to the group for the resource. The instructions may also cause the processor to assign the determined privilege level to the group for the resource and apply the assigned privilege level to the members of the group for the resource.
G06F 12/14 - Protection contre l'utilisation non autorisée de mémoire
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 9/46 - Dispositions pour la multiprogrammation
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
A system for providing a personalized assistant for network-based communication services utilizes one or more processors and memory to enhance user interaction through intelligent query processing. The system receives queries from computing devices and processes them using an intermediate model that analyzes communication session transcripts, user data, and session metadata alongside shared content from the communication service. The intermediate model generates prompt templates with content selection criteria to identify relevant transcript portions and shared content, constructing targeted prompts for a generative language model. The system handles various content types including files, screen sharing, and chat messages through rule-based engines, while employing transcript partitioning and rolling summary techniques for extended sessions. Advanced features include predictive follow-up query generation with response caching, role-based prompt customization, and feedback-driven learning for continuous improvement. The generative language model output is translated into personalized responses and presented to users.
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 15/06 - Création de gabarits de référenceEntraînement des systèmes de reconnaissance de la parole, p. ex. adaptation aux caractéristiques de la voix du locuteur
59.
POLYNUCLEOTIDE ENCAPSULATION AND PRESERVATION USING SELF-ASSEMBLING MEMBRANES
Polynucleotides such as DNA are stored inside vesicles formed from self-assembling membranes. The vesicles may be protocells, liposomes, micelles, colloidosomes, proteinosomes, or coacervates. The vesicles may include surface functionalization to improve polynucleotide encapsulation and/or to bind polynucleotides having specific sequences. Encapsulation in vesicles provides protection for the polynucleotides. Additional protection is provided by addition of one or more stabilizers. The stabilizer may be nucleic-acid stabilizers that stabilize the polynucleotides or may be a protective structural layer around the vesicles such as a layer of silica. A process for stably storing polynucleotides in vesicles and a process for recovering stored polynucleotides from vesicles are both disclosed. The polynucleotides may be used for storage of digital information.
A61K 31/7088 - Composés ayant au moins trois nucléosides ou nucléotides
A61K 47/14 - Esters d’acides carboxyliques, p. ex. acides gras monoglycérides, triglycérides à chaine moyenne, parabènes ou esters d’acide gras de PEG
A61K 47/18 - AminesAmidesUréesComposés d’ammonium quaternaireAcides aminésOligopeptides ayant jusqu’à cinq acides aminés
A61K 47/26 - Hydrates de carbone, p. ex. polyols ou sucres alcoolisés, sucres aminés, acides nucléiques, mono-, di- ou oligosaccharidesLeurs dérivés, p. ex. polysorbates, esters d’acide gras de sorbitan ou glycyrrhizine
A61K 47/36 - PolysaccharidesLeurs dérivés, p. ex. gommes, amidon, alginate, dextrine, acide hyaluronique, chitosane, inuline, agar-agar ou pectine
A61K 47/62 - Préparations médicinales caractérisées par les ingrédients non actifs utilisés, p. ex. les supports ou les additifs inertesAgents de ciblage ou de modification chimiquement liés à l’ingrédient actif l’ingrédient non actif étant chimiquement lié à l’ingrédient actif, p. ex. conjugués polymère-médicament l’ingrédient non actif étant un agent de modification l’agent de modification étant une protéine, un peptide ou un acide polyaminé
A61K 47/69 - Préparations médicinales caractérisées par les ingrédients non actifs utilisés, p. ex. les supports ou les additifs inertesAgents de ciblage ou de modification chimiquement liés à l’ingrédient actif l’ingrédient non actif étant chimiquement lié à l’ingrédient actif, p. ex. conjugués polymère-médicament le conjugué étant caractérisé par sa forme physique ou sa forme galénique, p. ex. émulsion, particule, complexe d’inclusion, stent ou kit
A method securely erasing data on a storage drive includes transmitting a communication that initiates an erasure operation on a storage drive and receiving a drive erasure attestation generated in association with erasure operation and by a root-of-trust of the storage drive. The drive erasure attestation includes a first claim that contains cryptographic evidence of a measured state of the storage drive following the erasure operation. The method further includes verifying the first claim and instructing a ledger service to record the drive erasure attestation in a ledger in response to the verification. Verification of the first claim depends upon confirmation of a match between first measurement values in the first claim and a first set of stored values previously-verified as corresponding to a correct implementation of the erasure operation.
G06F 21/78 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du stockage de données
Systems and methods are provided for automatic recovery of node resource memory devices. A platform basic input/output system (“BIOS”) of a node collects, from a node resource of the node, operational state information for memory components of a memory device, and determines whether at least one memory component is undetected. If so, the platform BIOS sends a notification of the undetected memory component(s) to a controller of the node that relays the notification to a control plane fabric (“CPF”) agent in a control plane. The CPF agent automatically determines a potential cause and a potential resolution, including memory device reset, firmware updates, etc. The CPF agent sends commands to the controller that cause the platform BIOS to initiate a recovery process for the plurality of memory components of the memory device, based on the potential resolution.
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
Disclosed are methods for managing execution of plugins of a machine-learning based system. A plugin configuration defines inputs required by the plugin and capabilities provided by the plugin. Capabilities describe the plugin’s functionality, such as how the plugin affects the response, what type of content the plugin generates, etc. In some configurations, when responding to a prompt, a collection of relevant plugins is identified. Configurations of these plugins may be analyzed to optimize execution, including determining optimal execution order or enabling parallel execution. Plugin configurations may also be analyzed to improve security by conditionally preventing one plugin from accessing the output of another. Plugin configurations may also be used to inform a client what plugins will run and what results they may yield. This enables the client to optimize and streamline how the response is displayed.
G06F 21/51 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade du chargement de l’application, p. ex. en acceptant, en rejetant, en démarrant ou en inhibant un logiciel exécutable en fonction de l’intégrité ou de la fiabilité de la source
A computer-implemented method for compressed compact data storage and processing within a cloud-based environment is disclosed. In one aspect, the method for processing data signals, includes receiving a plurality of data signals corresponding to a user, the plurality of data signals includes a plurality of user raw records at corresponding time values, compressing the plurality of data signals using an incremental compression algorithm to form a single compressed iterative record, organizing the single compressed iterative record into hierarchical segments based on predefined time intervals using a waterfall data model, and storing the single compressed iterative record in a first cloud storage system.
A computer-implemented method for managing data in a computing environment. In one aspect, a method includes receiving a declarative input that indicates an outcome for data handling, identifying, from the declarative input, a predefined data filter configuration and a predefined data propagation configuration, filtering incoming data according to the predefined data filter configuration to generate filtered data, and replicating the filtered data to a data storage according to the predefined data propagation configuration.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p. ex. des interruptions ou des opérations d'entrée–sortie
A network element has a replication process between a first instance and a second instance of the network element, such that the second instance is able to take over functioning of the network element in the event of failure of the first instance. The first instance receives a desired configuration to be applied to the network element. The second instance also receives the desired configuration. The second instance drops the desired configuration it received. The desired configuration is mapped from a declarative form to an imperative form at the first instance and the imperative form of the desired configuration is executed at the first instance such that the desired configuration is applied at the network element.
H04L 41/082 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant des mises à jour ou des mises à niveau des fonctionnalités réseau
H04L 41/0663 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant la reprise sur incident de réseau en réalisant des actions prédéfinies par la planification du basculement, p. ex. en passant à des éléments de réseau de secours
Systems, methods, and software are disclosed herein for transferring a workflow from a source application to a destination application in various implementations. In an implementation, a computing apparatus receives a request from a source application to hand off a workflow to a destination application. In response to the request, the computing apparatus generates a handoff link for transferring the workflow from the source application to the destination application and transmits the handoff link to the source application.
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
67.
VIRTUALIZING DISCRETE AND MIGRATABLE TRUSTED PLATFORM MODULES (TPMS)
Systems and methods are provided for implementing virtualization of discrete and migratable cryptographic processors (e.g., trusted platform modules (“TPMs”)). In examples, an orchestrator in a control plane causes migration of a first cryptographic processor emulator (e.g., a TPM emulator) that has been instantiated on a first platform root of trust (“PROT”) to a second PROT, by requesting secret data (e.g., an endorsement seed associated with the cryptographic processor emulator, sealed secrets, etc.) stored in a first memory in the first PROT. The orchestrator receives the secret data, instantiates a second cryptographic processor emulator on the second PROT based on the secret data, and transfers the secret data to a second memory in the second PROT. The orchestrator instructs the cryptographic processor emulator on the first PROT to delete the secret data from the first memory, and sends a status of the migration to a requesting device that requested the migration.
A method for utilizing contextual data in generating machine translations. The method includes receiving a translation request including an initial prompt received via a user interface. The initial prompt includes a first language passage and a translation instruction. The initial prompt also includes a context data signal received via a context data source. The method further includes generating a context instruction based on the context data signal and generating a modified prompt including the initial prompt and the context instruction. The method further includes sending the modified prompt to a neural machine translation (NMT) model to process the modified prompt and receiving a second language translation passage as a response to the modified prompt. The second translation language passage being a second language translation of the first language passage translated according to the translation instruction and the context instruction.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
Systems and methods are provided for implementing server fast boot using cache-coherent interconnect memory. A cache-coherent interconnect node partitions a memory pool and pre-allocates a memory region of the memory pool to each compute node of a plurality of compute nodes. A basic input/output system (“BIOS”) of a compute node maps a local memory of the compute node to a memory region that has been pre-allocated to the compute node. The BIOS boots an operating system (“OS”) of the compute node in the memory region. Concurrent with the OS executing workloads using the memory region, the BIOS trains and initializes the local memory, after completion of which the BIOS notifies the OS that the local memory is ready. The OS migrates contents from the memory region to the local memory, and subsequently executes the workload from the local memory or a combination of the local memory and the memory region.
A method is disclosed for managing network communication in a virtual machine hosting computer system with nested child partitions. The method involves loading a network driver in a level-one child partition and creating a virtual switch within the level-one child partition. The virtual switch establishes a synthetic data path between a synthetic network adapter offered by a root partition and a network driver in a level-two child partition. A network interface controller (NIC) switch capability is exposed to the virtual switch, and a peripheral component interconnect express (PCIe) virtual function offered by the root partition is passed from the level-one child partition to the level-two child partition, enabling the level-two child partition to take advantage of the PCIe virtual function.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
71.
AUTOMATIC SILENT MODE EXCEPTION ACCORDING TO A TRUSTED CALLER
Systems and methods are provided for selectively generating a notification on a callee device for an incoming call for a call session. The caller device registers a callee as a trusted partner callee in the caller device, thereby enabling the caller to initiate a call session request as a priority call to the callee. The callee device registers the caller as a trusted partner caller in the callee device. The callee device enables the callee to activate the silent mode and an exception to the silent mode. The caller device transmits a call session request with a priority call to the callee device. The callee device rings to notify the callee about the incoming call upon receiving a call session request for a priority call from a trusted partner caller while the silent mode and the exception operation are both active. A call session starts when the callee device answers.
H04M 3/436 - Dispositions pour intercepter des appels entrants
H04L 65/1104 - Protocole d'initiation de session [SIP]
H04M 1/72454 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques en tenant compte des contraintes imposées par le contexte ou par l’environnement
H04M 1/72484 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles où les fonctions sont activées par la réception d’une démarche de communication
H04M 19/04 - Dispositions d'alimentation de courant pour systèmes téléphoniques fournissant un courant de sonnerie ou des tonalités de surveillance, p. ex. tonalité de numérotation ou tonalité d’occupation le courant de sonnerie étant produit aux sous-stations
Aspects of the present disclosure relate to engagement-based communication session management. In examples, an interaction intent metric is generated for a user according to a variety of factors relating to the user (e.g., the semantic content and tone of the user's speech, a direction of the user's gaze, and historical user characteristics) and the meeting (e.g., whether the user's name was mentioned by another communication participant or whether another communication participant is soliciting input), among other examples. Accordingly, if a positive interaction intent is identified and the user is currently muted, an action can be recommended to address the mismatch between the positive interaction intent and the muted status of the user. Similarly, if a negative interaction intent is identified and the user is currently unmuted, an action can be performed to address the mismatch between the negative interaction intent and the unmuted status of the user.
A computing system is provided, which receives a molecular graph at a message passing graph neural network (MPGNN), and produces scalar embeddings representing features of nodes and edges of the graph and vector embeddings representing geometric relationships of the graph. The system processes the scalar embeddings via a vector scalar interactive message passing mechanism of a message passing sub-block of the
A computing system is provided, which receives a molecular graph at a message passing graph neural network (MPGNN), and produces scalar embeddings representing features of nodes and edges of the graph and vector embeddings representing geometric relationships of the graph. The system processes the scalar embeddings via a vector scalar interactive message passing mechanism of a message passing sub-block of the
MPGNN to generate and pass scalar information from the scalar embeddings to an embedding space containing the vector embeddings. The system updates the vector embeddings based on the embedding space containing the scalar information and the vector embeddings. The system updates the scalar embeddings based on run-time geometry calculations of the geometric relationships encoded in the vector embeddings. The system computes an updated molecular graph based on the updated scalar and vector embeddings and outputs a target molecular property value based on the updated molecular graph.
G16C 20/70 - Apprentissage automatique, exploration de données ou chimiométrie
G06N 3/042 - Réseaux neuronaux fondés sur la connaissanceReprésentations logiques de réseaux neuronaux
G16C 10/00 - Chimie théorique computationnelle, c.-à-d. TIC spécialement adaptées aux aspects théoriques de la chimie quantique, de la mécanique moléculaire, de la dynamique moléculaire ou similaires
G16C 20/30 - Prévision des propriétés des composés, des compositions ou des mélanges chimiques
74.
QUERY RESPONSE GENERATION IN A DEVELOPER TOOL USING SEMANTICALLY RELATED KEYWORDS IN RELEVANT CODE CHUNKS
Techniques are described herein that are capable of responding to a query in a developer tool using semantically related keywords in relevant code chunks. A user-generated query regarding a location of an element in a codebase of a software development project is received. The codebase is parsed into code chunks. Semantically related keywords, including keywords from the user-generated query and other keywords that are semantically related to the keywords, are identified. Relevant code chunks are selected from the code chunks based on satisfaction of a relevancy criterion regarding the user-generated query. Execution of an instruction is triggered, which causes a visual representation of a response to the user-generated query to be generated. The execution of the instruction causes the visual representation to include at least portions of the relevant code chunks and further causes at least a subset of the semantically related keywords to be highlighted in the portions.
Innovations in encoder-side decisions that use the results of hash-based block matching are presented. For example, some of the innovations relate to ways of building hash tables that include some (but not all) uniform blocks. Other innovations relate to ways of determining motion vector resolution based on results of hash-based block matching. Still other innovations relate to scene change detection, including long-term reference picture selection and picture quality determination during encoding.
H04N 19/176 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c.-à-d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p. ex. un objet la zone étant un bloc, p. ex. un macrobloc
H04N 19/14 - Complexité de l’unité de codage, p. ex. activité ou estimation de présence de contours
H04N 19/142 - Détection de coupure ou de changement de scène
H04N 19/154 - Qualité visuelle après décodage mesurée ou estimée de façon subjective, p. ex. mesure de la distorsion
H04N 19/503 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage prédictif mettant en œuvre la prédiction temporelle
76.
COMPUTING DEVICE WITH INDEPENDENTLY COHERENT NODES
A computing device includes a system-on-a-chip. The computing device comprises a network interface controller (NIC) that hosts a plurality of virtual functions and physical functions. Two or more compute nodes are coupled to the NIC. Each compute node is configured to operate a plurality of Virtual Machines (VMs). Each VM is configured to operate in conjunction with a virtual function via a virtual function driver. A dedicated VM operates in conjunction with a virtual NIC using a physical function hosted by the NIC via a physical function driver hosted by the compute node. The computing device further comprises a fabric manager configured to own a physical function of the NIC, to bind virtual functions hosted by the NIC to individual compute nodes, and to pool I/O devices across the two or more compute nodes.
A method for recommending a computer hardware configuration, including: receiving, by a processor, a machine-readable specification of a computing task; extracting, by the processor, a plurality of features from the machine-readable specification of the computing task; supplying, by the processor, the plurality of features to a reinforcement learning model to generate a proposed computer hardware configuration to execute the computing task; and providing, by the processor, the proposed computer hardware configuration to a user.
According to examples, an apparatus may include a processor and a memory on which are stored machine-readable instructions that, when executed by the processor, may cause the processor to receive event data for a subject incident. The processor may filter a set of candidate incidents to identify a first predefined number of candidate incidents. The first predefined number of candidate incidents may be filtered based on a respective first similarity score assigned to each of the candidate incidents. The processor may assign a respective second similarity score to each of the identified first predefined number of candidate incidents. The second similarity score may be based on common property values between the subject incident and respective candidate incidents. The processor may identify and output a second predefined number of candidate incidents among the first predefined number of candidate incidents based on the assigned second similarity score.
The discussion relates to thermal management. One example can include a circuit board including inner, intermediate, and outer generally concentric zones and a cryogenically cooled chip located in the inner zone as well as non-cryogenic electronic components positioned in the outer zone. In this example, the intermediate zone can have a skeletonized configuration that slows thermal energy movement from the outer zone to the inner zone.
Methods, systems, and computer program products are provided that implement vector-related requests using query operators. For example, a system includes a database, a parser, a converter, an optimizer, and an execution engine. The database is associated with query operators that are non-vector-specific. The database stores a table with vector embeddings. The parser is configured to parse a request indicating a vector operation associated with the vector embeddings. The converter is configured to convert the vector operation into a logical operator tree comprising a representation of the request as a logical flow of the query operators, enabling the vector operation without vector-specific executable code or operators. The optimizer is configured to convert the logical operator tree into an executable plan. The execution engine is configured to execute the executable plan against the table with vector embeddings.
According to the implementation of the present disclosure, a solution for parsing the hierarchical relationship of elements in an image is provided. According to the solution, the second element in the first element is determined based on a feature(s) of the input image and the first element in the input image. The third element in the second element is detected based on the feature and the second element. The first element, the second element and the third element correspond to corresponding regions in the input image. Based on the determination of the second element and the detection result of the third element, a hierarchy indicating the relationship between elements in the input image is determined. In this way, the hierarchy of elements in the image can be obtained without post-processing.
G06V 10/86 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les représentations syntaxiques ou structurelles du motif d’image ou vidéo, p. ex. reconnaissance des chaînes symboliquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant des correspondances graphiques
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/776 - ValidationÉvaluation des performances
The description relates to dynamic memory management. One example includes an assembly that entails processing elements and memory. A dynamic UMA/NUMA configuration module is configured to facilitate managing a first region of the memory based upon a Uniform Memory Access (UMA) architecture and a second region of the memory based upon a Non-Uniform Memory Access (NUMA) architecture. The dynamic UMA/NUMA configuration module is configured to dynamically adjust ratios of the memory in the first region and the second region based upon workload changes on the processing elements.
Malware activity detection for networked computing systems is described. A network session record is provided to a machine learning (ML) model configured to generate an indication of whether the provided network session record evidences malware activity. The network session record indicates network traffic activity in a time period. Responsive to an indication by the ML model, correlation scores are calculated by, for each process session record in a process session record set, calculating a correlation score indicative of a correlation between the provided network session record and the process session record. Each process session record in the process session record set corresponds to a process executed by a computing device in the time period. A determination that a correlation score indicates a corresponding process session record is indicative of the evidenced malware activity is made. Responsive to the determination, a malware activity alert is generated.
Techniques are described herein that are capable of performing intent-based scheduling via a digital personal assistant. For instance, an intent of user(s) to perform an action (a.k.a. activity) may be used to schedule time (e.g., on a calendar of at least one of the user(s)) in which the action is to be performed. Examples of performing an action include but are not limited to having a meeting, working on a project, participating in a social event, exercising, and reading.
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06Q 10/063 - Recherche, analyse ou gestion opérationnelles
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
Various embodiments discussed herein are directed to improving existing technologies by enabling users to share content items directly from an operating system component, with little to no user interface input requirements at the underlying communications application. For instance, some embodiments receive an indication that a mouse pointer is hovering over an operating system taskbar icon and automatically produce a flyout window so that a user can share a currently opened application page to other users via a selection of a button within the flyout window. Such application page may be shared via a single selection at the flyout window or an additional “are you sure” or confirmation step. In this way, excessive drilling, navigation, and other user input at the application is reduced and simplified, thereby improving the user experience, content sharing accuracy, and computer resource consumption, among other improvements.
G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
H04L 12/18 - Dispositions pour la fourniture de services particuliers aux abonnés pour la diffusion ou les conférences
86.
BINOCULAR NEAR-EYE DISPLAY WITH DISPLAY ALIGNMENT TRACKER
A mixed-reality near-eye display system in a head-mounted display (HMD) device includes a display alignment tracker configured for monitoring virtual image pixels in binocular waveguide-based displays and providing adjustments to a display engine to reduce binocular and color misalignments that can occur from thermal expansion of HMD device components and mechanical shock and vibration during device use. Surface relief gratings, located on waveguide combiner plates guiding separate display colors, are configured to in-couple and guide virtual image light from a projector-based display engine and simultaneously out-couple light for the near-eye display and alignment tracking.
H04N 13/344 - Affichage pour le visionnement à l’aide de lunettes spéciales ou de visiocasques avec des visiocasques portant des affichages gauche et droit
H04N 13/361 - Reproduction d’images stéréoscopiques mixtesReproduction d’images stéréoscopiques et monoscopiques mixtes, p. ex. une fenêtre avec une image stéréoscopique en superposition sur un arrière-plan avec une image monoscopique
87.
ULTRA-LOW PRECISION WEIGHT QUANTIZATION OF MACHINE LEARNING MODEL
A computer system is provided that includes processing circuitry. The computer system being configured to implement a machine learning (ML) model having a transformer architecture that, during a training operation or inference operation, is configured to receive an activation input matrix of activation input values and obtain a weight matrix of weight values. The ML model is further configured to perform ultra-low precision (ULP) quantization by quantizing each of the weight values in the weight matrix to a corresponding selected value from a predefined set of binary or ternary quantized weight values and compute a matrix arithmetic result based on at least a portion of the weight matrix with the quantized weight values and at least a portion of the activation input matrix.
This document generally relates to computer mice that have customizable physical configurations. One example includes a mouse that has adjustable height, tilt, and cant relative to a horizontal reference surface. A host device, such as a computer is configured to generate a user interface (UI) through which a user can define a desired height, tilt, and cant and the host device configured to cause the mouse to automatically adjust to the desired height, tilt, and cant defined by the user on the UI.
G06F 3/038 - Dispositions de commande et d'interface à cet effet, p. ex. circuits d'attaque ou circuits de contrôle incorporés dans le dispositif
G06F 3/0354 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection des mouvements relatifs en deux dimensions [2D] entre le dispositif de pointage ou une partie agissante dudit dispositif, et un plan ou une surface, p. ex. souris 2D, boules traçantes, crayons ou palets
Systems and methods are provided for automated incident investigation. Anomaly detection is used to identify anomalies in incident data (e.g., alerts, changes, metrics, logs, and/or system health), and the identified anomalies are converted into facts (or textual prompt inputs for a large language model (“LLM”)). A troubleshooting or diagnostic system is run on the anomalies to provide additional facts to identify a root cause of an incident. The facts from the diagnostics, the facts from the anomaly detections are entered into a consolidated explainer that generates a summary of what happened, what is a likely cause, and what to do next to resolve the issue. In examples, anomaly enrichment data including a time correlation result, a weighted list of abnormal transaction patterns, a list of abnormal trace patterns, a list of exception patterns, a difference pattern, and/or region data are input as further facts to enhance the incident investigation process.
Systems and methods are provided for automated incident investigation. Anomaly detection is used to identify anomalies in incident data (e.g., alerts, changes, metrics, logs, and/or system health), and the identified anomalies are converted into facts (or textual prompt inputs for a large language model (“LLM”)). A troubleshooting or diagnostic system is run on the anomalies to provide additional facts to identify a root cause of an incident. The facts from the diagnostics, the facts from the anomaly detections are entered into a consolidated explainer that generates a summary of what happened, what is a likely cause, and what to do next to resolve the issue. In examples, anomaly enrichment data including a time correlation result, a weighted list of abnormal transaction patterns, a list of abnormal trace patterns, a list of exception patterns, a difference pattern, and/or region data are input as further facts to enhance the incident investigation process.
A computing system including one or more processing devices that train an oversubscription reinforcement learner at least in part by receiving computing resource usage trajectories. At the oversubscription reinforcement learner, the training further includes generating prototypes based at least in part on the computing resource usage trajectories. The training further includes, based at least in part on the prototypes, generating an oversubscription rate. The training further includes outputting a prototype feedback query and/or an oversubscription rate feedback query. The training further includes receiving a prototype feedback input and/or an oversubscription rate feedback input. Based at least in part on the computing resource usage trajectories, the prototypes, and the prototype feedback input and/or the oversubscription rate feedback input, the training further includes computing an objective function value and training the oversubscription reinforcement learner based at least in part on the objective function value.
Systems and methods are directed to training and utilizing a generative language model that is constrained by a predetermined template that is used to train the generative language model. Once trained, customer data is accessed and transmitted to an evaluation component associated with the generative language model. The generative language model generates one or more sentences based on a feedback input of the plurality of feedback inputs, whereby the one or more sentences each include a sentiment, a target, and a reason for the sentiment in a format defined by the predetermined template. The evaluation component then identifies the sentiment, the target, and the reason from a sentence of the one or more sentences. A communication is then presented, on a device of a user, based on at least the sentiment and the reason identified from the sentence. The communication can be an alert or a report.
This disclosure generally relates to securely launching a hypervisor and subsequently validating that the hypervisor was securely launched. As is described herein, once a hypervisor has been initialized or has otherwise launched, a verification operation is performed. The verification operation may be used to ensure that the hypervisor was securely launched. When it is determined that the hypervisor was securely launched, one or more platform details are obtained. These platform details may then be stored in a memory device.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 21/51 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade du chargement de l’application, p. ex. en acceptant, en rejetant, en démarrant ou en inhibant un logiciel exécutable en fonction de l’intégrité ou de la fiabilité de la source
To optimize the compilation of shaders for execution within an application, a computer system discovers the context in which the shaders are executed. The application is compiled and executed on a target platform. Snapshots of the application during execution are captured. A snapshot includes data and commands passed between the central processing unit and the graphics processing unit of the target platform to generate a single frame of graphics data. The shaders used in these snapshots are identified. These shaders are compiled with a number of different permutations of available compiler options, resulting in sets of differently compiled shaders. The snapshot is re-executed with the sets of differently compiled shaders, and performance is measured. The set of compiler options that results in compiled shaders providing better performance can be used as the set of compilation parameters for the set of shaders for this application.
G06T 1/20 - Architectures de processeursConfiguration de processeurs p. ex. configuration en pipeline
G09G 5/36 - Dispositions ou circuits de commande de l'affichage communs à l'affichage utilisant des tubes à rayons cathodiques et à l'affichage utilisant d'autres moyens de visualisation caractérisés par l'affichage de dessins graphiques individuels en utilisant une mémoire à mappage binaire
95.
AUTOMATION OF VISUAL INDICATORS FOR DISTINGUISHING ACTIVE SPEAKERS OF USERS DISPLAYED AS THREE-DIMENSIONAL REPRESENTATIONS
Systems and methods are disclosed for enhancing identification of active speakers in communication sessions conducted within three-dimensional (3D) environments. A first user interface arrangement displays 3D representations of participants from a virtual camera perspective, wherein an avatar of a participant may be oriented so that its face is not visible. Upon detecting the participant as an active speaker from a speech signal, the system transitions to a second user interface arrangement that concurrently displays a two-dimensional (2D) live video stream of the active speaker and the 3D representation of the active speaker. The transition further includes modifying a position or orientation of the virtual camera to render the avatar from a perspective that reveals the avatar's face. By combining the 2D live video stream with the reoriented 3D avatar view, the system improves visual cues of speech activity, reduces missed conversational content, and enhances engagement in immersive meetings.
G06F 3/04815 - Interaction s’effectuant dans un environnement basé sur des métaphores ou des objets avec un affichage tridimensionnel, p. ex. modification du point de vue de l’utilisateur par rapport à l’environnement ou l’objet
G10L 25/78 - Détection de la présence ou de l’absence de signaux de voix
H04L 65/403 - Dispositions pour la communication multipartite, p. ex. pour les conférences
A diffusion model is implemented in the analog processing domain. Analog restoration model circuitry is configured to denoise an analog signal (referred to as ‘signal restoration’ processing). Analog noise injection circuitry coupled to the analog restoration model circuitry receives the denoised signal and injects an amount of noise back into it. The resulting noise-injected signal is fed back to the analog restoration model circuitry for further signal restoration processing, and the resulting signal is again passed to the noise injection circuitry for noise injection. Various mechanisms for implementing the noise injection stage in the analog domain are described. In a first example embodiment, a constant noise signal is applied with a variable scaling factor. In a second example embodiment, a variable noise signal is generated using analog noise generation circuitry.
G06N 3/067 - Réalisation physique, c.-à-d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone utilisant des moyens optiques
Examples described herein generally relate to systems and methods for handwriting recognition. In an example, a computing device may receive input corresponding to a handwritten word and apply first recognition model to the input. The first recognition model may be configured to determine a first confidence level of a first portion of the input is greater than a second confidence level of a second portion of the input. The computing device may also apply a second recognition model to the input, wherein the second recognition model is different from the first recognition model and combine results of the first recognition model and the second recognition model to determine a list of candidate words. The computing device may also output one or more candidate words from the list of candidate words.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 30/24 - Reconnaissance de caractères caractérisée par la méthode de traitement ou de reconnaissance
G06V 30/262 - Techniques de post-traitement, p. ex. correction des résultats de la reconnaissance utilisant l’analyse contextuelle, p. ex. le contexte lexical, syntaxique ou sémantique
98.
HYPERPARAMETER TRANSFER VIA THE THEORY OF INFINITE-WIDTH NEURAL NETWORKS
Systems and method are provided that are directed to tuning a hyperparameter associated with a small neural network model and transferring the hyperparameter to a large neural network model. At least one neural network model may be received along with a request for one or more tuned hyperparameters. Prior to scaling the large neural network, the large neural network is parameterized in accordance with a parameterizing scheme. The large neural network is then scaled and reduced in size such that a hyperparameter tuning process may be performed. A tuned hyperparameter may then be provided to a requestor such that the hyperparameter can be directly input into the large neural network. By tuning a hyper parameter using a small neural network, significant computation cycles and energy may be saved.
The automatic detection of inconsistencies in a database system is described. A first signature and a second signature are received. The first signature is a signature of a result of a first execution of the query against a database by a first version of database engine program code. The second signature is a signature of a result of a second execution of the query by a second version of the database engine program code. A determination is made of whether the first signature and the second signature match. In response to the first signature and the second signature failing to match, an inconsistency report regarding at least one of the first or second versions of the database engine program code is generated and remediation regarding at least one of the first or second versions of the database engine program code is performed.
A distributed query processor in a server is configured for compute scale and cache preservation to enable efficient cluster usage for query processing. The query processor includes an operator analyzer and an operator scheduler. The operator analyzer determines a first operator, of a graph of operators representative of a user query, to have a first characteristic and assigns the first operator to a first node set of a plurality of node sets. The first node set is associated with the first characteristic. A second node set of the node sets is associated with a second characteristic different from the first characteristic. The operator scheduler is configured to cause the first operator to be executed in the assigned first node set to generate a first operator result, and a query result to be generated based at least on the first operator result.
brevets
