Described techniques and systems can obtain a request to process metric data based on observation of a computer-implemented resource. The request can be authenticated. Based at least on authenticating the request, the request can be augmented to include data linked to the computer-implemented resource. The metric data can be processed based on the augmented request, the processing can include disseminating the metric data.
Implementations for providing event processing services that associate multiple accounts are described. A user of a first account may have rules for event processing that cause the event to be sent to a second account. If a received event satisfies the rule, the event may be processed for the first account and processed for the second account using a single processing node and/or single rule evaluation sequence.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06N 5/025 - Extraction de règles à partir de données
A speech-processing system may be configured to generate expressive synthesized speech. The system may include a prosody prediction model that generates a combination of durations and acoustic representations that may be based on the content of the text as well as additional context information. The model may be trained to predict a joint probability between linguistic representations (e.g., derived from text) and combined duration/acoustic representations (e.g., derived from audio). At inference, the model can process linguistic representations derived from text to predict combined duration/acoustic representations. In some implementations, the model may process additional information; for example, semantic embeddings output by a language model based on the text. In another example, the model may receive a speaker embedding representing voice characteristics of a particular speaker. A decoder may process the durations and acoustic representations output by the model to generate audio data representing the synthesized speech and representing expressive prosodic variation.
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
Described is an aerial vehicle landing pad configured to capture various metrics regarding landing of an aerial vehicle thereon. The landing pad may be formed of layers, such as one or more sensors layers enclosed in protective layers. The landing pad may include elements with force sensors to sense a force of a landing of an aerial vehicle on the landing pad. The landing pad may include elements with pressure sensors to determine elements subject to pressure from landing structures of the aerial vehicle on the landing pad. Locations of the elements that indicate a pressure signal may be used determine a location of the aerial vehicle on the landing pad, an orientation of the aerial vehicle, and/or a type of aerial vehicle.
G01L 5/00 - Appareils ou procédés pour la mesure des forces, du travail, de la puissance mécanique ou du couple, spécialement adaptés à des fins spécifiques
B64D 45/00 - Indicateurs ou dispositifs de protection d'aéronefs, non prévus ailleurs
A query placement system to receive a query from a client of a managed database service and identify a pool of processing clusters, respectively capable of processing the query. The query placement system randomly selects a first subset of two or more processing clusters from the pool of processing clusters. The query placement system sends the query to a first selected processing cluster in the first subset, wherein the first selected processing cluster is selected based on utilization data for the pool of processing clusters. The query placement system receives a response indicating that the selected processing cluster does not accept the query for execution, the response includes an estimated utilization for the query executing at the first selected processing cluster. The query placement system sends the query to a second selected processing cluster of the second subset based on the utilization data and the estimated utilization for the query.
Techniques for generating synthetic data and/or machine learning model testing are described. For example, synthetic data may be generated according to a request by selecting one or more transformation modules to be used to generate synthetic data, instantiating the selected one or more transformation modules, and applying the selected one or more transformation modules in a defined order to at least one dataset to generate synthetic data.
This disclosure describes, in part, techniques for implementing customized privacy zones for security monitoring. In embodiments, such techniques may comprise receiving first data defining a first area associated with a privacy zone, receiving image data generated by a camera, the image data encompassing at least a portion of the first area, determining a position of an object detected within the image data, and determining, based on the first data and the position of the object, that the object is outside of the first area associated with the privacy zone, The techniques may further comprise defining a portion of image data that corresponds to the first area less a second area associated with the object detected within the image data, applying at least one obfuscation technique to the portion of image data, and sending the image data having the applied obfuscation technique to at least one second electronic device.
Approaches presented herein relate to the analysis and/or management of a communication network including resources from multiple, independent communications networks. At least one edge device can be placed within individual communication networks, allowing for the capture and anonymization of data from the various provider networks. The data for various users can be aggregated by location and associated with an identifying key. A cloud-based service can generate a snapshot using this data from the various individual networks, and a decision engine can be used to generate a set of recommendations or actions to improve operation (e.g., performance or security, etc.) of the network or perform actions such as disaster recovery. The recommendations or actions can be provided for individual devices, locations, communication networks, or providers but based upon the data aggregated and analyzed across multiple individual networks.
H04W 24/00 - Dispositions de supervision, de contrôle ou de test
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04W 24/02 - Dispositions pour optimiser l'état de fonctionnement
Computing systems and associated methods are described for managing error conditions associated with shared resources in a partitioned computing system. In some examples, a flush signal is generated by a controller of an expansion card or other component of the partitioned computing system responsive to detecting a communication issue between the component and a first host partition. Responsive to the flush signal, an Input/Output (I/O) fabric of the component terminates active memory transactions for the first host partition and transmits a success status signal associated with the active memory transactions to an initiator of the active memory transactions. The controller may then reset a port coupled to the first host partition to prepare the component for re-establishing a link with the first host partition.
G06F 13/42 - Protocole de transfert pour bus, p. ex. liaisonSynchronisation
G06F 11/22 - Détection ou localisation du matériel d'ordinateur défectueux en effectuant des tests pendant les opérations d'attente ou pendant les temps morts, p. ex. essais de mise en route
G06F 13/16 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus de mémoire
G06F 13/28 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus d'entrée/sortie utilisant le transfert par rafale, p. ex. acces direct à la mémoire, vol de cycle
13.
Stereo structured light machine vision system for guidance of automated tote exchange equipment
Inventory systems may include an inventory holder, a transfer apparatus, and a stereo vision system localized to determine a three dimensional (3D) pose of the inventory holder. The stereo vision system includes a first camera and a first laser disposed at a first end portion of a platform, and a second camera and a second laser disposed at a second end portion of the platform. The first camera and the first laser being localized to capture a first image of a first frame portion of an opening of the inventory holder. The second camera and the second laser being localized to capture a second image of a second frame portion of the opening. Furthermore, one or more processors can be configured to determine the 3D pose of the inventory holder based on the first image and the second image.
B65G 1/137 - Dispositifs d'emmagasinage mécaniques avec des aménagements ou des moyens de commande automatique pour choisir les objets qui doivent être enlevés
Automated container accumulation and delivery systems and methods may include a magazine body, a slide, and a workstation. The magazine body may receive and store a plurality of containers in vertical magazine lanes. Upon request, a container may be released from a lowest position of a magazine lane, and the slide may guide the released container to the workstation for processing. In addition, remaining containers within the magazine lane from which the container was released may be moved or indexed downward in order to prepare another container for release from the lowest position of the magazine lane responsive to a subsequent request.
B65G 1/08 - Dispositifs d'emmagasinage mécaniques avec des moyens pour que les objets se présentent à l'enlèvement dans des positions ou à des niveaux prédéterminés les objets étant amenés par pesanteur
In various examples, a first robot assigned to carry a first load may be determined. An estimated queuing time at a work station may be determined. A processing time associated with processing the first load at the work station may be determined. An arrival time for the first robot may be determined by: combining the estimated queuing time and the processing time to determine a total amount of time for the first robot; determining a first time period that is after an earliest arrival time and which is associated with available occupancy at the work station for at least the total amount of time; and determining the arrival time for the first robot as the beginning of the first time period. The first robot may be controlled to cause the first robot to arrive at the work station at the arrival time.
B65G 1/137 - Dispositifs d'emmagasinage mécaniques avec des aménagements ou des moyens de commande automatique pour choisir les objets qui doivent être enlevés
G05B 19/4155 - Commande numérique [CN], c.-à-d. machines fonctionnant automatiquement, en particulier machines-outils, p. ex. dans un milieu de fabrication industriel, afin d'effectuer un positionnement, un mouvement ou des actions coordonnées au moyen de données d'un programme sous forme numérique caractérisée par le déroulement du programme, c.-à-d. le déroulement d'un programme de pièce ou le déroulement d'une fonction machine, p. ex. choix d'un programme
16.
Adapting concurrency to support machine learning model prediction
A database system may include a machine learning model which may be used to perform various data analytics for data stored in the database system. In response to a request to invoke the machine learning model to generate a prediction from data stored in the database system, the database system may evaluate the request to determine whether to perform the request at a primary query engine or assign the request to another computing resource distinct from the primary query engine. The database system may provision the other computing resource as needed to create a secondary query engine to use the machine learning model to generate the prediction as requested.
Techniques for resource leak detection and reclamation are described. Application code executed by multiple processors is modified, during runtime, to insert an unconditional branch into the code leading to separate accounting code, which registers accesses to particular resources in a data structure. The unconditional branch is later removed and the data structure is analyzed to determine whether ones of the resources have been lost.
Systems and techniques are generally described for selecting a machine learning model for compression artifact removal and resolution upscaling of video streaming data. In various examples, a system or method receives a stream of video data, determines a category of the stream of video data based at least partially upon a compression level of the stream of video data, selects weights for a machine learning model based upon the category, and executes the machine learning model with the selected weights to remove compression artifacts in the stream of video data and upscale a resolution of the stream of video data.
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
Techniques are described herein for providing variable length text during playback of a video. Audio corresponding to a portion of the video may be identified and segmented by a neural network. A number of captions of varying length can be identified for each segment using a second neural network. The user may be presented with a user interface that enables playback of various portions of the video (e.g., options corresponding to previously uttered sentences). During playback, one of the captions may be provided. Which caption is presented may be controlled by the user. At least some of these captions can be shorter than the actual words spoken during the segment, while still providing the same or substantially similar semantic meaning.
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
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
H04N 21/488 - Services de données, p. ex. téléscripteur d'actualités
A machine learning model may be configured for training using an associated learning technique. A model configured for end-to-end backpropagation may adapted for associated learning by introducing functions for projecting hidden vectors and labels to a shared representation space and for reconstructing labels from representation vectors. An associated learning loss may be calculated at each layer, with the resulting gradients backpropagated locally through that layer rather than all layers. A reconstruction loss may be calculated using each layer's output including the predicted label. Training by associated learning may be parallelized (e.g., layer by layer) to yield efficiency gains. In addition, associated learning training may be more robust to training label errors. The resulting model may be used to, for example, predict data sequences in an autoregressive manner in which subsequent portions of the output data sequence are predicted in part based on previous predicted portions of the output data sequence.
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
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
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
22.
Optimal play route prediction during sports broadcasts
Systems and techniques are described for providing optimal play route prediction during sports broadcasts. In various examples, a first frame of tracking data indicating a first respective location of each player of a first plurality of players on a field plane may be received at a first time. A first predicted direction of motion may be determined for the first frame based at least in part on a first objective. A second frame of tracking data indicating a second respective location of each player of the first plurality of players on the field plane may be received at a second time. A second predicted direction of motion for the second frame may be determined based at least in part on the first objective. A first graphical overlay may be displayed on a live video feed based on one or more of the first predicted direction and the second predicted direction.
G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p. ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
A63B 24/00 - Commandes électriques ou électroniques pour les appareils d'exercice des groupes
Systems, apparatuses, methods, and techniques are described for feedback-based multimodal fragment retrieval. An example method includes receiving user input data comprising a user search query. The example method also includes determining, based on the first user search query, a first and second set of search parameters. The example method also includes generating search execution plan. The example method also includes retrieving, based on executing the search execution plan with respect to a set of candidate retrieval sources, a first set of relevant multimodal fragments. The example method also includes generating a first multimodal search result object, wherein the first multimodal search result object comprises at least a subset of the first set of relevant multimodal fragments. The example method also includes providing the first multimodal search result object to at least a first user device associated with the first user.
Systems and methods provide for a multi-modal development environment to receive inputs using a variety of different input modalities in different user interfaces (UIs). Multiple user interfaces may be linked within the development environment to maintain state information so that inputs provided to one UI are represented in the other UIs using an appropriate equivalent representation based on the UI modality. Users of the development environment may select a given UI for interaction based on a desired task and then see changes tracked and relayed through the different UIs to verify changes within the development environment. The UIs may also be contextually linked to permit the user to work between both UIs without losing the context due to the switch.
Linear playout provides media content according to a schedule, including live events. Media pipelines for ingesting and providing live event content may be allocated and torn down before and after each live event. Allocating media pipelines for each live event in a season reduces computational resource consumption.
H04N 21/238 - Interfaçage de la voie descendante du réseau de transmission, p. ex. adaptation du débit de transmission d'un flux vidéo à la bande passante du réseauTraitement de flux multiplexés
H04N 21/262 - Ordonnancement de la distribution de contenus ou de données additionnelles, p. ex. envoi de données additionnelles en dehors des périodes de pointe, mise à jour de modules de logiciel, calcul de la fréquence de transmission de carrousel, retardement de la transmission de flux vidéo, génération de listes de reproduction
H04N 21/845 - Structuration du contenu, p. ex. décomposition du contenu en segments temporels
26.
Systems and methods for mitigating audio-video misalignment
Systems and methods for mitigating audio-video misalignment are provided. The systems and methods involve detecting an audio cue within an audio signal associated with the live content (for example, the audio captured by a microphone at the source of the live content). When the audio cue is detected, a visual element at the source of the live content is manipulated to produce a visual cue within the video signal of the live content. When the video and audio are being processed for transmission to the viewer devices, when a portion of the audio signal includes the audio cue, the corresponding video frame(s) may be checked to determine if the visual cue within the video frame(s). If not, then it may be determined a misalignment exists between the video and audio signals in the live content. An action may then be taken to remedy the misalignment, such as introducing a delay into the video or audio signal.
An address decode and translate (ADT) circuit includes an address decode circuit configured to receive and decode transactions issued by a plurality of source nodes, and a resolution circuit configured to make certain resolutions and decisions based on results of decoding the transactions. For example, the resolution circuit can determine, among a plurality of target nodes of an adapter device, respective target nodes for performing the transactions, and translate transaction addresses of the transactions to local addresses of the adapter device. The resolution circuit is also configured to perform, for example, enabling monitoring of the execution of the transactions, detecting a denial-of-service (DOS) attack by the transactions, reordering the transactions, determining data caching attributes for the transactions, or a combination.
Techniques for amplification reflection attack protection using routing policy-aware traffic handling are described. A routing policy is indicative of how clients are to be routed amongst multiple destinations for a resource. The routing policy can be used to configure a responder component to enable the responder component to determine which sources of traffic it should expect. When unexpected traffic arrives at the responder, such as spoofed traffic that is part of an amplification reflection attack, the responder can drop the traffic or perform another remediative action to protect the attack target.
An autonomous mobile device (AMD) performs operations associated with task requests received from sources such as user input, internal or external processes, and so forth. A task request may comprise adaptive and non-adaptive conditions. Adaptive conditions may be satisfied by operation of the AMD, such as finding a particular person or moving to a particular location. Non-adaptive conditions are satisfied without operation by the AMD. A task request may be selected for execution when a current state of the AMD corresponds to conditions specified by the task request. Metatask(s) associated with a task request may be determined. For example, a task request that involves interacting with a particular person has a metatask of finding that particular person. A task request for which all conditions are satisfied may be enqueued for execution. A metatask associated with a task request that has its non-adaptive conditions satisfied may be enqueued for execution.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
Improved resource utilization based-modeling is described herein. In an example, a computer system receives layout data indicating a layout of storage areas, staging areas, and material handling equipment configured to move items to at least the storage areas. The computer system receives first association data indicating staging area-to-delivery resource associations and second association data indicating item-to-delivery resource associations corresponding to items to be delivered. The computer system generates an input to a model based on the layout data, the first association data, and the second association data. The computer system determines an output of the model based on the input. The output is generated by the model based on a storage area-to staging area travel distance minimization. The output indicates a distribution of the items across the storage areas. The computer system causes a device to present, in a user interface, the layout and the distribution based on the output.
Systems and techniques are described for motion detection. In various examples, a radar sensor may transmit at least a first frame and a second frame over a first period of time. Difference data representing differences between at least a first signal corresponding to the first frame and a second signal corresponding to the second frame may be determined by the radar sensor. First data may be determined by a passive infrared (PIR) sensor over the first period of time. A first machine learning model may generate, using the difference data and the first data, second data indicating whether motion is detected during the first period of time.
G01S 13/536 - Discrimination entre objets fixes et mobiles ou entre objets se déplaçant à différentes vitesses utilisant la transmission d'ondes continues non modulées, ou modulées en amplitude, en fréquence ou en phase
G01S 13/86 - Combinaisons de systèmes radar avec des systèmes autres que radar, p. ex. sonar, chercheur de direction
A system for determining whether image data is authentic based on a projected light pattern is described. The system is configured to obtain image data submitted to a biometric authorization system that applies facial recognition techniques to the image data to make an authorization determination. The system is further configured to apply a detection model to the image data to generate an image synthesis score for the image data, wherein the detection model is trained to detect synthesized image data according to a light pattern projected onto a target during image data capture. The system classifies the image data as fake according to the image synthesis score. The system makes the authorization determination for the image data according to the classification of the image data as fake.
A system that implements a scaleable data storage service may maintain tables in a data store on behalf of storage service clients. The service may maintain data in partitions stored on respective computing nodes in the system. The service may support multiple throughput models, including a committed throughput model and a best effort throughput model. A service request to create a table may specify that requests directed to the table should be serviced under a committed throughput model and may specify the committed throughput level in terms of logical service request units. The service may reserve low-latency storage and other resources sufficient to meet the specified committed throughput level. A client/user may request a modification to the committed throughput level in anticipation of workload changes, such as an increase or decrease in traffic or data volume. In response, the system may increase or decrease the resources reserved for the table.
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
A multimedia streaming device can include a first circuit board configured to provide user controls and a second circuit board electrically coupled with the first circuit board and configured to provide content processing. The multimedia streaming device can also include a heat sink positioned between the first circuit board and the second circuit board and defining a speaker enclosure that includes a first portion in contact with the first circuit board, a second portion in contact with the second circuit board, and a third portion. The multimedia streaming device can additionally include a speaker installed in the third portion of the speaker enclosure.
Techniques for generating a prompt for a language model to determine an action responsive to a user input, are described. In some embodiments, the system receives a user input, determines one or more application programming interfaces (APIs) configured to perform actions that are relevant to the user input and exemplars representing examples of using the APIs with respect to user inputs similar to the current user input. The system further determines device states of devices that are determined to be related to the user input and also determines other contextual information (e.g., weather information, time of day, geographic location, etc.). The system generates a prompt including the user input, the APIs, the exemplars, the device states, and the other contextual information. A language model processes the prompt to determine an action responsive to the user input and the system causes performance of the action.
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
System and methods are provided for estimating the sound field from partial observations. Estimating an acoustic environment for virtual reality and augmented reality applications is a step in the creation of simulated acoustic sound scenes. In particular, the impulse responses of room can be estimated with a generative model. In a teleconferencing scenario with remote participants and a group of participants in a common physical space, giving the remote participants the impression that all other participants are sitting is in the same room acoustically requires filtering the speech of the remote participants with impulse responses estimated at the desired rendering position in the conference room.
G10K 11/178 - Procédés ou dispositifs de protection contre le bruit ou les autres ondes acoustiques ou pour amortir ceux-ci, en général utilisant des effets d'interférenceMasquage du son par régénération électro-acoustique en opposition de phase des ondes acoustiques originales
40.
DOWN-SIZED CLUSTER PERFORMANCE MODELING FOR A TIERED DATA PROCESSING SERVICE
Methods for modeling performance of tiered storage of a data processing service given a decrease in the storage capacity of a warm storage tier of the tiered storage are disclosed. Metadata of the warm storage tier is used to track hits due to incoming queries on data blocks that are stored in the warm storage tier. The metadata prioritizes data block identifiers that correspond to the data blocks stored in the warm storage tier by frequency of hits due to the incoming queries, or various other prioritization schemes. One or more partitions of the metadata may be set that correspond to respective downsized storage capacity scenarios of the warm storage tier. When an incoming query targets a data block within a given partition of the metadata, a hit counter is incremented to track the hit rate that would be made on the downsized warm storage tier corresponding to that partition.
Methods and apparatus are described for delivering streams of media content in ways that maintain compatibility among different streaming protocols for inserting secondary content into the streams of media content. This is accomplished by encoding media content the same for each streaming protocol but generating different output groups based on each streaming protocol.
Embodiments of a privacy preserving supplemental content server (PPSCS) implements a privacy preserving protocol with a content server that requests the PPSCS to serve supplemental content for users. In embodiments, a user-to-segment map (USM) containing user-private information is split into secret shares and stored separately at the PPSCS and the content server. When servicing a request, the USM data is used to identify a key segment of a user, which is in turn used to select a supplemental content for the user. Advantageously, the selection process is performed according to the privacy preserving protocol, which guarantees that (a) the content server does not learn any user-private information about the user in the USM, (b) the PPSCS learns at most one user segment of the user (e.g. the key segment), and (c) the PPSCS cannot track the user over time using any user-private information about the user learned during the execution.
A model deployment tuning system (MDTS) receives a trained ML model, specified constraints, and model evaluation data and applies a plurality of model utilization techniques to the trained ML model to produce a plurality of useable model versions of the trained ML model. The MDTS executes each of the plurality of useable model versions of the trained ML models on a plurality of different compute instance types using the model evaluation data to produce model evaluation results for a plurality of different combinations. The MDTS filters the model evaluation results based on the specified constraints to indicate one or more of the different combinations satisfying the specified constraints. The MDTS deploys one of the plurality of useable model versions of the trained ML model to a compute instance types according to a selected combination satisfying the specified constraints.
A system that improves beacon discovery by enabling a device to determine a dynamic threshold and connect to a gateway that satisfies the dynamic threshold. For example, the device may iteratively scan through available channels for a first duration of time, detecting beacon signals and storing corresponding signal strengths, then calculate a dynamic threshold value using the stored information. In some examples, the dynamic threshold value is calculated using a sum and counter implementation, with the counter incrementing with each beacon signal detected and a summing component adding the signal strength. Additionally or alternatively, the device may switch between performing first beacon discovery using a static threshold and performing second beacon discovery using a dynamic threshold. For example, the device may perform the first beacon discovery when movement of the device exceeds a threshold, while performing the second beacon discovery when movement of the device is below the threshold.
H04W 48/16 - ExplorationTraitement d'informations sur les restrictions d'accès ou les accès
H04W 24/04 - Configurations pour maintenir l'état de fonctionnement
H04W 48/10 - Distribution d'informations relatives aux restrictions d'accès ou aux accès, p. ex. distribution de données d'exploration utilisant des informations radiodiffusées
A loading apparatus may include a chute passageway, a gate, and a splitter. The chute passageway may include a chute surface positioned extending along at least a portion of a distance between an inlet opening of the chute and an outlet opening of the chute passageway. The gate may be moveable between a closed position obstructing passage through the outlet opening and an open position permitting passage through the outlet opening. The splitter may be mechanically coupled with the gate by a linkage configured to convert movement of the gate toward the closed position into movement of the splitter toward an away position so as to split a traveling wall of a receptacle away from a base wall of the receptacle when the receptacle is received with the base wall along the chute surface.
B65B 43/46 - Alimentation ou positionnement des sacs, boîtes ou cartons en position dilatée, ouverte ou deboutAlimentation des réceptacles préformés rigides, p. ex. boîtes en fer-blanc, capsules, tubes en verre, flacons, vers la position d'empaquetageMise en place des réceptacles ou récipients au poste de remplissageMaintien des réceptacles ou récipients pendant le remplissage en se servant de griffes
This disclosure describes, in part, techniques for using presence detection in order to switch between power modes of a device. The disclosure relates to detection of oscillating and rotating objects (or other repetitive motion objects) for rejection of radar returns related to the motion of such objects. Accordingly, the systems described herein provide for identifying radar returns as related to a repetitive motion object in proximity of the device. The radar returns can be processed to determine if related to a repetitive motion object such as a fan or a non-repetitive motion object such that the device can be controlled for presence detection based on actual presence and avoiding false presence detections due to repetitive motion and movement.
G01S 13/56 - Discrimination entre objets fixes et mobiles ou entre objets se déplaçant à différentes vitesses pour la détection de présence
G01S 7/41 - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe utilisant l'analyse du signal d'écho pour la caractérisation de la cibleSignature de cibleSurface équivalente de cible
H04N 21/44 - Traitement de flux élémentaires vidéo, p. ex. raccordement d'un clip vidéo récupéré d'un stockage local avec un flux vidéo en entrée ou rendu de scènes selon des graphes de scène du flux vidéo codé
H04N 21/442 - Surveillance de procédés ou de ressources, p. ex. détection de la défaillance d'un dispositif d'enregistrement, surveillance de la bande passante sur la voie descendante, du nombre de visualisations d'un film, de l'espace de stockage disponible dans le disque dur interne
H04N 21/443 - Procédés de système d'exploitation, p. ex. démarrage d'un boîtier décodeur STB, implémentation d'une machine virtuelle Java dans un boîtier décodeur STB ou gestion d'énergie dans un boîtier décodeur STB
48.
Distributed processing of partitioned and ordered data
Scheduling of time-series data samples for processing according to client-specified criteria is performed. A client may submit a request to establish an execution pipeline to process time-series data, the request including a partitioning definition and an ordering definition. Responsive to this request, a scheduler may receive a time-series data sample and generate a partitioning key according to the partitioning definition to direct the sample to one of multiple partition queues. After enqueuing, the schedular may determine that the sample should be blocked from processing until satisfaction of an unblocking condition is achieved. This satisfaction may include processing of one or more other samples according to the ordering definition or a time period has elapsed. Blocking criteria may also include limitations in a number of simultaneously executing sample processes. Processing of samples of different queues may occur independently.
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 9/52 - Synchronisation de programmesExclusion mutuelle, p. ex. au moyen de sémaphores
G06F 16/14 - Détails de la recherche de fichiers basée sur les métadonnées des fichiers
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 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
A system and method for estimating values of an operator, such as energy levels of a Hamiltonian, is disclosed. The estimation is performed in a way such that the runtime of performing the estimation is independent of a complexity of the operator, e.g., a number of terms in the Hamiltonian. Also, errors can be statistically suppressed by performing additional sampling, due to a lack of biased error in the estimator. Additionally, samples may be tested using only a single ancilla qubit.
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
G06F 17/14 - Transformations de Fourier, de Walsh ou transformations d'espace analogues
G06F 17/17 - Évaluation de fonctions par des procédés d'approximation, p. ex. par interpolation ou extrapolation, par lissage ou par le procédé des moindres carrés
Techniques are provided for congestion aware placement of the fabric components of an interconnect in an integrated circuit device. A floorplan of the interconnect is projected on a virtual grid that includes placement locations for the fabric components. Locations of the fabric components can be initialized with the placement locations of the virtual grid. Updated locations for the placement of each of the fabric components on the virtual grid can be determined based on minimization of a total wirelength (TWL) cost function of all the nets in the interconnect. Timing slices are inserted in the interconnect after the placement of the fabric components at the updated locations. The floorplan information with the placement information of the fabric components and the timing slices can be used for the physical design of the interconnect to provide a timing clean result.
Systems and methods for a workflow manager to adaptively throttle service calls to service endpoints are disclosed herein, according to some embodiments. A system includes a plurality of service endpoints. The system also includes a workflow definition repository storing workflow definitions, where a workflow definition defines both tasks for a workflow to perform that corresponds to service calls to the service endpoints, and a dependency ordering between the tasks. The system also includes workflow execution nodes implementing workflow engine instances. A workflow engine instance executes a workflow according to a workflow definition. Responsive to health information indicating that a service endpoint is operating below a performance threshold, the workflow manager modifies workflow definitions using that service to incorporate a staging area. Instead of transitioning to a task that corresponds to a service call to the service endpoint, the workflow engine instances executing modified workflow definitions, transition to the staging area.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
G06Q 10/0639 - Analyse des performances des employésAnalyse des performances des opérations d’une entreprise ou d’une organisation
A client computer system implements a cryptocurrency wallet using derived cryptographic keys generated from an implicit certificate. The client computer system uses a root key pair that includes a root public key and a root private key to produce the implicit certificate. The implicit certificate is provided to other entities which generate derived public keys from the implicit certificate. In an embodiment, the client computer system encodes an identifier and additional information into the implicit certificate. In an embodiment, entities may derive one or more public keys from the implicit certificate, and the client computer system may derive corresponding private keys from the implicit certificate and the root key pair. In an embodiment, the client computer system generates a tree or derived key pairs that may be used to delegate portions of the cryptocurrency wallet to other computer systems.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
H04L 9/14 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité utilisant plusieurs clés ou algorithmes
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
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
53.
Identifying item origin by matching image embeddings
Techniques for item origin identification by matching image embeddings are described herein. For example, a computer system can access first image data corresponding to a set of items at a first location of a facility. The first image data can be associated with the first location and can be obtained by a first imaging device. The computer system can generate first set of image embeddings based on the first image data. The first set of image embeddings can represent the set of items. The computer system can determine that a first item of the set of items originated at the first location based at least in part on a matching algorithm comparing the first set of image embeddings with a second image embedding that represents the first item at an identification location of the facility.
Systems and methods for input processing architecture interfaces include receiving first audio data representing a first voice command within a first input processing architecture. A first action domain associated with the first voice command may be determined by the first input processing architecture. A first domain API may be determined, wherein the first domain API is predefined for interfacing with a second input processing architecture. Utilizing an application of multiple applications, a first input processing result associated with the first voice command may be determined. The first input processing result may be provided to the first domain API. The first input processing architecture may be caused to utilize the first input processing result from the first domain API to determine a first action to be performed responsive to the first voice command.
Systems and techniques for automatic audio adjustments to video and/or audio files based on user preferences. The systems and techniques receive data and information to determine content to identify and adjust or remove within the audio data such as a filter list of words or rating data. The systems and techniques further determine the timestamps for the instances within the audio/video file. The audio/video file is de-mixed by a machine learning model into multiple components, for example vocal and non-vocal components. An audio adjustment is made based on the content identified before re-mixing to present the adjusted content to a user.
G10L 25/57 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes spécialement adaptées pour un usage particulier pour comparaison ou différentiation pour le traitement des signaux vidéo
Systems and techniques are described for image signal processor motion detection. In various examples, first image data including pixel values may be generated, where each pixel value is associated with a respective color tag of a color filter array. A first set of the pixel values corresponding to a first block may be determined. A second set of pixel values may be determined based on a respective pixel value of the first set and the respective color tag associated with that respective pixel value. A first intensity value associated with the first block may be determined based on the second set of pixel values. A second intensity value associated with a reference block may be determined. A comparison value representing a difference between the first intensity value and the second intensity value may be determined. A signal indicating detected motion may be sent based on the comparison value.
H04N 19/82 - Détails des opérations de filtrage spécialement adaptées à la compression vidéo, p. ex. pour l'interpolation de pixels mettant en œuvre le filtrage dans une boucle de prédiction
H04N 7/18 - Systèmes de télévision en circuit fermé [CCTV], c.-à-d. systèmes dans lesquels le signal vidéo n'est pas diffusé
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
H04N 5/14 - Circuits de signal d'image pour le domaine des fréquences vidéo
57.
Enhanced electrostatic discharge trap for microphones
An electrostatic discharge trap device for protecting a water-resistant microphone from electrostatic discharge may include a conductive material positioned between a microphone port and a microphone venting stack-up to prevent liquid entry into the microphone, wherein the electrostatic discharge trap device is configured to receive an electric spark from the microphone port and conduct the electric spark away from the microphone venting stack-up to a conductive layer.
Techniques are described for training and use of machine learning models to determine objective video quality scores. Video quality scores predict the quality of video content perceived by viewers. Quality scores have various uses, including the selection of encoding profiles and determination of encoding ladders. A core model and residual model may be used to determine quality scores.
H04N 21/234 - Traitement de flux vidéo élémentaires, p. ex. raccordement de flux vidéo ou transformation de graphes de scènes du flux vidéo codé
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
Techniques for tracing a source for a generative artificial intelligence model output are described. In some examples, a source is traced by generating content using the GenAI model; generating a fingerprint for the content; comparing the fingerprint for the content to one or more fingerprints for content of one or more datasets to determine a match; retrieving metadata associated with the match; and determining and performing one or more actions in response to the retrieved metadata.
A system performs federated learning and retraining of a machine learning model used for processing audio detected by a user device. The system uses both gradient data (which may correspond to false-rejects) and audio data (which may correspond to false-positives) received from devices. The system may also use a teacher model to produce labels for data in an automated fashion, thus allowing retraining to happen in an unsupervised manner.
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
Artifacts, including parameters are data sets, associated with experiment tasks are stored at an experiment management service. A query specifying a particular value of a parameter and a particular data set is received, and an indication of an experiment result associated with the particular data set and the particular parameter value is provided.
G06F 16/14 - Détails de la recherche de fichiers basée sur les métadonnées des fichiers
G06F 16/16 - Opérations sur les fichiers ou les dossiers, p. ex. détails des interfaces utilisateur spécialement adaptées aux systèmes de fichiers
G06F 18/2113 - Sélection du sous-ensemble de caractéristiques le plus significatif en classant ou en filtrant l'ensemble des caractéristiques, p. ex. en utilisant une mesure de la variance ou de la corrélation croisée des caractéristiques
Methods and apparatus for client-directed placement of remotely configured service instances are described. One or more placement target options are selected for a client of a network-accessible service based on criteria such as service characteristics of the placement targets. The selected options, including a particular placement target that includes instance hosts configurable from remote control servers, are indicated programmatically to the client. A determination is made that a service instance is to be configured at the particular placement target on behalf of the client. A remote control server is configured to issue administrative commands to an instance host at the particular placement target to configure the service instance.
H04L 67/025 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP] pour la commande à distance ou la surveillance à distance des applications
H04L 41/0895 - Configuration de réseaux ou d’éléments virtualisés, p. ex. fonction réseau virtualisée ou des éléments du protocole OpenFlow
H04L 41/5041 - Gestion des services réseau, p. ex. en assurant une bonne réalisation du service conformément aux accords caractérisée par la relation temporelle entre la création et le déploiement d’un service
H04L 67/52 - Services réseau spécialement adaptés à l'emplacement du terminal utilisateur
63.
Overlay networks of third-party virtualization frameworks using a cloud virtualized computing service as underlying infrastructure
A connectivity manager of an overlay network which is to be set up using resources of a cloud computing environment as an underlay network is instantiated at a computing resource of the cloud. Using routing information of the overlay network, a route server of the cloud modifies a route table of the cloud. An encapsulation tunnel is created between the connectivity manager and a second computing resource at which a hypervisor of the overlay network runs. Based on the modified route table, a network packet from a source outside the overlay network is routed via the connectivity manager and the tunnel to a virtual machine of the overlay network at the second computing resource.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
H04L 45/021 - Mises à jour des tables d’acheminement avec garantie de cohérence, p. ex. en utilisant des nombres d’époque
H04L 45/76 - Routage dans des topologies définies par logiciel, p. ex. l’acheminement entre des machines virtuelles
H04L 61/2503 - Traduction d'adresses de protocole Internet [IP]
64.
Data access control in data processing applications
Techniques for data access control in data processing applications are described. A portion of user code including a first data access directed to a data source is received from an application. An identity associated with the portion of user code is obtained. A policy including an access control rule that limits access to the data source based at least in part on the identity is obtained. Data access code is generated by evaluating at least a portion of code associated with the first data access. A permitted data access result that complies with the policy is obtained by evaluating the data access code. The permitted data access result is sent to the application.
G06F 21/53 - 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 de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée
65.
Techniques for optimizing storage and speed of audio fingerprinting and matching systems
Techniques are disclosed to optimize resource usage and matching speed of audio track fingerprinting and matching systems without causing excessive impacts on match accuracy. Fingerprints of corpus of audio tracks are recorded via a fingerprint table for use to match query tracks with known tracks in the corpus. However, very large buckets in the fingerprint table create strain on system resources and typically add little to no discriminative power to improve track matching accuracy. Thus, in embodiments, the disclosed system tracks the entry count of individual buckets, and drops bucket data of a bucket when the bucket reaches a count threshold. In embodiments, the disclosed system performs another technique during the matching process to exclude the highest-count fingerprint buckets from the matching process. These techniques may be adjusted according to user configuration or empirical data to maintain a high match accuracy level despite using fewer fingerprints.
G10L 19/018 - Mise en place d’un filigrane audio, c.-à-d. insertion de données inaudibles dans le signal audio
G10L 25/54 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes spécialement adaptées pour un usage particulier pour comparaison ou différentiation pour la recherche
66.
Immunogenic response prediction based on major histocompatibility complex (MHC) data
Immunogenic response prediction techniques are described. In an example, a system receives first training data that identifies a peptide, a first set of multiple major histocompatibility complex (MHC) molecules, and an immunogenic response associated with the peptide and the first set. The system updates a parameter of a first model based at least in part on the first training data. The first model is configured to determine a probability of causing the immunogenic response by a pair formed by the peptide and a MHC molecule from the first set. The system also receives second data that identifies a second set of MHC molecules, and generates, by using the first model and a second model, an immunologic response prediction of pairing the peptide with a MHC molecule from the second set. The second model is configured to generate at least one of peptide-MHC binding predictions or peptide-MHC cell surface presentation predictions.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
67.
Systems and methods for automated website security testing
Systems and methods are provided for automated website security testing. The systems and methods reduce or eliminate the need for a user to manually click through a web application to perform application security testing by embedding one or more API calls to the application security testing service within an already-existing automated user interface test. When a web page is reached during the user interface that that is desired to be tested using the application security test, a cookie associated with the web page is obtained and provided to the API associated with the application security test. The application security test then returns a result and the user interface test continues. Any number of additional API calls for to the application security test service may be performed for any other number of web pages as the user interface test progresses through the web pages as well.
Technologies of contactless and real-time sleep tracking are described. One method of a sleep-monitoring device includes receiving radar data from a radar unit, the radar data representing a user's breathing. The method determines, using the radar data, sleep-stage data, presence data, and user identification data associated with the user. The method determines, using the i) sleep-stage data, ii) the presence data, and iii) the user identification data, a first event corresponding to sleep associated with the user and a second event corresponding to the sleep associated with the user, the second event occurring after the first event. The method modifies, using the presence data, the user identification data, the first event, and the second event, the sleep-stage data to obtain modified sleep-stage data. The method generates, using the modified sleep-stage data, a hypnogram of the sleep associated with the user.
A61B 5/00 - Mesure servant à établir un diagnostic Identification des individus
A61B 5/05 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiquesMesure utilisant des micro-ondes ou des ondes radio
A61B 5/08 - Dispositifs de mesure pour examiner les organes respiratoires
Some embodiments provide a method for training a machine-trained (MT) network. The method receives a network comprising a plurality of parameters. The method trains the network by iteratively (i) propagating inputs through the network to generate outputs and adjusting the parameters based on differences between the generated outputs and expected outputs to minimize a loss function with respect to the parameters, (ii) probabilistically projecting the parameters to minimize the loss function with respect to a set of constraints on the weight values, the probabilistic projection treating the parameters as probability distributions, and updating a set of variables of the loss function based on the probability distributions.
Described implementations determine or monitor one or more parameters of an electrical circuit at a location to determine device usage at the location and utilize that information to determine when consumable inventory at the location is depleted and should be reordered. For example, when a device at the location is turned on, the device affects voltage that is introduced into the voltage signal at the location and detectable by, for example, a plug-in sensor. Different devices generate different patterns or signatures of voltage as they operate, thereby making the signatures unique, or almost unique, to different device types and/or different devices. Utilizing this information for devices that utilize consumable inventory, such as coffee pods, laundry detergent, dishwashing detergent, frozen dinners, popcorn, etc., it can be determined when the consumable inventory is depleted and should be reordered.
Approaches presented herein relate to human authentication in a computerized environment. In particular, challenge-response authentication can be performed where a requestor must submit a correct and valid response. An automated attack on such an environment may use a proxy network to cause a large number of malicious requests to be received to the environment, over a period of time, that appear to come from different sources. To make such an attack less appealing, challenge-response authentication can require an amount of additional data to be transmitted with each request, where that amount is small enough to not have a significant impact on a single request from a legitimate user, but large enough that the amount of data to be transmitted when aggregated across a large number of malicious requests will be significant, resulting in a high cost to the attacker if the proxy network provider charges based on data transmission.
A camera system is automatically focused based on pixel disparity values calculated by the camera at various times. A lens of a camera is positioned at an initial distance from an imaging sensor of the camera based on an initial digital-to-analog conversion value. Subsequently, pixel disparity values are calculated for each of a plurality of regions of a field of view of the camera. An optimal distance between the lens and the image sensor is calculated based on the pixel disparity values and a fitting constant for the camera, as well as the initial digital-to-analog conversion value, and the lens is repositioned to a distance corresponding to the median. The process may be performed following triggering events, or on a regular basis, and repeated over time.
Systems and methods are provided to perform multiply-accumulate operations of reduced precision numbers in a systolic array. Each row of the systolic array can receive reduced inputs from a respective reducer. The reducer can receive a particular input and generate multiple reduced inputs from the input. The reduced inputs can include reduced input data elements and/or a reduced weights. The systolic array may lack support for inputs with a first bit-length and the reducers may reduce the bit-length of a given input from the first bit-length to a second shorter bit-length and provide multiple reduced inputs with second shorter bit-length to the array. The systolic array may perform multiply-accumulate operations on each unique combination of the multiple reduced input data elements and the reduced weights to generate multiple partial outputs. The systolic array may sum the partial outputs to generate the output.
G06F 7/544 - Méthodes ou dispositions pour effectuer des calculs en utilisant exclusivement une représentation numérique codée, p. ex. en utilisant une représentation binaire, ternaire, décimale utilisant des dispositifs n'établissant pas de contact, p. ex. tube, dispositif à l'état solideMéthodes ou dispositions pour effectuer des calculs en utilisant exclusivement une représentation numérique codée, p. ex. en utilisant une représentation binaire, ternaire, décimale utilisant des dispositifs non spécifiés pour l'évaluation de fonctions par calcul
G06F 7/499 - Maniement de valeur ou d'exception, p. ex. arrondi ou dépassement
G06F 15/80 - Architectures de calculateurs universels à programmes enregistrés comprenant un ensemble d'unités de traitement à commande commune, p. ex. plusieurs processeurs de données à instruction unique
74.
TECHNIQUES FOR ACCESSING LOCAL NETWORKS VIA A VIRTUALIZED GATEWAY
Disclosed are various embodiments for receiving, via a network, a request from a client to establish a network tunnel over the network. Various embodiments can create a virtual network comprising a virtual network gateway in response to receiving a service call. Various embodiments can further allocate an available computing resource to the virtual network gateway to augment a first computing resource. Allocating the available computing resource can be performed in response to a usage of the first computing resource assigned to the virtual network gateway.
H04L 41/04 - Architectures ou dispositions de gestion de réseau
H04L 41/0896 - Gestion de la bande passante ou de la capacité des réseaux, c.-à-d. augmentation ou diminution automatique des capacités
H04L 41/0897 - Capacité à monter en charge au moyen de ressources horizontales ou verticales, ou au moyen d’entités de migration, p. ex. au moyen de ressources ou d’entités virtuelles
H04L 41/5054 - Déploiement automatique des services déclenchés par le gestionnaire de service, p. ex. la mise en œuvre du service par configuration automatique des composants réseau
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
H04L 67/08 - Protocoles spécialement adaptés à l'émulation du terminal, p. ex. Telnet
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/1008 - Sélection du serveur pour la répartition de charge basée sur les paramètres des serveurs, p. ex. la mémoire disponible ou la charge de travail
H04L 67/141 - Configuration des sessions d'application
H04L 69/24 - Négociation des capacités de communication
H04L 69/329 - Protocoles de communication intra-couche entre entités paires ou définitions d'unité de données de protocole [PDU] dans la couche application [couche OSI 7]
A quantum computing service provides a quantum algorithm development kit that enables a customer to define a quantum task, a quantum algorithm, or a quantum circuit using an intermediate representation. The quantum computing service is then configured to automatically translate the quantum task, quantum algorithm, or quantum circuit into a specific representation specific to a particular quantum computing technology selected by the customer to be used to execute the customer's quantum task, quantum algorithm, or quantum circuit.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
G06N 10/80 - Programmation quantique, p. ex. interfaces, langages ou boîtes à outils de développement logiciel pour la création ou la manipulation de programmes capables de fonctionner sur des ordinateurs quantiquesPlate-formes pour la simulation ou l’accès aux ordinateurs quantiques, p. ex. informatique quantique en nuage
Systems and methods are disclosed for containers for use in collaborative work environments. In one embodiment, an example container may include a first container wall configured to rotate toward a center of the container, a second container wall coupled to the first container wall and configured to rotate toward the center of the container, the second container wall having a first rotatable flap configured to rotate outwards with respect to the second container wall, a third container wall coupled to the first container wall and configured to rotate toward the center of the container, the third container wall having a second rotatable flap configured to rotate outwards with respect to the third container wall, a fourth container wall coupled to the second container wall and the third container wall, the fourth container wall configured to rotate toward the center of the container, and a base.
B62B 3/02 - Voitures à bras ayant plus d'un essieu portant les roues servant au déplacementDispositifs de direction à cet effetAppareillage à cet effet comportant des parties réglables, rabattables, attachables, détachables ou transformables
B07C 3/00 - Tri du courrier ou des documents selon la destination
B62B 5/06 - Appareillage pour la propulsion à main, p. ex. guidons
This disclosure describes, in part, systems and techniques for determining compensation models to adjust load cell data and ensure accuracy of the load cells on a mobile apparatus through changing environments and conditions. This disclosure relates, specifically, to generating a compensation model by gathering sensor data for known weights of items over a range of weights, locations, temperatures, and humidity values and building a compensation model to infer compensation error to apply to the estimated weight data from the load cells. The compensation model can be used by a fleet of carts to infer weights of items in a manner accurate enough for sale-by-weight of items.
G01G 19/415 - Appareils ou méthodes de pesée adaptés à des fins particulières non prévues dans les groupes avec dispositions pour indiquer, enregistrer ou calculer un prix ou d'autres quantités dépendant du poids utilisant des moyens de calcul électromécaniques ou électroniques utilisant uniquement des moyens de calcul électroniques combinés à des moyens d'enregistrement
G06Q 30/0283 - Estimation ou détermination de prix
78.
Graphical user interface for generative AI software development assistant
Techniques for displaying a graphical user interface of a software development system are described. An initial description of an initial structure of a software system is obtained, the initial description including an identification of interconnections amongst provider network resources that form the initial structure. A modified description of a modified structure of the software system is obtained, the modified structure based on at least a change to the initial structure of the software system described in the initial description. A difference between the initial description and the modified description is determined. An electronic device is caused to display a graphical user interface including a visual depiction of the initial structure of the software system and an indication of the difference, the visual depiction based at least in part on the initial description.
A watchdog timer may be implemented to detect whether a software-based activity monitor is alive. A software-based activity monitor may manage throttling performed by a hardware-based activity monitor. The software-based activity monitor may reset the watchdog timer in the hardware-based activity monitor within a period of time to indicate that the software-based activity monitor is alive. If the watchdog timer is not reset within a period of time, the hardware-based activity monitor begins throttling using watchdog throttling criteria.
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 15/80 - Architectures de calculateurs universels à programmes enregistrés comprenant un ensemble d'unités de traitement à commande commune, p. ex. plusieurs processeurs de données à instruction unique
Techniques are described herein for using an artificial intelligence (AI) model to support tasks for different program codes. For example, a computer system can determine a request of an application that is executing on a device. The application can include program codes that each provide content functions and present content at a user interface for the application. The request may be associated with contextual data and user data and may indicate content entities for a first program code. The computer system can input the content entities, the contextual data, and the user data into an AI model that is trained on historical data associated with the content functions. The AI model can output a relevance score or an embedding vector for the content entities that can be used in performing the first content function and presenting the content entities on the user interface.
An acoustic echo cancellation (AEC) system that dynamically controls an adaptation speed of an adaptive filter, enabling the adaptive filter to converge quickly while protecting near-end speech. For example, a device may control the adaptation speed of the adaptive filter to adapt quickly when near-end speech is not present and adapt slowly when near-end speech is present. The device controls the adaptation speed by dynamically determining step-size values and/or performing error normalization to limit the rate of adaptation. In some examples, the device determines the variable step-size parameter based on a relative strength of a microphone signal and a reference signal over time. For example, the device can compare current energy levels of the microphone signal and the reference signal to a range of energy levels to determine a microphone step-size value, a reference step-size value, and an AEC step-size value.
G10K 11/178 - Procédés ou dispositifs de protection contre le bruit ou les autres ondes acoustiques ou pour amortir ceux-ci, en général utilisant des effets d'interférenceMasquage du son par régénération électro-acoustique en opposition de phase des ondes acoustiques originales
H04M 9/08 - Systèmes téléphoniques à haut-parleur à double sens comportant des moyens pour conditionner le signal, p. ex. pour supprimer les échos dans l'une ou les deux directions du trafic
A system can operate a speech-controlled device to perform user engagement detection (UED) processing to detect when speech represented in audio data is directed to the device. For example, the device may extract audio features from the audio data and process these audio features using a classifier to estimate an orientation of the user's head, which may be used as a proxy for user engagement. Thus, if the head orientation is within an engagement zone (which varies based on distance to the user), the device may determine that the user is engaged with the device and perform language processing on input speech. In contrast, if the head orientation is outside of the engagement zone, the device may determine that the user is not engaged and ignore the input speech. To enable additional functionality, the classifier may optionally output a coarse estimate of the head orientation along with the UED determination.
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 25/21 - 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 sur la puissance
Training a machine learning model for application to an audio enhancement system for a target speaker may be performed. When at least one clean audio speech sample of a target speaker is captured, the machine learning model may then be trained using noisy audio speech samples in which the voice of the target speaker is present in addition to the voices of other speakers and/or background noise. Once the machine learning model is sufficiently trained, it may be deployed for use in audio enhancement and voice processing for an audio transmission service.
G10L 17/04 - Entraînement, enrôlement ou construction de modèle
G10L 17/02 - Opérations de prétraitement, p. ex. sélection de segmentReprésentation ou modélisation de motifs, p. ex. fondée sur l’analyse linéaire discriminante [LDA] ou les composantes principalesSélection ou extraction des caractéristiques
G10L 17/06 - Techniques de prise de décisionStratégies d’alignement de motifs
A device includes a housing, a first cover coupled to the housing, a second cover coupled to the housing, and a microphone assembly. The first cover includes a first channel. The microphone assembly includes a printed circuit board (PCB) having a microphone and a second channel, and a seal. The seal has a third channel configured to align with the first channel and the second channel, and a cavity. The seal is configured to transition between an unfolded state in which the PCB is insertable into the cavity, and a folded state in which the PCB is at least partially enclosed within the cavity and the microphone is enclosed within the cavity.
Context-based control inputs for a device are described herein. In an example, a device presents a first user interface (UI). The device determines, while the first UI is presented, a first user interaction corresponding to a first instance of a user input with the device. The device determines a first context associated with the first user interaction and a first control input based on the first user interaction and the first context. The device causes execution of a first action based on the first control input. The device determines a second user interaction with the device that corresponds to a second instance of the user input. The device determines a second context associated with the second user interaction and determines a second control input based on the second user interaction and the second context. The device causes execution of a second action based on the second control input.
A computing system assembly can include a drawer defining an interior volume sized for holding a computing appliance. The drawer can be slidable between a deployed state and a stowed state relative to a rack-mountable chassis slidably receivable in a rack. A drawer latch coupled with the drawer's exterior can be actuatable to release the drawer from being retained in the chassis and to release the drawer for movement from the stowed state toward the deployed state. An appliance latch also coupled with the drawer's exterior can be actuatable in response to movement of the drawer from the stowed state toward the deployed state to move from a secure state in which the appliance latch at least partially blocks access out of the interior volume of the drawer and to an accessible state in which the appliance latch permits access out of the interior volume of the drawer.
A docking station includes a housing for accommodating an aerial vehicle, a charging contact for transferring electrical power to the aerial vehicle within the housing, and a sensor trigger for initiating or terminating the charging of the aerial vehicle. The sensor trigger includes an insertable element having an upper platform biased into contact with a surface of the housing and a blade-like extension that descends below the surface, as well as a sensor, such as a photointerrupter module, for determining positions of the blade-like extension. When an aerial vehicle is docked within the charging station, the aerial vehicle depresses the insertable element into the housing and causes a change in state of the sensor trigger, thereby energizing the charging contact, and transferring electrical power to the aerial vehicle. When the aerial vehicle departs the docking station, the state of the sensor trigger is restored, and the charging contact is deenergized.
B64U 80/25 - Transport ou stockage spécialement adaptés aux véhicules aériens sans pilote avec des dispositions pour assurer le service du véhicule aérien sans pilote pour la recharge de batteriesTransport ou stockage spécialement adaptés aux véhicules aériens sans pilote avec des dispositions pour assurer le service du véhicule aérien sans pilote pour le ravitaillement en combustible
B64U 70/97 - Moyens de guidage du véhicule aérien sans pilote vers un emplacement spécifique sur la plate-forme, p. ex. structures de plate-forme empêchant un atterrissage hors-piste
B64U 10/14 - Plates-formes volantes comportant quatre axes distincts de rotors, p. ex. quadcoptères
88.
Systems and methods for payload shuttles for efficiently loading and unloading containers
Systems, methods, and computer-readable media are disclosed for multi-level storage systems to facilitate movement of shuttles across a multi-level storage structure for retrieving, loading, unloading, and moving packages. The multi-level storage system may include the multi-level storage structure for storing packages, which may be placed into containers and positioned on a container tray. Shuttles may navigate the multi-level storage system to load and unload containers. Each shuttle may hold one or more container and may include one or more actuator systems to load and unload the containers. The actuator systems may include a motor connected to a tether fixed to one or more protrusions which may enter a channel under a container tray to move the container tray onto the shuttle or may unload the container off the shuttle.
B65G 1/06 - Dispositifs d'emmagasinage mécaniques avec des moyens pour que les objets se présentent à l'enlèvement dans des positions ou à des niveaux prédéterminés
89.
Concentric suction cup tools with integrated air chambers
Systems and methods are disclosed for concentric suction cup tools with integrated air chambers. In one embodiment, an example picking assembly may include a vacuum manifold having a first integrated air pressure path and a second integrated air pressure path, and a first piston subassembly that includes a first air pipe, a first vacuum pipe, a first bushing disposed between the first air pipe and the first vacuum pipe, and a first suction cup, where the first piston subassembly is configured to independently actuate from a retracted position to an extended position. The picking assembly may include a second piston subassembly having a second air pipe, a second vacuum pipe, a second bushing disposed between the second air pipe and the second vacuum pipe, and a second suction cup, where the second piston subassembly is configured to independently actuate from the retracted position to the extended position.
Waveguide combiners with multiple image planes are described herein. In an example, an apparatus includes a first optical element configured to receive light, a substrate having an input surface and an output surface and configured to propagate the light received by the first optical element along a propagation path within the substrate, and a second optical element configured to output the light propagated along the propagation path. The input surface of the substrate is coupled to the first optical element. The second optical element includes a first diffraction grating coupled to the output surface and characterized by a first focal distance and a second diffraction grating coupled to the first diffraction grating in a stacked arrangement and characterized by a second focal distance.
G02F 1/295 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p. ex. commutation, ouverture de porte ou modulationOptique non linéaire pour la commande de la position ou de la direction des rayons lumineux, c.-à-d. déflexion dans une structure de guide d'ondes optique
Techniques for data flow analysis of cloud-based software applications are described. A first portion of source code of a software application is determined to obtain data from a data source identified by a first resource identifier of a cloud provider network, the determination based on a mapping of a first statement in the first portion of the source code to an application programming interface (API) call. A trace of a data flow from the first portion of the source code to a second portion of the source code is obtained. A data sink identified by a second resource identifier of the cloud provider network is determined based on a mapping of a second statement in the second portion of the source code to another API call. A result that includes an identification of a data flow from the data source identified by the first resource identifier to the data sink identified by the second resource identifier is generated.
A technique for arranging matrix multiplications for concurrent execution in an integrated circuit device may include obtaining a representation of a data dependency graph of a neural network model. The data dependency graph may include having an accumulation group (AG) pack of accumulation groups (AGs), in which each of the AGs has one or more matrix multipartition instructions. A representation of a memory location base partition constraint graph of the AG pack can be generated, and an AG row group constraint graph can be generated based on the memory location base partition constraint graph. The AGs of the AG pack can then be assigned to tiles in an integrated circuit device based on the AG row group constraint graph.
A system and techniques for configuring a trained model to dedicate a portion of its output data to include signature data that may be used to identify information about the model. The model may be configured so that some portion of its least-significant output bits may represent the signature data. The signature data may be a unique code that corresponds to the particular model. The signature data may also include encoded data that may represent information such as a model version, model author, or the like. A recipient of the model output data may thus use the signature data to determine information about the particular model, even if the model itself is inaccessible.
Systems and methods for test account management are disclosed. Data may be stored for a plurality of test accounts in at least one memory. Each test account is associated with a test account pool. Data indicative of a plurality of rules associated with the plurality of test accounts may be received. At least one rule indicates an expiration date. The expiration date for the plurality of test accounts may be set in the at least one memory based on the at least one rule indicating the expiration date. The plurality of test accounts may be automatically suspending upon determining that the expiration date is expired. The at least one memory may be updated to indicate that the plurality of test accounts are suspended.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
95.
Predicting a future workload for scaling database processing resources for satisfying a performance objective
A future workload may be predicted for a database system to make a scaling determination based on a performance objective. A performance budget for a database system may be determined and used to select different scaling decisions that may reconfigure a current processing cluster of the database system or add a new processing cluster to the database system to provide further access to a database.
This disclosure describes techniques and architecture for enriching dataset metadata of datasets arranged in tabular form comprising rows and columns, wherein each column has a name. The dataset metadata is enriched with business semantics for natural language question answering. The techniques include one or more of generating one or more synonyms for each name; ranking the names with respect to a likelihood that a column includes possible data to be returned to a user in response to a received NLQ from the user; predicting a date granularity for each column; and predicting a semantic type to describe values in the columns.
Techniques are described herein for generating an autocomplete query. An example method includes a system receiving, via graphical user interface (GUI) at a first device, a first prefix. The system can generate, via a first language model, a first autocomplete query associated with an item based at least in part on the first prefix. The system can determine a non-user based input for a reward model. The system can generate a reward for the first language model based at least in part on the non-user based input. The system can cause a change of weights of the first language model based at least in part on the reward. The system can receive, via a second GUI at a second device, the first autocomplete prefix. The system can generate a second autocomplete query based at least in part on the first autocomplete prefix and the change of weights.
A system configured to improve audio processing by performing dereverberation, noise reduction, and residual echo suppression during a communication session. The system may include a deep neural network (DNN) configured to jointly mitigate additive noise, reverberation, and residual echo. The DNN may be a convolutional recurrent network with dense connectivity (CRN-DC) and may be configured to process complex-valued spectrograms corresponding to the isolated audio data and/or estimated echo data generated by during echo cancellation. The DNN may generate a speech mask and/or an ambient noise mask, enabling the device to generate output audio data representing target speech and a variable amount of ambient noise. For example, the device may separately reconstruct the target speech using the speech mask and the background noise using the ambient noise mask, which enables the device to control the amount of ambient noise represented in the output audio data.
G10K 11/175 - Procédés ou dispositifs de protection contre le bruit ou les autres ondes acoustiques ou pour amortir ceux-ci, en général utilisant des effets d'interférenceMasquage du son
Techniques for ASR processing using language model (LM)-generated context are described. A LM is prompted to generate words that are relevant for/may be included in a future user input. The prompt to the LM can include words from user interaction history, dialog history, dialog topic, user preferences, etc. The information included in the prompt may focus on rare or unique words rather than words that the ASR model is already confident in recognizing. The techniques can be plugged into an existing/pretrained ASR model and can be used with any existing/pretrained LM, thus saving resources needed to implement and maintain the components.
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
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
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
A system configured to improve SSL processing and/or target goal detection by fusing SSL data with object information to generate a combined target likelihood estimate that takes into account what the device knows about the surrounding environment. For example, the device may generate object information by performing object detection, floorplan estimation, distance measurements, and/or the like. Using this object information, the device may calculate a likelihood estimate value for each direction around the device, with known objects (e.g., walls) corresponding to low likelihood values. In response to an acoustic event (e.g., wakeword detection), the device may fuse the target likelihood estimates generated using SSL data and/or object information to generate the combined target likelihood estimate. Thus, the combined target likelihood estimate enables the device to accurately associate the acoustic event with a corresponding SSL track (e.g., direct sound) and ignore reflections caused by objects in the environment.
G10L 25/51 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes spécialement adaptées pour un usage particulier pour comparaison ou différentiation
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
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 25/78 - Détection de la présence ou de l’absence de signaux de voix
G10L 25/87 - Détection de points discrets dans un signal de voix
brevets
