Devices, systems, and methods are provided for voice-based presentation of a user's sentiment. A method may include receiving, by a device, voice data of a person at a time; determining, based on the voice data, an energy level of the person at the time; determining, based on the voice data, a sentiment level of the person at the time; selecting a presentation color indicative of the sentiment level; determining, based on the energy level, a first brightness of the first presentation color; and presenting an indication of the presentation color and the time.
Describe herein are techniques for providing cloud-based discovery. For example, a device may be configured to provide device registration and de-registration notifications to a cloud-based discovery service. The cloud-based discovery service may be configured to respond to discovery request by identifying registered devices that meet the criteria of the discovery request. The cloud-based discovery service may also be configured to provide endpoint information associated with registered devices in response to the discovery request, such that a device is able to utilize the endpoint information to connect with one or more of the registered devices.
The present disclosure generally relates to systems and methods for utilization of network mitigation techniques in the form of null address routing to mitigate coordinated DDOS attacks. One or more computing devices can install malware code into a network device after exploiting a vulnerability of the network device. A monitoring and mitigation service can monitor network devices and detect malware code installed on the network-based service. The monitoring and mitigation service can identify the internet protocol (IP) address or any routing information regarding the computing devices that sent the malware code. Based on the identified information, the monitoring and mitigation service can identify and implement the network mitigation information in the form of null routing addresses that will cause network communications associated with the identified computing device to be terminated or otherwise not delivered to the intended network-based resources.
In response to receiving a reservation request at a provider network, metadata indicating that a group of network addresses of a subnet is reserved for operations of a particular category is stored. A first request for an operation, requiring assignment of an address of the reserved group is rejected if the operation does not belong to the particular category, even if the address is not in use. In response to a second request for an operation which does belong to the particular category, an address of the reserved group is assigned.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
H04L 61/5007 - Adresses de protocole Internet [IP]
A device includes a first housing and a second housing pivotably coupled to the first housing. The second housing has a first camera disposed on a first side of the first housing and a second camera disposed on a second side of the first housing. The first camera has a first field of view (FoV) that is adjustable via pivoting the second housing, and the second camera has a second FoV that is adjustable via pivoting the second housing. The second FoV is different than the first FoV. A privacy cover is coupled to the second housing and is configured to transition between a first position in which the first camera is unobstructed and a second position in which the first camera is obstructed.
G08B 13/196 - Déclenchement influencé par la chaleur, la lumière, ou les radiations de longueur d'onde plus courteDéclenchement par introduction de sources de chaleur, de lumière, ou de radiations de longueur d'onde plus courte utilisant des systèmes détecteurs de radiations passifs utilisant des systèmes de balayage et de comparaison d'image utilisant des caméras de télévision
Disclosed are various embodiments for self-service management of network address allocations in a cloud provider network. In one embodiment, a first network address pool is created for a customer of a cloud provider network in response to a first request. A second network address pool is internally reserved for the customer, where the second network address allocation is contiguous to the first network address pool. The first network address pool is expanded to include at least a portion of the second network address pool in response to a second request.
Systems and methods are disclosed for unloading containers of various container types. In one embodiment, an example container unloading system may include a container support platform configured to rotate a container from an upright position to an angled position, a centering guide configured to guide the container onto the container support platform, a hydraulic device configured to actuate the container support platform, and a controller configured to determine presence of the container on the container support platform, and cause the container support platform to rotate the container via actuation of the side-mounted hydraulic device.
Described are systems and methods for in-facility purchase of items from a single seller when those items are offered for sale by multiple sellers. For example, a materials handling facility may include two or more sellers (Seller A and Seller B) that offer items for sale within the facility. A user may pick items from Seller A and items from Seller B and complete an in-facility purchase of those picked items from one of the sellers, such as Seller B, by payment of the purchase price and applicable taxes to that seller. At a subsequent time, for example when the user exits the facility, Seller B may pay Seller A at least a portion of the purchase price for the Seller A items sold by Seller B as part of the in-facility purchase.
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
This disclosure is directed to methods, apparatuses, and systems for providing content streams with highly targeted, interactive content in a personalized manner. A content producer can generate a user-generic content stream associated with one or more user-specific content flags, which can describe how the user-specific content can be presented along with the content stream. A content-provider can purchase or otherwise acquire the rights to insert their user-specific content into another content provider's user-generic content. Both the user-specific and user-generic content can be provided to the user by means of a voice-controlled device associated with a cloud-based profile of the user. A user can interact with the personalized content to receive supplemental information.
H04H 20/18 - Dispositions de synchronisation de la radiodiffusion ou de la distribution par l'intermédiaire de plusieurs systèmes
H04N 21/41 - Structure de clientStructure de périphérique de client
H04N 21/435 - Traitement de données additionnelles, p. ex. décryptage de données additionnelles ou reconstruction de logiciel à partir de modules extraits du flux de transport
H04N 21/436 - Interfaçage d'un réseau de distribution local, p. ex. communication avec un autre STB ou à l'intérieur de la maison
H04N 21/45 - Opérations de gestion réalisées par le client pour faciliter la réception de contenu ou l'interaction avec le contenu, ou pour l'administration des données liées à l'utilisateur final ou au dispositif client lui-même, p. ex. apprentissage des préférences d'utilisateurs pour recommander des films ou résolution de conflits d'ordonnancement
Devices and techniques are generally described for inference reduction in natural language processing using semantic similarity-based caching. In various examples, first automatic speech recognition (ASR) data representing a first natural language input may be determined. A cache may be searched using the first ASR data. A first skill associated with the first ASR data may be determined from the cache. In some examples, first intent data representing a semantic interpretation of the first natural language input data may be determined by using a first natural language process associated with the first skill.
A codec system dynamically selects a codec from multiple available codecs with a highest level of encoding quality at a computing device based at least in part on the available computing resources at a particular computing device. The codec system can continuously monitor encoding performance and if encoding with the selected codec uses too many computing resources, then the codec system can switch to a codec that uses fewer computing resources.
H04N 21/2343 - Traitement de flux vidéo élémentaires, p. ex. raccordement de flux vidéo ou transformation de graphes de scènes du flux vidéo codé impliquant des opérations de reformatage de signaux vidéo pour la distribution ou la mise en conformité avec les requêtes des utilisateurs finaux ou les exigences des dispositifs des utilisateurs finaux
H04N 21/234 - Traitement de flux vidéo élémentaires, p. ex. raccordement de flux vidéo ou transformation de graphes de scènes du flux vidéo codé
H04N 21/418 - Carte externe destinée à être utilisée en combinaison avec le dispositif client, p. ex. pour l'accès conditionnel
Embodiments of a content recommendation or selection system are described. The system uses a pipeline of machine learning models to select content for a user. In embodiments, a first user model generates a first score of content categories for the user based on short-term user data. A second user model generates a second score of the categories for the user based on long-term user data. The two scores are combined to select the categories to include on the content user interface. In embodiments, new categories are added to the recommendations based on an exploration-exploitation algorithm. In embodiments, content categories are organized on the user interface in a manner to promote neighborhood diversity. Advantageously, the machine learning pipeline enables independent configurability of various objectives of the content recommendation or selection system and reduces the amount of machine learning resources needed to implement the system.
Various embodiments of transcoding system that includes a pre-filtering system are disclosed. The pre-filtering system includes amorphous sub-filter modules and is configured to automatically configure a sequence of filter modules to be used to filter a given segment of a media object being transcoded based on artifacts resulting from an earlier decoding process. The pre-filtering system does not require prior knowledge of what encoding parameters that were used to encode the media object being transcoded. Also, the filtering system supports a wide variety of encoding formats and can automatically adjust the filtering sequence and/or filtering parameters based on the variability of compression artifacts resulting from the decoding of media objects previously encoded using a plurality of encoding formats and/or encoding parameters.
H04N 19/40 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le transcodage vidéo, c.-à-d. le décodage partiel ou complet d’un flux d’entrée codé suivi par un ré-encodage du flux de sortie décodé
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
H04N 19/117 - Filtres, p. ex. pour le pré-traitement ou le post-traitement
H04N 19/136 - Caractéristiques ou propriétés du signal vidéo entrant
H04N 19/167 - Position dans une image vidéo, p. ex. région d'intérêt [ROI]
H04N 19/172 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c.-à-d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p. ex. un objet la zone étant une image, une trame ou un champ
H04N 19/23 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage d'objets vidéo avec codage des zones présentes sur l’ensemble d’un segment vidéo, p. ex. plans-objets vidéo, image de fond ou mosaïque
A constellation of satellites provides communication services to user terminals (UTs). Downstream data addressed to a UT is received at a point-of-presence (POP) and tokenized before sending to a satellite serving the UT. Tokens are associated with resource blocks (RBs), each RB indicative of a particular combination of downlink frequency and timeslot. Tokens are then allocated to downstream data. This tokenized downstream data is sent to the satellite. Untokenized downstream data may be buffered for later tokenization or discarded. A satellite may use information in the token to schedule transmission on a downlink to the UT. The supply of tokens may be based on shaper input data such as gateway queue depth, estimated latency from the POP to the satellite, estimated time to empty a buffer onboard the satellite, and so forth. The supply of tokens may be adjusted to minimize data loss during handovers from one satellite to another.
Disclosed herein are methods of scoring predicted immunogenicity of neoantigens from biological samples of a subject. Methods can include the steps of preparing biological samples for nucleic acid sequencing; nucleic acid sequencing; evaluating the initial sequencing results by analyzing (e.g., comparing) sequencing parameters of the results; based on an analysis (e.g., a comparison) of sequencing parameters, combining the initial sequencing results to yield union sequencing results or selecting a representative biological sample; and scoring the predicted immunogenicity of neoantigens in the biological samples based on either the union sequencing results or the sequencing results of the representative sample. Methods can further include the step of comparing sequencing parameters of union sequencing results and the initial sequencing results. Methods can further include the steps of generating a neoantigen vaccine that contains or encodes for a neoantigen scored for predicted immunogenicity and administering the neoantigen vaccine to a subject.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
17.
SOFTWARE TESTING SERVICE WITH AUTOMATED FAILURE REPRODUCTION AND ROOT CAUSE ANALYSIS
A cloud-based software testing service orchestrates the testing of pieces of software, such as software to be deployed to a vehicle. Also, the cloud-based software testing service, in response to detecting a failure, automatically instantiates multiple virtual machines configured to emulate a testing environment for testing one or more of the pieces of software, with which the detected failure is associated. These virtual machines allow for rapid execution of multiple instances of re-testing to be performed to determine a reproducibility measure for the failure. Based on the reproducibility measure, additional re-testing may be performed. Expanded testing logs generated during the re-testing are provided to a trained machine learning model that automatically determines, for reproducible failures, a root cause of the failure.
Contents of client-initiated handshake messages of a security protocol are obtained at a handshake processing offloader configured for an application. The offloader uses a first security artifact (which is inaccessible from a front-end request processor of the application) and the contents of the handshake messages to generate a second security artifact. The second security artifact is transmitted to the front-end request processor, which uses it to perform cryptographic operations for client-server interactions of the application.
Systems and methods are described for facilitating network traffic between serverless function executions and isolated cloud resources within virtualized network environments. Virtualized network environments, by default, may be isolated such that external traffic is not permitted to enter the environment. Permissions for traffic that may enter the environment are often set on the basis of network addresses. In the context of serverless functions, such permissions may be difficult to establish because executions of serverless functions can occur on a dynamically selected environment without a fixed network address. The present disclosure provides for creation of user-defined connectors that facilitate routing of network traffic between executions of serverless functions and user virtualized network environments without requiring that routing occur on the bases of network addresses.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
20.
CONVERSATIONAL LANGUAGE MODEL BASED CONTENT RETRIEVAL
Devices and techniques are generally described for LM-based content retrieval. First query data including a first request related to first content may be received. First action data associated with the first query data may be determined. First prompt data including a representation of the first query data and data representing the first action data may be generated. The first prompt data may instructs a first LM to recognize entities in the first query data relevant to the first action data. The first LM may determine a first recognized entity from the first request. The first recognized entity may be associated with the first content. A request to resolve the first recognized entity may be generated. A first resolved entity for the first recognized entity may be determined. The first LM may generate first instructions to perform the first action data using the first resolved entity.
Techniques for using a model to generate a response to a user input, where the response is associated with a personality determined to be relevant to the user input, are described. The system receives a user input and context data associated with the user input. Using the user input data and/or the context data, the system determines a personality (e.g., including a personality type and/or personality characteristics) relevant to the user input. The system generates a prompt instructing a model to generate a response to the user input that corresponds to the personality. The model processes the prompt to generate a response to the user input that corresponds to the personality. In some embodiments, the model generates a request for another component of the system to generate information responsive to the user input. The model may transform the responsive information into the personality-associated response.
A cloud-based software testing service orchestrates the testing of pieces of software, such as software to be deployed to a vehicle. Also, the cloud-based software testing service, in response to detecting a failure, automatically instantiates multiple virtual machines configured to emulate a testing environment for testing one or more of the pieces of software, with which the detected failure is associated. These virtual machines allow for rapid execution of multiple instances of re-testing to be performed to determine a reproducibility measure for the failure. Based on the reproducibility measure, additional re-testing may be performed. Expanded testing logs generated during the re-testing are provided to a trained machine learning model that automatically determines, for reproducible failures, a root cause of the failure.
Devices, systems, and methods for tokenizing search attributes and terms of a search query for an index-based search. A method may include receiving, by a search service of a provider network, a first search query to search a first searchable document set, the first search query including a first search term in a first language; applying a first tokenization rule to identify the first search term in the first search query; determining that the first search term is in the first language; applying a second tokenization rule to tokenize the first search term based on the first search term being in the first language; causing a launch of a search instance by a managed compute service of the provider network, the search instance to execute a search function for a keyword-based text search using the tokenized first search term.
Disclosed herein are methods of treating an individual at risk for incidence or recurrence of cancer in need thereof. Methods can include the steps of identifying an individual at risk for incidence or recurrence of cancer based on a risk stratification parameter; analyzing a biological sample from using a multi-cancer detection (MCD) test to yield an MCD test result; and based on the MCD test result and optionally the risk stratification parameter, administering a neoantigen immunogenic composition to the individual in need thereof. Methods can include the steps of sequencing and analyzing of the biological sample from the individual or a new biological sample from the individual to identify neoantigens to be included in the neoantigen immunogenic composition; and analyzing a second biological sample from the individual at risk for incidence or recurrence of cancer using a second multi-cancer detection (MCD) test to determine efficacy of the neoantigen immunogenic composition.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
25.
METHODS FOR SELECTION AND COMBINATION OF SEQUENCING RESULTS FROM BIOLOGICAL SAMPLES FOR NEOANTIGEN SCORING
Disclosed herein are methods of scoring predicted immunogenicity of neoantigens from biological samples of a subject. Methods can include the steps of preparing biological samples for nucleic acid sequencing; nucleic acid sequencing; evaluating the initial sequencing results by analyzing (e.g., comparing) sequencing parameters of the results; based on an analysis (e.g., a comparison) of sequencing parameters, combining the initial sequencing results to yield union sequencing results or selecting a representative biological sample; and scoring the predicted immunogenicity of neoantigens in the biological samples based on either the union sequencing results or the sequencing results of the representative sample. Methods can further include the step of comparing sequencing parameters of union sequencing results and the initial sequencing results. Methods can further include the steps of generating a neoantigen vaccine that contains or encodes for a neoantigen scored for predicted immunogenicity and administering the neoantigen vaccine to a subject.
C07K 14/47 - Peptides ayant plus de 20 amino-acidesGastrinesSomatostatinesMélanotropinesLeurs dérivés provenant d'animauxPeptides ayant plus de 20 amino-acidesGastrinesSomatostatinesMélanotropinesLeurs dérivés provenant d'humains provenant de vertébrés provenant de mammifères
26.
MANAGING REPLICATION OF COMPUTING NODES FOR PROVIDED COMPUTER NETWORKS
Techniques are described for providing managed computer networks, such as for managed virtual computer networks overlaid on one or more other underlying computer networks. In some situations, the techniques include facilitating replication of a primary computing node that is actively participating in a managed computer network, such as by maintaining one or more other computing nodes in the managed computer network as replicas, and using such replica computing nodes in various manners. For example, a particular managed virtual computer network may span multiple broadcast domains of an underlying computer network, and a particular primary computing node and a corresponding remote replica computing node of the managed virtual computer network may be implemented in distinct broadcast domains of the underlying computer network, with the replica computing node being used to transparently replace the primary computing node in the virtual computer network if the primary computing node becomes unavailable.
H04L 67/1029 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour accéder à un serveur parmi une pluralité de serveurs répliqués en utilisant des données liées à l'état des serveurs par un répartiteur de charge
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
H04L 61/2503 - Traduction d'adresses de protocole Internet [IP]
H04L 61/5007 - Adresses de protocole Internet [IP]
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]
H04L 101/668 - Adresses de sous-réseaux du protocole Internet [IP]
27.
MULTI-TENANT RADIO-BASED APPLICATION PIPELINE PROCESSING SYSTEM
Connectivity between a radio-based application pipeline processing server and a control plane of a provider network is verified. Based on requests received at the control plane, a first isolated request handler, a second isolated request handler and an offloading manager are launched at the server. The offloading manager causes a first network function for which a request is received from the first request handler to be executed at a first network function accelerator of the server, and a second network function for which a request is received from the second request handler to be executed at a second network function accelerator of the server.
A storage object and an associated permissions record is stored at a storage server. The permissions record indicates that some storage consumers are not permitted to perform a type of I/O operation on the storage object. In response to detecting that an event of a deletion triggering type with respect to the records, a modified version of the permissions record is stored at the server, indicating that the storage consumers remain prohibited from performing the I/O operations. In response to receiving a command to perform a particular I/O at the server after the modified version has been stored, the modified version is used to process the command.
A system may provide a voice user interface (VUI) for sending a media comment (e.g., brief clips of audio data representing speech) to a media content creator such as a podcaster, talk show, music app, etc. The system can identify a destination for the media comment based on context (e.g., an identifier corresponding to media content currently or recently output by a user device) and/or via voice dialog with the user. Content creators can invite, receive, and play users' media comments on the show, thereby increasing audience engagement. A media comment may include a request for or dedication of a song, a “shout out” to another listener, a story/opinion, a question, a response to a poll, a contest entry, etc.
Techniques for performing readout and reset of fluxonium qubits are disclosed. When fluxonium hardware components are coupled to a quantum metamaterial through a readout resonator, said components may be dispersively coupled such that a quantum state of the corresponding fluxonium qubit is read out through the quantum metamaterial, and then the state of the fluxonium qubit is subsequently reset in order to proceed with a quantum computation to be performed. Alternatively, when fluxonium hardware components are coupled directly to a quantum metamaterial, a quantum state of a fluxonium qubit is read out using resonance fluorescence, and then may be subsequently reset back to its ground state, also using resonance fluorescence. A width of a passband of the quantum metamaterial, along with frequencies of the control sequences used, may be tuned such that either readout or reset is selectively activated.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
G06N 10/20 - Modèles d’informatique quantique, p. ex. circuits quantiques ou ordinateurs quantiques universels
31.
GENERATING KEYWORDS TO PRODUCE SYNTHETIC DOCUMENTS WHILE MAINTAINING DATA PRIVACY
A service may generate keywords to produce synthetic documents, while maintaining data privacy for the original documents. A client may extract keyword sequences from locally stored documents, embed the keyword sequences into vectors, and generate a DP-KDE distribution based on the vectors. The DP-KDE distribution preserves data privacy for the original documents. The service receives the DP-KDE distribution, obtains a particular vector from the DP-KDE (e.g., based on a calculated score for the DP-KDE using random Gaussian completions), decodes the particular vector into a sequence of synthetic keywords, and uses the sequence of synthetic keywords to prompt an LLM to produce one or more synthetic documents.
G06F 16/383 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
Techniques for using a model to generate a response to a user input, where the response is associated with a personality determined to be relevant to the user input, are described. The system receives a user input and context data associated with the user input. Using the user input data and/or the context data, the system determines a personality (e.g., including a personality type and/or personality characteristics) relevant to the user input. The system generates a prompt instructing a model to generate a response to the user input that corresponds to the personality. The model processes the prompt to generate a response to the user input that corresponds to the personality. In some embodiments, the model generates a request for another component of the system to generate information responsive to the user input. The model may transform the responsive information into the personality-associated response.
Techniques for two-dimensional (2D) image processing to generate a three-dimensional (3D) model and determine a 2D plan are described herein. In an example, a 3D model of a room can be generated by using a video file portion of a video file as a first input to a first machine learning (ML) model. Semantic segmentation of the room can be generated by using the video file portion as a second input to a second ML model. The semantic segmentation may indicate that an object having an object type is shown in a first image frame of the video file portion. A 3D representation of the object in the 3D model can be determined. The 3D model can be corrected by setting a property of the 3D representation to a predefined value. A 2D floor plan of the room can be generated based on the corrected 3D model.
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/24 - Alignement, centrage, détection de l’orientation ou correction de l’image
G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p. ex. de visages similaires sur les réseaux sociaux
H04N 5/74 - Dispositifs de projection pour reproduction d'image, p. ex. eidophor
34.
DYNAMIC TEXT TOKENIZATION FOR INDEX-BASED SEARCHING OF ANNOTATED DATA ASSETS USING KEYWORD-BASED TEXT SEARCHING
Devices, systems, and methods for tokenizing search attributes and terms of a search query for an index-based search. A method may include receiving, by a search service of a provider network, a first search query to search a first searchable document set, the first search query including a first search term in a first language; applying a first tokenization rule to identify the first search term in the first search query; determining that the first search term is in the first language; applying a second tokenization rule to tokenize the first search term based on the first search term being in the first language; causing a launch of a search instance by a managed compute service of the provider network, the search instance to execute a search function for a keyword-based text search using the tokenized first search term.
Verifying large language model responses involves obtaining a query and its corresponding answer from a large language model. This conversational text is then fed into a second large language model, which translates the answer into first-order logic. The verification process uses an automated theorem prover. It checks the validity of this logic translation by determining the unsatisfiability of two scenarios: one where the negation of the logic translation and domain-specific logic formulas are combined, and another where the logic translation itself is combined with these formulas. Based on this analysis, the theorem prover ascertains whether the translated answer is valid, invalid, or neither. The final step is communicating this verification status through an appropriate output medium, such as a graphical user interface, a database, or a report, providing a structured and methodical approach to assessing the accuracy and reliability of language model responses.
Techniques for two-dimensional (2D) image processing to generate a three-dimensional (3D) model and determine a 2D plan are described herein. In an example, a 3D model of a room can be generated by using a video file portion of a video file as a first input to a first machine learning (ML) model. Semantic segmentation of the room can be generated by using the video file portion as a second input to a second ML model. The semantic segmentation may indicate that an object having an object type is shown in a first image frame of the video file portion. A 3D representation of the object in the 3D model can be determined. The 3D model can be corrected by setting a property of the 3D representation to a predefined value. A 2D floor plan of the room can be generated based on the corrected 3D model..
A service may generate keywords to produce synthetic documents, while maintaining data privacy for the original documents. A client may extract keyword sequences from locally stored documents, embed the keyword sequences into vectors, and generate a DP-KDE distribution based on the vectors. The DP-KDE distribution preserves data privacy for the original documents. The service receives the DP-KDE distribution, obtains a particular vector from the DP-KDE (e.g., based on a calculated score for the DP-KDE using random Gaussian completions), decodes the particular vector into a sequence of synthetic keywords, and uses the sequence of synthetic keywords to prompt an LLM to produce one or more synthetic documents.
A constellation of satellites provides communication services to user terminals (UTs). Downstream data addressed to a UT is received at a point-of-presence (POP) and tokenized before sending to a satellite serving the UT. Tokens are associated with resource blocks (RBs), each RB indicative of a particular combination of downlink frequency and timeslot. Tokens are then allocated to downstream data. This tokenized downstream data is sent to the satellite. Untokenized downstream data may be buffered for later tokenization or discarded. A satellite may use information in the token to schedule transmission on a downlink to the UT. The supply of tokens may be based on shaper input data such as gateway queue depth, estimated latency from the POP to the satellite, estimated time to empty a buffer onboard the satellite, and so forth. The supply of tokens may be adjusted to minimize data loss during handovers from one satellite to another.
Verifying large language model responses involves obtaining a query and its corresponding answer from a large language model. This conversational text is then fed into a second large language model, which translates the answer into first-order logic. The verification process uses an automated theorem prover. It checks the validity of this logic translation by determining the unsatisfiability of two scenarios: one where the negation of the logic translation and domain-specific logic formulas are combined, and another where the logic translation itself is combined with these formulas. Based on this analysis, the theorem prover ascertains whether the translated answer is valid, invalid, or neither. The final step is communicating this verification status through an appropriate output medium, such as a graphical user interface, a database, or a report, providing a structured and methodical approach to assessing the accuracy and reliability of language model responses.
Embodiments for a standardized machine data interface protocol are described herein. A request for information about a state of a component of a machine may be received where the request is in an agnostic data format. A particular machine and a particular component of the particular machine may be determined based on the agnostic data format. A data structure of the agnostic data format for the particular machine and the particular component may be determined where the data structure is associated with the state. The state may be requested from the particular machine for the particular component using a format of the data structure. The state of the particular component may be received according to the format of the data structure. The state of the particular component may be converted from the format of the data structure to the agnostic data format of the request.
A clock selection circuit allows seamless switching between different clock signals in a clock distribution network. The clock selection circuit can be an Integrated Circuit (IC). The clock signals can be analyzed by a processor in communication with the IC to ensure the clock signals are validated. Analysis can include comparing time stamps between received pulses of the clock signals to determine if the clock signals are occurring at regular intervals. The processor can then assign a priority order to the clock signals and select one of the clock signals to use. An identifier associated with the selected clock signal can be programmed into the IC. The IC can then redistribute the selected clock signal to multiple other ICs in a hierarchical clock distribution network. Ultimately, the distributed clock signal can be received by server computers to ensure instances being executed have accurate and synchronized timing.
Respective delegation records indicating that a first access controller and a second access controller have been authorized to grant access to a respective set of cells of a table of a storage management service are stored. In response to receiving an access request of a data accessor, permission records indicating that the access controllers have granted permissions to the data accessor to respective subsets of the table's cells are identified. A collection of cells of the table to which the data accessor has been granted access permission is identified using the permission records, and a response to the access request is generated using the collection.
A federated permission management service provides clients with customized access to a data set using customized authorization metadata. The federated permission management service may define and apply permissions that are defined at a data lake that provides access to many different data sets from many different sources, as well as those permissions that may be defined at the source of the data set, which may be provided when performing a data sharing request. By allowing for permissions to be specified at the data lake in addition to permissions specified at a source of a data set, the permission management service can provide a fine-grained access control to specific objects of the data set, such as specific columns, specific rows, or specific cells of a database to be shared, even for those data sets in the data lake having different sources.
Systems and methods are provided for use of use of fuzzy-match-based translation suggestions to augment machine translation of input sentences or other texts. A machine translation system may use a model trained to translate a source language input to a target language output based on pseudo-randomly selected translation suggestions in the target language, while at inference time the machine translation system may use translation selections associated with source language samples that have a high degree of similarity to the source language input to be translated. To efficiently use the translation suggestions, they may be encoded in context with the source language input to be translated, and the machine translation system may use the encoded translation suggestions with to generate a translation in the target language.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
45.
Sample size and duration prediction for online activity
Devices and techniques are generally described for sample size prediction for online activity. In various examples, first data related to a first sample of users interacting with an online service during a first time period may be received. In some cases, first key performance indicator (KPI) data related to the first sample of users' interaction with the online service may be received. A predicted sample size of users that will interact with the online service for a second time period following the first time period may be predicted. A predicted statistical power may be determined using the predicted sample size. In some examples, a minimum amount of time to route traffic to the online service may be determined based at least in part on the predicted statistical power.
Described is a system for counting stacked items using image analysis. In one implementation, an image of an inventory location with stacked items is obtained and processed to determine the number of items stacked at the inventory location. In some instances, the item closest to the camera that obtains the image may be the only item viewable in the image. Using image analysis, such as depth mapping or Histogram of Oriented Gradients (HOG) algorithms, the distance of the item from the camera and the shelf of the inventory location can be determined. Using this information, and known dimension information for the item, a count of the number of items stacked at an inventory location may be determined.
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
Techniques are described for detecting a periphery of a surface based on a point set representing the surface. The surface may correspond to a display medium upon which content is projected. A shape model may be matched and aligned to a contour of the point set. A periphery or edge of the surface and corresponding display medium may be determined based on the aligned shape model.
G03B 21/00 - Projecteurs ou visionneuses du type par projectionLeurs accessoires
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
H04N 9/31 - Dispositifs de projection pour la présentation d'images en couleurs
48.
Liveness detection based on gesture validation, facial expression analysis, and concurrency validation
Techniques for liveness detection based on gesture validation, facial expression analysis, and concurrency validation. The techniques include selecting a color light pattern challenge and sending the color light pattern challenge to a personal computing device for display on a display screen of the personal computing device. A set of target images (video) is received by a liveness detection service in a provider network from the personal computing device as a response to the challenge. The liveness detection service analyzes the set of target images for macro-facial expression and micro-facial expressions. A liveness determination is made by the liveness detection service as to whether the user of the personal computing device is a live genuine user or an impersonated user based on the analysis of the macro and micro-facial expressions detected in the set of target images.
Described are implementations that facilitate group determination and association at entry into a facility so that activities of group members of the group are associated with the group and/or applied to a single account designated for the group. For example, if four individuals enter the facility together, the disclosed implementations determine whether the four individuals are to be associated as a group. If associated as a group, an account, such as an account of one of the individuals, is also determined and associated with the group. Activities, such as an item pick, performed by one of those individuals is associated with the group and if there is a fee or charge associated with the activity it is applied to the associated account.
G07C 9/29 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer le laissez-passer comportant des éléments électroniques actifs, p. ex. des cartes à puce
50.
Systems and methods for automated communication summarization
Systems and methods develop and apply one or more extractive summarization models for locating contact center conversation details in a transcript, extracting pertinent verbiage, and, in a transformation of the communication details, automatically generating summaries at one or more levels of abstraction, the summaries in full sentences, in a manner that a contact center agent understands. The models are trained using machine learning algorithms.
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
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
51.
Detecting corrupted speech in voice-based computer interfaces
Approaches are generally described for corrupted speech detection in voice-based computer interfaces. First input data including first audio data representing a user utterance may be received. First data representing the first audio data may be generated using a first encoder. First text data representing a transcription of the user utterance may be generated. Second data representing the first text data may be generated using a second encoder different from the first encoder. Third data may be generated by combining the first data and the second data. The third data may be sent to a classifier network trained to predict a relevant corruption state for speech processing inputs. The classifier network may determine that the first input data corresponds to a first corruption state.
Techniques implemented by a network-access analysis system to analyze network access controls for networks, identify traffic flows that are unobserved and unrequired, and determine proposed changes to the network access controls that restrict access from unobserved traffic flows. The system may analyze the network access controls, and determine whether unrequired traffic flows are allowed to be communicated in the network. For instance, the system may analyze network flow logs and identify observed traffic flows that are required by applications in the network, and also identify unobserved traffic flows that are permitted access to, but are not observed in, the network. The system may propose changes to the network access controls to restrict network access by these unobserved traffic flows. A network administrator can receive recommendations from the system regarding the proposed changes, and determine whether they would like to implement the proposed changes to their network access controls.
Conflicts may be detected between a generated access management policy and invoked identity and access management policies. An access management policy to be updated to provide expected results for example requests may be received. Another access management policy that would be invoked to evaluate the example access requests may be identified. A conflict between the expected results for the updates and the invoked access management policy may be determined. An indication of the conflict between the expected results of the example requests may be provided.
A camera system includes a housing and camera modules (e.g., digital cameras) that are aligned with fields of view that extend below the housing. The camera modules are provided about a perimeter of the housing and mounted to a bench within the housing. Two camera modules have axes of orientation extending below and away from a centroid of the camera system. Two camera modules have axes of orientation extending below and toward the centroid of the camera system. The housing includes inlets and outlets that enable air to flow past the camera modules and other components within the housing. Images captured by the camera modules of the camera system may be utilized for any purpose.
H04N 23/90 - Agencement de caméras ou de modules de caméras, p. ex. de plusieurs caméras dans des studios de télévision ou des stades de sport
G08B 13/196 - Déclenchement influencé par la chaleur, la lumière, ou les radiations de longueur d'onde plus courteDéclenchement par introduction de sources de chaleur, de lumière, ou de radiations de longueur d'onde plus courte utilisant des systèmes détecteurs de radiations passifs utilisant des systèmes de balayage et de comparaison d'image utilisant des caméras de télévision
H04N 23/52 - Éléments optimisant le fonctionnement du capteur d'images, p. ex. pour la protection contre les interférences électromagnétiques [EMI] ou la commande de la température par des éléments de transfert de chaleur ou de refroidissement
H05K 7/20 - Modifications en vue de faciliter la réfrigération, l'aération ou le chauffage
55.
Detecting and controlling different types of Zigbee devices on different networks and channels
Technologies directed to detecting and controlling different types of ZigBee devices on different ZigBee networks reliably and efficiently. In one method of operating a first device, the method includes detecting first and second Zigbee networks. The method sends a first request to rejoin the first Zigbee network, the first request being encoded with the first network key. While rejoined as part of the first Zigbee network, the method detects a first set of devices part of the first Zigbee network. The method repeats this for a second set of devices part of the second Zigbee network. The method determines, using the device data, a subset of controllable devices located in proximity, and sends a message with the command to each in response to receiving a command. Each message is encoded with a respective network key and a respective link key specified in the device data.
H04W 4/80 - Services utilisant la communication de courte portée, p. ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
H04W 4/06 - Répartition sélective de services de diffusion, p. ex. service de diffusion/multidiffusion multimédiaServices à des groupes d’utilisateursServices d’appel sélectif unidirectionnel
Rotatable joints may include one or more braking assemblies. The one or more braking assemblies may control a degree of movement of the rotatable joint to provide a range of damping. In some instances, the braking assemblies may include brake band(s) that tighten and loosen around a hub, or other rotatable member of the rotatable joint. The amount of braking, or tautness of the brake band(s), may be variably controlled to arrest the hub by different amounts. In some instances, the tightening of the brake band(s) around the hub may be controlled using linear actuator(s) and/or magnetic element(s). Implementing braking assemblies having controlled actuation may improve control of rotatable joints without adding cost, complexity, weight, or bulk.
B25J 19/00 - Accessoires adaptés aux manipulateurs, p. ex. pour contrôler, pour observerDispositifs de sécurité combinés avec les manipulateurs ou spécialement conçus pour être utilisés en association avec ces manipulateurs
F16D 49/10 - Freins avec un organe de freinage coopérant avec la périphérie d'un tambour, d'une jante de roue ou d'une pièce analogue ayant la forme d'une bande d'encerclement s'étendant sur environ 360° actionnés mécaniquement
F16D 65/06 - Bandes, sabots ou patinsPivots ou leurs organes de support pour freins à action extérieure
F16D 65/28 - Mécanismes d'actionnement pour freinsMoyens pour amorcer l'opération de freinage à une position prédéterminée disposés en dehors du frein
Dynamic camera image presentation in a vehicle is described herein. In an example, a computer system presents, on a display of a vehicle, first image data generated by a camera of the vehicle. The first image data is based at least in part on a first presentation property. The computer system determines a trigger to change the first presentation property and a second presentation property associated with a type of the trigger. The computer system presents, on the display, second image data generated by the camera. The second image data is presented based at least in part on the second presentation property.
B60R 1/26 - Dispositions de visualisation en temps réel pour les conducteurs ou les passagers utilisant des systèmes de capture d'images optiques, p. ex. des caméras ou des systèmes vidéo spécialement adaptés pour être utilisés dans ou sur des véhicules pour visualiser une zone extérieure au véhicule, p. ex. l’extérieur du véhicule avec un champ de vision prédéterminé vers l’arrière du véhicule
B60K 35/00 - Instruments spécialement adaptés aux véhiculesAgencement d’instruments dans ou sur des véhicules
B60K 35/28 - Dispositions de sortie, c.-à-d. du véhicule à l'utilisateur, associées aux fonctions du véhicule ou spécialement adaptées à celles-ci caractérisées par le type d’informations de sortie, p. ex. divertissement vidéo ou informations sur la dynamique du véhiculeDispositions de sortie, c.-à-d. du véhicule à l'utilisateur, associées aux fonctions du véhicule ou spécialement adaptées à celles-ci caractérisées par la finalité des informations de sortie, p. ex. pour attirer l'attention du conducteur
B60K 35/29 - Instruments caractérisés par la manière dont les informations sont traitées, p. ex. présentant des informations sur plusieurs dispositifs d’affichage ou hiérarchisant les informations en fonction des conditions de conduite
H04N 23/69 - Commande de moyens permettant de modifier l'angle du champ de vision, p. ex. des objectifs de zoom optique ou un zoom électronique
Described are systems and methods for active weathervaning of a hybrid flight aerial vehicle, such as an unmanned aerial vehicle (UAV). Active weathervaning of the hybrid flight aerial vehicle during can be provided during vertical takeoff and landing (VTOL)/hover flight without the assistance of any low-speed wind sensors and during transitions between VTOL/hover flight and fixed-wing, wing-borne, horizontal flight. Additionally, active weathervaning can be provided during propulsion mechanism failure conditions where the aerial vehicle may be experiencing failure conditions associated with one or more propulsion mechanisms.
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64C 29/02 - Aéronefs capables d'atterrir ou de décoller à la verticale, p. ex. aéronefs à décollage et atterrissage verticaux [ADAV, en anglais VTOL] dont l'axe matérialisant la direction du vol est vertical lorsque l'aéronef est au sol
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
A device includes a camera and a privacy cover configured to rotate between a first position and a second position. In the first position, the camera is deactivated and the privacy cover obstructs the camera. In the second position, the camera is activated and the camera is unobstructed by the privacy cover. A first indication is visible through a portion of the privacy cover in the first position, the first indication indicating that the camera is deactivated. A second indication is visible through the portion of the privacy cover in the second position, the second indication indicating that the camera is activated.
A particular hyper-parameter combination (HPC) that was recommended for a first task is included in a collection of candidate HPCs evaluated for a second task. Hyper-parameter analysis iterations are conducted for the second task using the collection. In one of the iterations, the second task is executed using a first iteration-specific set of HPCs, including the particular HPC and one or more other members of the collection. One or more of the HPCs of the first iteration-specific set of HPCs are pruned to generate a second iteration-specific set of HPCs for a subsequent iteration. HPCs are selected for pruning based on a comparison of their results with the results obtained from the particular HPC that was recommended for the first task. A recommended HPC for the second task is identified based on results of the analysis iterations.
Systems and methods are described herein for routing data by transferring a physical storage device for at least part of a route between source and destination locations. In one example, a computing resource service provider, may receive a request to transfer data from a customer center to a data center. The service provider may determine a route, which includes one or more of a physical path or a network path, for the data loaded onto a physical storage device to reach the data center from the customer center. Determining the route may include associating respective cost values to individual physical and network paths between physical stations between the customer and end data centers, and selecting one or more of the paths to reduce a total cost of the route. Route information may then be associated with the physical storage device based on the route.
G06Q 10/08 - Logistique, p. ex. entreposage, chargement ou distributionGestion d’inventaires ou de stocks
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p. ex. lecture de la lumière blanche réfléchie
G06Q 10/047 - Optimisation des itinéraires ou des chemins, p. ex. problème du voyageur de commerce
G06Q 10/0835 - Relations entre l’expéditeur ou le fournisseur et les transporteurs
G06Q 10/087 - Gestion d’inventaires ou de stocks, p. ex. exécution des commandes, approvisionnement ou régularisation par rapport aux commandes
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/0488 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels
G09F 3/20 - Armatures, cadres ou entourages pour étiquettes pour des étiquettes réglables, mobiles ou interchangeables
This disclosure describes, in part, systems and techniques for secure storage and retrieval of items by users without requiring manual check-in and check-out procedures. The systems and techniques involve tracking locations (anonymously) of users within a facility and associating locations where the user placed items with a unique identifier. The item is secured except for access by the user as gates or panels prevent accessing items or exiting with items other than those associated with the user.
G07C 9/29 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer le laissez-passer comportant des éléments électroniques actifs, p. ex. des cartes à puce
G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
G07C 9/10 - Barrières mobiles avec moyens d’enregistrement
G07C 9/25 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer combiné à une vérification d’identité du titulaire du laissez-passer utilisant des données biométriques, p. ex. des empreintes digitales, un balayage de l’iris ou une reconnaissance de la voix
G07C 9/28 - Enregistrement de l’entrée ou de la sortie d'une entité isolée comportant l’utilisation d’un laissez-passer le laissez-passer permettant le repérage ou signalant la présence
64.
Voice controlled assistant with coaxial speaker and microphone arrangement
A voice controlled assistant has a housing to hold one or more microphones, one or more speakers, and various computing components. The housing has an elongated cylindrical body extending along a center axis between a base end and a top end. The microphone(s) are mounted in the top end and the speaker(s) are mounted proximal to the base end. The microphone(s) and speaker(s) are coaxially aligned along the center axis. The speaker(s) are oriented to output sound directionally toward the base end and opposite to the microphone(s) in the top end. The sound may then be redirected in a radial outward direction from the center axis at the base end so that the sound is output symmetric to, and equidistance from, the microphone(s).
H04R 1/32 - Dispositions pour obtenir la fréquence désirée ou les caractéristiques directionnelles pour obtenir la caractéristique directionnelle désirée uniquement
H04R 1/34 - Dispositions pour obtenir la fréquence désirée ou les caractéristiques directionnelles pour obtenir la caractéristique directionnelle désirée uniquement en utilisant un seul transducteur avec des moyens réfléchissant, diffractant, dirigeant ou guidant des sons
G10L 15/20 - Techniques de reconnaissance de la parole spécialement adaptées de par leur robustesse contre les perturbations environnantes, p. ex. en milieu bruyant ou reconnaissance de la parole émise dans une situation de stress
G10L 21/0216 - Filtration du bruit caractérisée par le procédé d’estimation du bruit
H04R 3/12 - Circuits pour transducteurs pour distribuer des signaux à plusieurs haut-parleurs
65.
Self-service management of network address allocations using hierarchical allocation pools
Disclosed are various embodiments for self-service management of network address allocations using hierarchical allocation pools. A first network address pool is created for a customer of a cloud provider network. The first network address pool is divided into a second network address pool for a cloud resource of the customer. A first network address block from the second network address pool is assigned to the cloud resource.
09 - Appareils et instruments scientifiques et électriques
Produits et services
(1) Recorded software and computer hardware for recording, storing, analyzing, and sharing enhanced video and images; integrated imaging hardware and software, namely, enhanced video and image systems and related functionality embedded into security and surveillance apparatuses
Changes made to a database table are accumulated, in durable storage, and snapshots of partitions of the table are obtained. For successive snapshots of a partition, the system accesses a previous snapshot, applies changes from the accumulated changes, and stores the updated snapshot to a durable data store. The accumulated changes and the successive partition snapshots are made available to restore the database to any point in time across a continuum between successive snapshots. Although each partition of the table may have a backup snapshot that was generated at a time different from when other partition snapshots were generated, changes from respective change logs may be selectively log-applied to distinct partitions of a table to generate an on-demand backup of the entire table at common point-in-time across partitions. Point-in-time restores of a table may rely upon a similar process to coalesce partition snapshots that are not aligned in time.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
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
69.
AUGMENTING DATASETS FOR TRAINING AUDIO GENERATION MODELS
A target voice dataset may be augmented using speech prediction. Encoder and decoder models may be trained to encode audio data into encoded speech data and convert it back to audio. The encoded units may include semantic information (e.g., phonemes and/or words) as well as feature data indicating prosody, timbre, speaker identity, speech style, emotion, etc. of speech. An acoustic/semantic language model (ASLM) may be configured to predict encoded speech data in a manner analogous to a language model predicting words; for example, based on preceding encoded speech data. The models may be used to generate synthesized speech samples having voice characteristics (e.g., feature data) similar to those of the target voice dataset. The augmented dataset may be used to train a text-to-speech (TTS) model to reproduce the target voice characteristics, and may improve performance of the TTS model over training with only the original target voice dataset.
G10L 13/047 - Architecture des synthétiseurs de parole
G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la paroleSélection d'unités de reconnaissance
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 25/18 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande
70.
EVENT ROUTING AND ENCRYPTION IN A MULTI-TENANT PROVIDER NETWORK
In a multi-tenant network, event routing and encryption techniques involve processing events through an event bus service. When an event is received, it is evaluated against routing rules. If the event matches a rule linking to a resource in another customer account, the event data is encrypted using a key associated with that account. Finally, the encrypted event is delivered to the target resource, ensuring secure communication between different customer accounts within the network.
The following description is directed to a configurable logic platform. In one example, a configurable logic platform includes host logic and a reconfigurable logic region. The reconfigurable logic region can include logic blocks that are configurable to implement application logic. The host logic can be used for encapsulating the reconfigurable logic region. The host logic can include a host interface for communicating with a processor. The host logic can include a management function accessible via the host interface. The management function can be adapted to cause the reconfigurable logic region to be configured with the application logic in response to an authorized request from the host interface. The host logic can include a data path function accessible via the host interface. The data path function can include a layer for formatting data transfers between the host interface and the application logic.
An attestation service is configured to receive a request to enable attestation for a compute instance according to an attestation policy indicating one or more baseline health measurement values for validating compute instances. The attestation service provides a network endpoint for the compute instance to request attestation. The attestation service receives, via the network endpoint from a compute instance, one or more health measurement values of the compute instance. The attestation service validates the compute instance based at least on a comparison of the one or more current health measurement values and the one or more baseline health measurement values. The attestation service, in response to validating the compute instance, generates an attestation token indicating that the compute instance is authorized to access a secured resource of the provider network.
Techniques for tracking and maintaining queues used for executing pending quantum objects using respective quantum processing units (QPUs) are disclosed. An amount of time to execute a given quantum object depends on many factors, and a non-deterministic nature of quantum computing resources is such that, while knowing an expected wait time in a queue for access to a given QPU is useful, it is difficult to reliably determine. A quantum computing service that manages submission and execution of quantum objects to respective QPUs may apply QPU-specific machine learning models in order to predict expected wait times and provide that information to customers. By generating labeled datasets using ground truth wait times pertaining to already-executed quantum objects, respective machine learning models may be trained using a supervised learning technique, which may be a self-contained and re-occurring process.
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
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
In a multi-tenant network, event routing and encryption techniques involve processing events through an event bus service. When an event is received, it is evaluated against routing rules. If the event matches a rule linking to a resource in another customer account, the event data is encrypted using a key associated with that account. Finally, the encrypted event is delivered to the target resource, ensuring secure communication between different customer accounts within the network.
09 - Appareils et instruments scientifiques et électriques
Produits et services
(1) Recorded software and computer hardware for recording, storing, analyzing, and sharing enhanced video and images; integrated imaging hardware and software, namely, enhanced video and image systems and related functionality embedded into security and surveillance apparatuses
76.
Background incremental deletion cleanup techniques at storage services
A determination is made as to whether a workload associated with a collection of data items satisfies a first condition. If the first condition is satisfied, a determination is made as to whether a metric of dirty records to which delete operations have been directed within a portion of a data item satisfies a second condition. If the second condition is also satisfied, a cleanup operation may be initiated so that data blocks storing the portion of the data item do not include the deleted record.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
Systems and methods for intelligent device grouping are disclosed. An environment, such as a home, may have a number of voice-enabled devices and accessory devices that may be controlled by the voice-enabled devices. One or more models, such as linguistics model(s) and/or device affinity models may be utilized to determine which accessory devices are candidates for inclusion in a device group, and a recommendation for grouping the devices may be provided. Device-group naming recommendations may also be generated and may be sent to users.
A system configured to detect custom acoustic events, where the system generates an acoustic event profile for the custom acoustic event based on a natural language description and without a sample of the sound. The system may generate a profile for a new custom sound based on a natural language description provided by the user; for example, a “microwave beep.” If the system does not have an existing event profile for a microwave beep, the system may ask the user questions to determine whether any existing event profiles are close (e.g., is the sound similar to a “fan,” “alarm,” “appliance beep,” etc.). The system may detect an event that may be a possible match for the custom sound and ask the user to verify whether the detected event corresponds to the custom sound. The system may update the event profile based on the user's response.
Techniques for performing voice-based user recognition are described. When a device receives audio data corresponding to a spoken user input, the device may generate spoken user input embedding data representing speech characteristics of the spoken user input. The device may also identify user embedding data representing speech characteristics of a user known to the device. A machine learning (ML) model may process the spoken user input embedding data to generate reduced spoken user input embedding data including a reduced number of dimensions, where the reduced number of dimensions are functions of the higher number of dimensions of the spoken user input embedding data. Moreover, the ML model may process the user embedding data to generate reduced user embedding data including a reduced number of dimensions, where the reduced number of dimensions are functions of the higher number of dimensions of the user embedding data and are tuned to characteristics of users of the device (as opposed to a representation of all possible users). A comparison of the reduced spoken user input embedding data and the reduced user embedding data may be used to determine whether the user spoke the user input.
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
The present disclosure generally relates to systems and methods for configuring Security Assertion Markup Language (SAML) access network-based services. An identity provider can authenticate the customer and provide SAML authentication information to a SAML configuration service. Based on the customer's authentication information, the SAML configuration service can discover SAML-enabled services and analyze the customer's usage pattern of each discovered service. The SAML configuration service may prioritize the discovered services based on the analysis and transmit a list of the discovered services to the customer based on a sequence of the prioritization. The SAML configuration service also can configure SAML configuration associated with each SAML-enabled service by identifying one or more parameters and applying parsing rules.
Systems and methods for automated actions for application policy violations are disclosed. For example, policy violation evaluation components may monitor requests and/or responses from one or more applications to identify content policy violations. When a violation is identified, an automated decision engine utilizes data representing the policy violation along with, in example, contextual information about the policy violation to identify a rule from a rules database that is associated with the policy violation. An action is determined from the selected rule, and a command is generated to perform the action in response to the policy violation.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/51 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade du chargement de l’application, p. ex. en acceptant, en rejetant, en démarrant ou en inhibant un logiciel exécutable en fonction de l’intégrité ou de la fiabilité de la source
An object-based data storage service receives a request to store a data object in association with a smart data storage tier. Based at least in part on characteristics of the data object, the object-based data storage service identifies and stores the data object in a first location corresponding to a first data storage tier. The object-based data storage service monitors access to the data object to identify a second set of characteristics of the data object. This second set of characteristics is used to determine that the data object is to be transitioned to a second data storage tier. The object-based data storage service, based at least in part on this determination, stores the data object in a second location corresponding to the second data storage tier.
Systems and methods are described for providing an application-level gateway that allows computing devices to utilize an on-demand network code execution system. An on-demand network code execution system may allow users to submit code to be executed in a serverless environment, and may provide an interface for executing the user-submitted code on demand. The interface may require that users authenticate, provide input in a particular format, or meet other criteria when sending a request to execute the code. An application-level gateway may thus provide an interface that implements these functions, thereby allowing computing devices to interact with the code as though it were running on a server (e.g., by using the Hypertext Transport Protocol). The application-level gateway may also use on-demand code execution to provide load balancing for servers that are running the user-submitted code, and seamlessly provide access to code that runs on both server-based and serverless environments.
Approaches presented herein can allocate resources in such a way that sufficient capacity will be provided to perform a job or task, while minimizing any excess capacity included with those allocated resources. A number of jobs can be performed with differently sized resource instances in some embodiments, to determine an instance size, from a set of available sizes, that is appropriate for each of those jobs. Various parameters for those jobs can be determined, and those values associated with the determined instance sizes. When a new job is received that is to be performed, the parameter values for that job can be compared against the corresponding values for these testing jobs, and an instance size can be selected where a testing job that was successfully performed with that instance size had the same or larger values for these parameters.
Techniques are described for predicting a future defect and triggering a mitigation action. In an example, a system generates a first input to a causal model based on geographical data associated with a location and area data associated with one or more areas that include the location, and determines a first output of the causal model. The first output indicates a first prediction of a cause of a past defect for a service associated with the location. The system also generates a second input to a predictive model based on the first input and the first output, and determines a second output of the predictive model. The second output indicates a second prediction of a future defect associated with the service. Based on the second prediction, a mitigation action can be performed such that the future defect is prevented.
Devices and techniques are generally described for generating user satisfaction data in a natural language processing system. In various examples, first user input data may be received by a natural language processing system. Behavioral data related to the first user input data may be determined. Natural language processing error data related to the first user input data may be determined. First response data corresponding to the first user input data may be determined. First response characteristic data related to the first response data may be determined. First user satisfaction data may be determined based at least in part on the first response characteristic data, the behavioral data, and the natural language processing error data.
G10L 13/00 - Synthèse de la paroleSystèmes de synthèse de la parole à partir de texte
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 15/30 - Reconnaissance distribuée, p. ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux
G10L 25/30 - Techniques d'analyse de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux
Systems and methods are described for implementing an event tracing system for an open radio access network (“RAN”). A RAN implementation may be distributed across multiple components, including both special-purpose components such as radio units and general purpose components such as local or cloud-based servers. A RAN event tracing system may thus be used to troubleshoot issues with the RAN implementation by collecting information from distributed components regarding events that occur on these components during the translation of data into radio signals and vice versa. The RAN event tracing system may be used to search for events associated with a particular identifier, such as a radio network temporary identifier, and to display representations of radio frames that were generated by the components and display information regarding the events that led to the placement of particular resource elements onto the radio frames.
H04L 43/04 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux
G06F 16/9538 - Présentation des résultats des requêtes
H04L 43/045 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux pour la visualisation graphique des données de surveillance
H04L 43/10 - Surveillance active, p. ex. battement de cœur, utilitaire Ping ou trace-route
45 - Services juridiques; services de sécurité; services personnels pour individus
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Advertising and marketing services, namely, promoting the goods and services of others; promoting the goods and services of others by organizing content of business information provided over a global computer network and other electronic and communications networks according to user preferences; promoting the goods and services of others by providing, searching, browsing and retrieving information, sites, and other resources available on global computer networks and other electronic and communications networks for others and providing consumer product information for the purpose of assisting with the selection of general consumer merchandise to meet the consumer's needs; providing information and news in the field of business, namely, information and news on current events and on economic, legislative, and regulatory developments as it relates to and can impact businesses; providing consumer information and related news in the field of entertainment, arts and literature, lifestyle and personal growth, education and child development, travel, business and finance, science and technology, politics and government, health and physical fitness, medicine, sports, weather, law, vehicles and transportation, real estate, fashion and design, food and cooking, home decorating, music and cinema, and history; providing information, news, and commentary in the field of politics, providing information in the field of government affairs, and providing consumer information relating to a wide variety of products; providing consumer information via voice-controlled automated inquiries, namely, providing an online automated consumer information resource database for searching, locating, rating and providing directions for the purchase, consumption and use of a wide range of consumer products, services and information over a global communications network Telecommunications services, namely, transmission of images, text, video and audio, and data via telecommunications networks, wireless communications networks, and the internet; computer services, namely, providing access to databases featuring news and information in the fields of artificial intelligence, machine learning, large language models, natural language processing, and software development; telecommunication services, namely, electronic transmission of streamed and downloaded audio, video and multimedia content files via computer and other communications networks; telecommunication access services; audio broadcasting and transmission for others of educational and entertainment digital media; delivery of messages by electronic transmission; electronic transmission of information and data Online social networking services; providing on-line computer databases and on-line searchable databases in the field of social networking; Personal concierge services for others comprising making requested personal arrangements and reservations and providing customer-specific information to meet individual needs; providing a searchable database featuring audio, video and audiovisual content available through the Internet, telecommunications networks and wireless telecommunications networks in the field of online social networking; security services for the protection of property and individuals, namely, home security services for the protection of people and tangible property, and personal security services for the protection of people and tangible property Downloadable computer programs and downloadable computer software for natural language processing, generation, understanding and analysis; downloadable software development kits (SDKs) comprising of downloadable software development tools and downloadable software for use as an application programming interface (API) for creating software and applications related to internet connected consumer electronic devices; downloadable search engine software; media players; computer peripheral devices; downloadable computer software for accessing, browsing, and searching online databases, audio, video, and multimedia content, games, software applications, software application marketplaces; cloud-connected and voicecontrolled smart audio speakers with virtual personal assistant capabilities; downloadable computer programs and downloadable computer software for machine-learning based language and speech processing software; voice-controlled information devices; downloadable computer chatbot software for simulating conversations; downloadable computer software for use as an application programming interface (API); wireless handheld devices; downloadable voice-enabled software applications for personal information management; wireless controllers to monitor and control the functioning of other electronic devices; downloadable computer software programs for developing computer software applications; downloadable computer software for use to connect and control internet of things (IoT) electronic devices; downloadable computer software using artificial intelligence (AI) for the production of speech, text, images, video, sound, and code; downloadable speech to text conversion software; downloadable computer software used for controlling wireless handheld devices, gaming devices, and toys; downloadable computer software for use in retail store operation and ordering services for a wide variety of consumer goods, namely, to facilitate e-commerce transactions; downloadable home automation and home device integration software; downloadable voice command and recognition software; downloadable computer software for building, managing, updating, developing, training, evaluating, and monitoring generative user experiences powered by machine learning, deep learning, and artificial intelligence; downloadable software for machine learning and deep learning; downloadable computer software for the development of software to manage, connect, and operate internet of things (IoT) electronic devices; downloadable wireless communication software for voice, audio, video, and data transmission; downloadable computer software for accessing, monitoring, tracking, searching, saving, and sharing information; downloadable software development kits (SDKs) consisting of downloadable computer software development tools for the development of voice service delivery and nature language understanding technology across global computer networks, wireless networks, and electronic communications networks; downloadable computer software used for controlling stand-alone voice controlled information and personal assistant devices; downloadable computer software for a generative AI powered application using natural language processing to generate answers within the scope of connected data repositories; downloadable computer software for use in the creation, deployment, and utilization of artificial intelligence software applications; downloadable personal vehicle integration software; downloadable personal assistant software; chatbots, digital assistants, natural language processors, and expert systems; downloadable computer software for multimodal machine-learning based language, text, speech, image, video, code, and sound processing software; downloadable computer software using artificial intelligence for machine learning and deep learning for facilitating interaction, communication and actions between humans and artificial intelligence chatbots; downloadable computer software for developing, running and analyzing algorithms that are able to learn to analyze, classify, and take actions in response to exposure to data; downloadable computer software for accessing, browsing and searching online databases; downloadable chatbot software for providing information from searchable indexes and databases of information, including text, music, images, videos, software algorithms, mathematical equations, electronic documents, and databases; downloadable computer software for connecting, operating, integrating, controlling, and managing networked consumer electronic devices via wireless networks; downloadable chatbot software for simulating conversations, analyzing images, sound and video, summarizing text, creating content, generating code, brainstorming, trip planning, and answering queries Entertainment services, namely, providing on-line prerecorded continuing audio programs in the field of entertainment information relating to motion pictures, music, television programs, books, educational multimedia presentations, movies, sporting goods, toys, games, electronics, entertainment videos and DVDs, and other household and consumer goods; providing on-line computer games and on-line interactive children's stories; providing information, reviews and personalized recommendations in the field of entertainment; entertainment services, namely, providing temporary use of non-downloadable chatbots and virtual assistants; provision of information in the field of entertainment; providing a website featuring information in the fields of software, artificial intelligence, augmented reality, generative artificial intelligence, artificial general intelligence, chatbots, commerce, business, entertainment, and software development; providing an on-line non-downloadable entertainment database, namely, providing online non-downloadable on-demand digital games provided on demand via voice activated requests, providing online non-downloadable movies, and providing television shows; providing information in the fields of business, commerce, entertainment, artificial intelligence, software, generative artificial intelligence, artificial general intelligence, large language models, software development, natural language processing, machine learning, chatbots, and augmented reality; providing information relating to entertainment and education provided online from a computer database or a global computer network relating to movies, motion pictures, documentaries, films, television programs, graphic works, animation, and multimedia entertainment presentations; entertainment services, namely, providing online nondownloadable clips of prerecorded audio, visual, and audiovisual works via wireless networks in the field of movies, television, musicals, recreational activities, sports, sporting events, sports instruction, leisure activities, educational and entertainment tournaments, sports and entertainment gaming, dance, art, cultural or educational exhibitions, membership clubs, radio, comedy shows, sports, educational and entertainment contests, educational and entertainment games, educational and entertainment festivals, museums, parks, concerts, cultural events, publishing, animation, fashion, current events, news, technology, and animation; providing a website featuring virtual environments in which users can interact with chatbots and virtual assistants for entertainment purposes; providing information, news, non-downloadable articles, and commentary in the field of entertainment information relating to movies, television, audiovisual works, music, audio works, books, theatre, literary works, sporting events, recreational activities, leisure activities, tournaments, art, dance, musicals, cultural or educational exhibitions, sports instruction, membership clubs, radio, comedy, contests, visual works, games, gaming, festivals, museums, parks, cultural events, concerts, publishing, animation, current events, and multimedia presentations; providing an on-line nondownloadable entertainment database, namely, providing online non-downloadable music, and other online non-downloadable digital text, online non-downloadable audio recordings, and online non-downloadable video files all featuring entertainment information in the nature of sports and entertainment books, sports and entertainment magazines, sports and entertainment news, and general sports and entertainment information; providing an on-line non-downloadable searchable database in the nature of on-demand and online nondownloadable audio recordings, video recordings, and audiovisual content, all in the field of sports and entertainment, available through the internet, telecommunications networks, and wireless telecommunications networks Software as a service (SaaS) featuring computer software for use in retail store operation and ordering services for a wide variety of consumer goods, namely, to facilitate e-commerce transactions; software as a service (SaaS) services featuring software for use in database management; software as a service (SaaS) services, namely, hosting software for use by others for use providing an online database featuring a wide range of general interest information via the internet; providing internet search engines; providing online non-downloadable software using artificial intelligence for the production of human speech and text; providing online nondownloadable chatbot software for simulating conversations; Software as a service (SaaS) services featuring software applications for a generative AI powered application using natural language processing to generate answers within the scope of connected data repositories; computer software development in the field of mobile applications; computer software consultation services for developing software applications; providing information from searchable indexes and databases of information, including databases, text, images, videos, music, software algorithms, mathematical equations, and electronic documents; application service provider (ASP) services featuring software for controlling, integrating, operating, connecting, and managing voice controlled information devices, namely, cloud-connected and voice-controlled smart consumer electronic devices and electronic personal assistant devices; providing customized computer searching services, namely, searching and retrieving information at the user's specific request via the internet; providing online non-downloadable software for natural language processing, generation, understanding and analysis; Software as a service (SaaS) featuring computer software for others to use for the development of software applications; hosting of third party digital content in the nature of photos, videos, text, data, images, web sites, and other electronic works on the internet; Software as a service (SaaS) services featuring software using artificial intelligence for machine learning and deep learning for building conversational query systems and digital assistants; computer services, namely, providing search platforms to allow users to request and receive content, text, visual works, audio works, audiovisual works, literary works, data, files, documents, and electronic works; technical support and consultation services for developing applications, namely, providing technical advice and information concerning the development of computer software applications and consulting services thereof; computer services, namely, providing search platforms to allow users to request and receive photos, videos, text, data, images, and electronic works; providing temporary use of online non-downloadable internet browser software; Software as a service (SAAS) services featuring software using artificial intelligence for indexing, integrating, and retrieving data for both internal applications and external communication; providing online non-downloadable software for multi-modal artificial intelligence and machine-learning based language, text, sound, code, video, image, speech, and sound processing software; Providing online non-downloadable software for machine learning and deep learning; Providing online non-downloadable software for use in large language models and artificial intelligence; Software as a service (SaaS) featuring computer software for accessing, browsing, and searching online databases, audio, video and multimedia content, games, and software applications, software application marketplaces; providing online nondownloadable software for processing speech, text, sound, code, videos, images, and sound input; providing online non-downloadable software for generating speech, text, sound, code, videos, images, and sound output; computer services, namely, creating and hosting an on-line website community for registered users to engage in social networking; Software as a service (SaaS) featuring computer software for connecting, operating, integrating, controlling, and managing networked consumer electronic devices, home climate devices and lighting products via wireless networks; Providing online non downloadable software for use in the creation, deployment, and utilization of artificial intelligence software applications; providing online nondownloadable software for creating generative models; providing temporary use of online nondownloadable computer software and hosting online web facilities to enable users to access computer software and download computer software; Providing temporary use of online nondownloadable software for facilitating multi-modal natural language, speech, text, sound, code, videos, images, and sound input; Software as a service (SaaS) featuring computer software for use as an application programming interface (API); Software as a service (SaaS) featuring computer software for others to use for the development of software to manage, connect, and operate internet of things (IoT) electronic devices; providing temporary use of on-line nondownloadable software and applications for accessing streaming audio and video files, games, social networks, text files, and multimedia files; application service provider (asp) featuring software for use in database management; platform as a service (PaaS) featuring computer software platforms for use in database management; design and development of computer hardware and computer software; Software as a service (SaaS) featuring computer software for accessing, monitoring, tracking, searching, saving, and sharing information on topics of general interest; application service provider (asp) featuring application programming interface (API) software for the streaming, storage, and sharing of video games, content, data and information; platform as a service (PaaS) services featuring computer software platforms for the development and operation of chatbots, digital assistants, natural language processors, and expert systems; Software as a service (SaaS) featuring computer software used for controlling stand-alone voice controlled information and personal assistant devices; providing online nondownloadable software for machine-learning based language and speech processing software
45 - Services juridiques; services de sécurité; services personnels pour individus
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Advertising and marketing services, namely, promoting the goods and services of others; promoting the goods and services of others by organizing content of business information provided over a global computer network and other electronic and communications networks according to user preferences; promoting the goods and services of others by providing, searching, browsing and retrieving information, sites, and other resources available on global computer networks and other electronic and communications networks for others and providing consumer product information for the purpose of assisting with the selection of general consumer merchandise to meet the consumer's needs; providing information and news in the field of business, namely, information and news on current events and on economic, legislative, and regulatory developments as it relates to and can impact businesses; providing consumer information and related news in the field of entertainment, arts and literature, lifestyle and personal growth, education and child development, travel, business and finance, science and technology, politics and government, health and physical fitness, medicine, sports, weather, law, vehicles and transportation, real estate, fashion and design, food and cooking, home decorating, music and cinema, and history; providing information, news, and commentary in the field of politics, providing information in the field of government affairs, and providing consumer information relating to a wide variety of products; providing consumer information via voice-controlled automated inquiries, namely, providing an online automated consumer information resource database for searching, locating, rating and providing directions for the purchase, consumption and use of a wide range of consumer products, services and information over a global communications network Telecommunications services, namely, transmission of images, text, video and audio, and data via telecommunications networks, wireless communications networks, and the internet; computer services, namely, providing access to databases featuring news and information in the fields of artificial intelligence, machine learning, large language models, natural language processing, and software development; telecommunication services, namely, electronic transmission of streamed and downloaded audio, video and multimedia content files via computer and other communications networks; telecommunication access services; audio broadcasting and transmission for others of educational and entertainment digital media; delivery of messages by electronic transmission; electronic transmission of information and data Online social networking services; providing on-line computer databases and on-line searchable databases in the field of social networking; Personal concierge services for others comprising making requested personal arrangements and reservations and providing customer-specific information to meet individual needs; providing a searchable database featuring audio, video and audiovisual content available through the Internet, telecommunications networks and wireless telecommunications networks in the field of online social networking; security services for the protection of property and individuals, namely, home security services for the protection of people and tangible property, and personal security services for the protection of people and tangible property Downloadable computer programs and downloadable computer software for natural language processing, generation, understanding and analysis; downloadable software development kits (SDKs) comprising of downloadable software development tools and downloadable software for use as an application programming interface (API) for creating software and applications related to internet connected consumer electronic devices; downloadable search engine software; media players; computer peripheral devices; downloadable computer software for accessing, browsing, and searching online databases, audio, video, and multimedia content, games, software applications, software application marketplaces; cloud-connected and voicecontrolled smart audio speakers with virtual personal assistant capabilities; downloadable computer programs and downloadable computer software for machine-learning based language and speech processing software; voice-controlled information devices; downloadable computer chatbot software for simulating conversations; downloadable computer software for use as an application programming interface (API); wireless handheld devices; downloadable voice-enabled software applications for personal information management; wireless controllers to monitor and control the functioning of other electronic devices; downloadable computer software programs for developing computer software applications; downloadable computer software for use to connect and control internet of things (IoT) electronic devices; downloadable computer software using artificial intelligence (AI) for the production of speech, text, images, video, sound, and code; downloadable speech to text conversion software; downloadable computer software used for controlling wireless handheld devices, gaming devices, and toys; downloadable computer software for use in retail store operation and ordering services for a wide variety of consumer goods, namely, to facilitate e-commerce transactions; downloadable home automation and home device integration software; downloadable voice command and recognition software; downloadable computer software for building, managing, updating, developing, training, evaluating, and monitoring generative user experiences powered by machine learning, deep learning, and artificial intelligence; downloadable software for machine learning and deep learning; downloadable computer software for the development of software to manage, connect, and operate internet of things (IoT) electronic devices; downloadable wireless communication software for voice, audio, video, and data transmission; downloadable computer software for accessing, monitoring, tracking, searching, saving, and sharing information; downloadable software development kits (SDKs) consisting of downloadable computer software development tools for the development of voice service delivery and nature language understanding technology across global computer networks, wireless networks, and electronic communications networks; downloadable computer software used for controlling stand-alone voice controlled information and personal assistant devices; downloadable computer software for a generative AI powered application using natural language processing to generate answers within the scope of connected data repositories; downloadable computer software for use in the creation, deployment, and utilization of artificial intelligence software applications; downloadable personal vehicle integration software; downloadable personal assistant software; chatbots, digital assistants, natural language processors, and expert systems; downloadable computer software for multimodal machine-learning based language, text, speech, image, video, code, and sound processing software; downloadable computer software using artificial intelligence for machine learning and deep learning for facilitating interaction, communication and actions between humans and artificial intelligence chatbots; downloadable computer software for developing, running and analyzing algorithms that are able to learn to analyze, classify, and take actions in response to exposure to data; downloadable computer software for accessing, browsing and searching online databases; downloadable chatbot software for providing information from searchable indexes and databases of information, including text, music, images, videos, software algorithms, mathematical equations, electronic documents, and databases; downloadable computer software for connecting, operating, integrating, controlling, and managing networked consumer electronic devices via wireless networks; downloadable chatbot software for simulating conversations, analyzing images, sound and video, summarizing text, creating content, generating code, brainstorming, trip planning, and answering queries Entertainment services, namely, providing on-line prerecorded continuing audio programs in the field of entertainment information relating to motion pictures, music, television programs, books, educational multimedia presentations, movies, sporting goods, toys, games, electronics, entertainment videos and DVDs, and other household and consumer goods; providing on-line computer games and on-line interactive children's stories; providing information, reviews and personalized recommendations in the field of entertainment; entertainment services, namely, providing temporary use of non-downloadable chatbots and virtual assistants; provision of information in the field of entertainment; providing a website featuring information in the fields of software, artificial intelligence, augmented reality, generative artificial intelligence, artificial general intelligence, chatbots, commerce, business, entertainment, and software development; providing an on-line non-downloadable entertainment database, namely, providing online non-downloadable on-demand digital games provided on demand via voice activated requests, providing online non-downloadable movies, and providing television shows; providing information in the fields of business, commerce, entertainment, artificial intelligence, software, generative artificial intelligence, artificial general intelligence, large language models, software development, natural language processing, machine learning, chatbots, and augmented reality; providing information relating to entertainment and education provided online from a computer database or a global computer network relating to movies, motion pictures, documentaries, films, television programs, graphic works, animation, and multimedia entertainment presentations; entertainment services, namely, providing online nondownloadable clips of prerecorded audio, visual, and audiovisual works via wireless networks in the field of movies, television, musicals, recreational activities, sports, sporting events, sports instruction, leisure activities, educational and entertainment tournaments, sports and entertainment gaming, dance, art, cultural or educational exhibitions, membership clubs, radio, comedy shows, sports, educational and entertainment contests, educational and entertainment games, educational and entertainment festivals, museums, parks, concerts, cultural events, publishing, animation, fashion, current events, news, technology, and animation; providing a website featuring virtual environments in which users can interact with chatbots and virtual assistants for entertainment purposes; providing information, news, non-downloadable articles, and commentary in the field of entertainment information relating to movies, television, audiovisual works, music, audio works, books, theatre, literary works, sporting events, recreational activities, leisure activities, tournaments, art, dance, musicals, cultural or educational exhibitions, sports instruction, membership clubs, radio, comedy, contests, visual works, games, gaming, festivals, museums, parks, cultural events, concerts, publishing, animation, current events, and multimedia presentations; providing an on-line nondownloadable entertainment database, namely, providing online non-downloadable music, and other online non-downloadable digital text, online non-downloadable audio recordings, and online non-downloadable video files all featuring entertainment information in the nature of sports and entertainment books, sports and entertainment magazines, sports and entertainment news, and general sports and entertainment information; providing an on-line non-downloadable searchable database in the nature of on-demand and online nondownloadable audio recordings, video recordings, and audiovisual content, all in the field of sports and entertainment, available through the internet, telecommunications networks, and wireless telecommunications networks Software as a service (SaaS) featuring computer software for use in retail store operation and ordering services for a wide variety of consumer goods, namely, to facilitate e-commerce transactions; software as a service (SaaS) services featuring software for use in database management; software as a service (SaaS) services, namely, hosting software for use by others for use providing an online database featuring a wide range of general interest information via the internet; providing internet search engines; providing online non-downloadable software using artificial intelligence for the production of human speech and text; providing online nondownloadable chatbot software for simulating conversations; Software as a service (SaaS) services featuring software applications for a generative AI powered application using natural language processing to generate answers within the scope of connected data repositories; computer software development in the field of mobile applications; computer software consultation services for developing software applications; providing information from searchable indexes and databases of information, including databases, text, images, videos, music, software algorithms, mathematical equations, and electronic documents; application service provider (ASP) services featuring software for controlling, integrating, operating, connecting, and managing voice controlled information devices, namely, cloud-connected and voice-controlled smart consumer electronic devices and electronic personal assistant devices; providing customized computer searching services, namely, searching and retrieving information at the user's specific request via the internet; providing online non-downloadable software for natural language processing, generation, understanding and analysis; Software as a service (SaaS) featuring computer software for others to use for the development of software applications; hosting of third party digital content in the nature of photos, videos, text, data, images, web sites, and other electronic works on the internet; Software as a service (SaaS) services featuring software using artificial intelligence for machine learning and deep learning for building conversational query systems and digital assistants; computer services, namely, providing search platforms to allow users to request and receive content, text, visual works, audio works, audiovisual works, literary works, data, files, documents, and electronic works; technical support and consultation services for developing applications, namely, providing technical advice and information concerning the development of computer software applications and consulting services thereof; computer services, namely, providing search platforms to allow users to request and receive photos, videos, text, data, images, and electronic works; providing temporary use of online non-downloadable internet browser software; Software as a service (SAAS) services featuring software using artificial intelligence for indexing, integrating, and retrieving data for both internal applications and external communication; providing online non-downloadable software for multi-modal artificial intelligence and machine-learning based language, text, sound, code, video, image, speech, and sound processing software; Providing online non-downloadable software for machine learning and deep learning; Providing online non-downloadable software for use in large language models and artificial intelligence; Software as a service (SaaS) featuring computer software for accessing, browsing, and searching online databases, audio, video and multimedia content, games, and software applications, software application marketplaces; providing online nondownloadable software for processing speech, text, sound, code, videos, images, and sound input; providing online non-downloadable software for generating speech, text, sound, code, videos, images, and sound output; computer services, namely, creating and hosting an on-line website community for registered users to engage in social networking; Software as a service (SaaS) featuring computer software for connecting, operating, integrating, controlling, and managing networked consumer electronic devices, home climate devices and lighting products via wireless networks; Providing online non downloadable software for use in the creation, deployment, and utilization of artificial intelligence software applications; providing online nondownloadable software for creating generative models; providing temporary use of online nondownloadable computer software and hosting online web facilities to enable users to access computer software and download computer software; Providing temporary use of online nondownloadable software for facilitating multi-modal natural language, speech, text, sound, code, videos, images, and sound input; Software as a service (SaaS) featuring computer software for use as an application programming interface (API); Software as a service (SaaS) featuring computer software for others to use for the development of software to manage, connect, and operate internet of things (IoT) electronic devices; providing temporary use of on-line nondownloadable software and applications for accessing streaming audio and video files, games, social networks, text files, and multimedia files; application service provider (asp) featuring software for use in database management; platform as a service (PaaS) featuring computer software platforms for use in database management; design and development of computer hardware and computer software; Software as a service (SaaS) featuring computer software for accessing, monitoring, tracking, searching, saving, and sharing information on topics of general interest; application service provider (asp) featuring application programming interface (API) software for the streaming, storage, and sharing of video games, content, data and information; platform as a service (PaaS) services featuring computer software platforms for the development and operation of chatbots, digital assistants, natural language processors, and expert systems; Software as a service (SaaS) featuring computer software used for controlling stand-alone voice controlled information and personal assistant devices; providing online nondownloadable software for machine-learning based language and speech processing software
92.
Managed Lifecycle Roles for Secure Credential Vending
Managed lifecycle roles are disclosed. Managed lifecycle roles may be used for secure credential vending or otherwise. For instance, an entity (e.g., administrator or other entity) requests, via an interface of a role manager, creation of a role associated with a lifecycle definition (e.g., an expression of an enforceable expiration of the role or similar characteristic). The role manager stores the role and role lifecycle definition to a data store. Another entity requests to use the role to perform some operation with respect to a resource. A credential service validates the request against a lifecycle definition for the role (and against an access control list, in some examples) and responds to valid requests with credentials useable to perform the operation with respect to the resource. The other entity uses the credentials to perform the operation with respect to the resource. A sweep process manages attributes of the roles.
Techniques for enabling access in a multi-assistant speech processing system are described, where a first assistant system may use components of a second assistant system as data processing components. Runtime operational data and user input data related to the first assistant may be kept separate from the processing data and input data related to the second assistant by propagating a first account ID, for user inputs directed to the first assistant, through the processing pipeline, and using a second account for user inputs directed to the second assistant. A mapping between the first account ID and the second account ID may be accessible to a select number of system components. Handoffs between the two assistants are handled in a manner where data related to one assistant is not accessible by the other assistant.
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 15/06 - Création de gabarits de référenceEntraînement des systèmes de reconnaissance de la parole, p. ex. adaptation aux caractéristiques de la voix du locuteur
Techniques for altering default language, in system outputs, with language included in system inputs are described. A system may determine a word(s) in user inputs, associated with a particular user identifier, correspond to but are not identical to a word(s) in system outputs. The system may store an association between the user identifier, the word(s) in the user inputs, and the word(s) in the system outputs. Thereafter, when the system is generates a response to a user input, the system may replace the word(s), traditionally in the system outputs, with the word(s) that was present in previous user inputs. Such processing may further be tailored to a natural language intent.
A response initiation time target based at least in part on a service level agreement is assigned to a task requested from a network-accessible service. A deadline parameter of a thread identified to perform sub-tasks of the task at a service logic implementation node is set based on the target. The thread is scheduled for execution using an operating system thread scheduling algorithm which selects threads for execution based on their deadline parameters. After a first sub-task of thread is completed, a response is sent to the requester of the task.
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Providing online forums; providing on-line chat rooms and electronic bulletin boards for transmission of messages among users in the field of open source software and software development; providing online access to repositories of information in the field of open source software and software development; video-on-demand transmission; streaming of video and audio material on the Internet. Providing information in the field of open source software and software development; providing online non-downloadable videos in the field of open source software and software development; education services, namely, providing non-downloadable webinars in the field of open source software and software development; education services, namely, providing classes, seminars, conferences, speaker series, workshops, and trainings in the field of open source software and software development.
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Retail store services and online retail store services featuring a wide array of consumer goods of others; retail store services and online retail store services featuring various merchandise and consumer products in the field of clothing, kitchen, entertaining, beauty, personal care, skincare, travel, fitness, health and wellness, home décor, fashion, and fashion accessories products; sales promotion for others; advertising and marketing services, namely, promoting a wide array of consumer goods for others; provision of commercial information and advice for consumers in the choice of products Pre-recorded downloadable audio recordings featuring reality, comedic, and dramatic entertainment programs; pre-recorded video recordings featuring reality, comedic, and dramatic entertainment programs; pre-recorded downloadable audio and visual recordings featuring reality, comedic, and dramatic entertainment programs; pre-recorded audio and visual recordings in optical discs, DVD and CD format featuring reality, comedic, and dramatic entertainment; programs motion picture films featuring animated entertainment, action adventure, live action, comedy, musicals, drama and documentaries Entertainment in the nature of an ongoing television series in the fields of comedy, drama and reality; entertainment services, namely, an ongoing television program in the fields of comedy, drama and reality provided through television, cable, the internet and wireless communications networks; providing online non-downloadable comic books and graphic novels; providing a website featuring blogs and non-downloadable publications in the nature of books, graphic novels, comics and screenplays in the field of entertainment; providing a website featuring entertainment information, audio, video and prose presentations, and online-non-downloadable publications in the nature of fiction and non-fiction books, graphic novels and comics all in the field of entertainment; entertainment services, namely, arranging and conducting contests; providing current event news and information in the field of entertainment relating to contests, video, audio and prose presentations and publications all in the field of entertainment; providing on-line reviews of television shows and movies; providing a video-on-demand website featuring non-downloadable movies and films; providing a website featuring non-downloadable videos in the field of movies, television shows, and film trailers on a variety of topics; providing a searchable on-line entertainment database featuring on-line non-downloadable music, movies, television shows, multimedia presentations in the field of entertainment, audio files featuring music, comic books, and publications in the nature of entertainment; and providing information on entertainment, movies and television shows via social networks
99.
ROUTING INGRESS TRAFFIC FOR LOGICALLY ISOLATED NETWORKS DESTINED FOR IP BLOCKS WITHOUT ANY NETWORK ADDRESS TRANSLATION
Route tables may be associated with ingress traffic for logically isolated networks. A routing device at the edge of a logically isolated network may receive a route to include in a route table that is associated with ingress traffic to the logically isolated network, where the ingress traffic is destined for a block of public or private IP addresses. The route instructs the edge routing device to forward such ingress traffic to a network interface of a network appliance hosted in the logically isolated network. Network packets received at the edge routing device may have a destination of one or more public or private IP addresses in the block of public/private IP addresses. The edge routing device may identify the route in the route table that forwards the ingress network traffic destined for the block of public or private IP addresses to the network interface for the network appliance.
Disclosed are various embodiments relating to an intersection of on-demand network slicing and content delivery. In one embodiment, in response to an application programming interface (API) request, a network slice is provisioned with a quality-of-service requirement in a radio-based network having a radio access network and an associated core network. Also in response to the API request, a transfer of content to a content delivery service at an edge location in the radio-based network is initiated in order to meet the quality-of-service requirement for the network slice.
H04W 48/18 - Sélection d'un réseau ou d'un service de télécommunications
H04W 4/50 - Fourniture de services ou reconfiguration de services
H04W 4/60 - Services basés sur un abonnement qui utilisent des serveurs d’applications ou de supports d’enregistrement, p. ex. boîtes à outils d’application SIM
H04W 28/02 - Gestion du trafic, p. ex. régulation de flux ou d'encombrement
H04W 28/08 - Équilibrage ou répartition des charges
H04W 28/16 - Gestion centrale des ressourcesNégociation de ressources ou de paramètres de communication, p. ex. négociation de la bande passante ou de la qualité de service [QoS Quality of Service]
