Techniques are disclosed relating to database configuration settings overrides. In some embodiments, a database system stores a set of default configuration settings that control operation of the database system. The database system receives a query requesting data from the database system, and metadata about the query. The database system determines, based on the query and the metadata, that a configuration settings override has been specified for the query, where the configuration settings override indicates that one or more of the default configuration settings are to be replaced with one or more configuration settings specific to the query. In response to the determining that a configuration settings override has been specified, the database system executes the query using the one or more specific configuration settings.
Techniques for generating a summary using a machine-learning model native to the operating system running on a user device are discussed herein. The communication platform may receive an instruction to generate a summary to be displayed to a user profile. In such cases, the communication platform may determine whether to generate the summary using on-device systems or using systems in a server of the communication platform (e.g., a device separate from the user device). Based on determining to generate the summary using the on-device systems, the communication platform may identify data to summarize. The communication platform may input the data into a machine-learning model (or large language model (LLM)) residing within the operating system of the user device and receive, as output, a summary. In such cases, the communication platform may cause the summary to be displayed via the user interface of the user device associated with the user profile.
Techniques are described for securing secrets in software build workflows. In some implementations, build instructions call for execution of a first program module and a second program module, where the first program module has been approved to make a privileged request, but the second program module has not. The first program module can be stored in a trusted repository, separately from the second program module. When the first program module is loaded for execution, a cryptographic signature can be validated to determine that the first program module is authentic and as a condition for passing a privileged credential to the first program module. The second program module has no access to the privileged credential. Instead, when the second program module is loaded for execution, a determination can be made whether the second program module makes any privileged requests. Any privileged requests from the second program module will not be fulfilled.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A method to approximate a segment count for a normalized dataset. The method includes sampling items in the primary database object to generate a sample, executing a segmentation count query on the sample to determine how many items in the sample satisfy a set of segment criteria, determining an error value based on an estimated sample size of the sample, a number of items in the sample that satisfy the set of segment criteria, and a confidence level value, determining a range of counts for the segment count based on the number of items in the sample that satisfy the set of segment criteria, the error value, and a total number of items in the primary database object, and providing the range of counts representing an approximated segment count for the normalized dataset.
Embodiments described herein provide bootstrapping language-images pre-training for unified vision-language understanding and generation (BLIP), a unified VLP framework which transfers flexibly to both vision-language understanding and generation tasks. BLIP enables a wider range of downstream tasks, improving on both shortcomings of existing models.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
6.
SEMANTIC SEARCHING OF STRUCTURED DATA USING GENERATED SUMMARIES
Methods, systems, apparatuses, devices, and computer program products are described. An application server or a data processing system may convert a set of metadata associated with a data object (e.g., document, record, asset) from a first structured format into a second serialized format. The set of metadata in the second serialized (e.g., unstructured) format may be input in a large language model (LLM). The LLM may generate a first natural language summary associated with the data object based on the set of metadata. After receiving a natural language query from a user, the LLM may generate a second natural language summary associated with the data object based on the natural language query. The natural language summaries may be vectorized, and the vectorized versions may be compared. Based on the comparison, an indication of the data object corresponding to the natural language query may be displayed.
Methods, systems, apparatuses, devices, and computer program products are described. An application server or a data processing system may generate a set of candidate natural language queries that correspond to a data object (e.g., document, report, assert) based on inputting a set of metadata associated with the data object into a large language model (LLM). The system may embed the candidate natural language queries into a first set of vectors, where a query space may include a collection of the first set of vectors related to the data object. In addition, the system may embed a natural language query received from a user into a second vector. The system may perform a vector-space comparison of the second vector to the first set of vectors or the query space, and retrieve a data object associated with the natural language query based on the comparison.
Techniques are disclosed relating to implementing a statement-level INSTEAD OF trigger. In one embodiment a computer system stores trigger information associated with a statement-level database trigger executable to initiate execution of at least one trigger instruction for a database instead of performing a particular database operation, on a database view, specified by a database operation statement. The computer system receives a first database operation statement specifying performance of the particular database operation on the database view and identifies a set of target rows, within the database view, targeted by the first database operation statement. In addition, the computer system generates a reference table associated with the database view, where the reference table includes rows corresponding to the target rows. The computer system executes the statement-level database trigger instead of executing the database operation statement, where executing the statement-level database trigger includes accessing the reference table.
Techniques are disclosed that relate to skip lists. A computer system maintains a skip list having towers of varying depths and entries storing pointers to other towers. A first tower includes an entry at a particular depth storing a pointer to access an entry of a second tower. The pointer includes first similarity information indicating an amount of similarity between a key of the first tower and a key of the second tower. The computer system performs a traversal of the skip list for a search key. The computer system generates second similarity information indicating an amount of similarity between the first tower's key and the search key. Based on a comparison involving the first and second similarity information and without accessing the second tower to obtain information about its key, the computer system determines whether to traverse to the second tower using the pointer or descend the first tower.
Techniques are disclosed relating to implementing an end-to-end orchestration for a datacenter on a cloud platform. A datacenter may be orchestrated on a cloud platform according to a declarative specification that describes dependences between datacenter entities (e.g., services) in the datacenter. Some datacenter entities may execution dependencies, which include activities, steps, or events that need to be completed for the datacenter entities to be ready for orchestration. Accordingly, in order for an orchestration workflow to be able to execute from beginning to end without interruption, all the execution dependencies for all the datacenter entities in the orchestration workflow need to be completed. The techniques disclosed include automatically initiating execution of the execution dependencies and waiting for indications that the execution activities are completed before executing the orchestration workflow.
A computer-implemented method is disclosed for predicting, based on a previous usage of a cloud-based computing resource by a number of users of the cloud-based computing resource, a future usage of the cloud-based computing resource. The method includes predicting, based on the predicted future usage of the cloud-based computing resource, an anomaly event at the cloud-based computing resource. The method also includes implementing a first anomaly mitigation action, based on the prediction of the anomaly event at the cloud-based computing resource and re-evaluating a status of the anomaly event at the cloud-based computing resource after the implementation of the first anomaly mitigation action. The method further includes implementing a second anomaly mitigation action at the cloud-based computing resource, based on the re-evaluation of the status of the anomaly event.
H04L 41/069 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant des journaux de notificationsPost-traitement des notifications
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
Systems, devices, and techniques are disclosed for network security policy generation and distribution. A security policy written using a Domain Specific Language (DSL) for network security may be received. The security policy may be associated with a service owner and a control plane. A representation of the security policy may be generated from the security policy. A configuration bundle of the service owner may be updated with the representation of the security policy. The security policy may be determined to be approved. A rule set may be generated from the representation of the security policy. A differential between the rule set and a current rule set may be determined. A security component associated with the control plane based on the differential may be configured.
Techniques are disclosed relating to implementing an incremental update to an existing datacenter on a cloud platform. The datacenter may have been built on a cloud platform according to a declarative specification that describes dependencies between datacenter entities in the datacenter. When an update is requested for the datacenter (e.g., by a customer or other entity), the system determines datacenter entities that are being changed in association with the update and execution dependencies associated with the update request. The system then initiates execution of the execution dependences and waits for the execution dependencies to be completed. Once the execution dependencies are completed, the system initiates orchestration of the datacenter in order to update the datacenter on the cloud platform with the addition or removal of datacenter entities on the datacenter.
Disclosed herein are system, method, and computer program product embodiments for secure user interface (UI) customization in an embedded application. An embodiment operates by generating an embedding code and an application configuration corresponding to an updated version of an embedded code of an embedded web application in response to a determination that the embedded web application was published successfully. The embodiment then stores the embedding code, the application configuration, and a particular version of a web component at an application server. The particular version of the web component is designated for use by the embedded web application during runtime of the embedded web application. The embodiment then configures an application endpoint to prevent the embedded web application from accessing, during runtime of the embedded web application, another version of the web component that is different from the particular version of the web component stored at the application server.
A system may include a communication interface receiving information characterizing a customer of a first database tenant of a plurality of database tenants accessing customer relations management services. The system may also include a database system storing one or more database records including the information characterizing the customer and being stored in a profile corresponding with the customer. The database system may receive a request to determine content to provide to the customer in association with an interaction between the customer and a second database tenant. A recommended content item may be determined based at least in part on the one or more database records. A message including an instruction for presenting the recommended content item in a user interface may be transmitted from the database system to a client machine associated with the customer.
Techniques are disclosed that pertain to upgrading a database application. A computer system may determine to upgrade a database application from a current version associated with a first instance of a database catalog that defines the structure of a database that is managed by that database application. The first instance is associated with a first catalog signature that is indicative of the first instance of the database catalog. The computer system generates a second catalog signature that is indicative of a second instance of the database catalog that is associated with the different version. The computer system compares the first catalog signature and the second catalog signature to determine whether the database catalog changes between the current and different versions. Based on the comparing, the computer system then selects one of multiple upgrade processes performable to upgrade the database application to the different version and performs the selected upgrade process.
A method to manage domain-based security profiles in a content delivery network (CDN) is disclosed. The method includes receiving security events detected by one or more security solutions implemented by one or more CDN instances of the CDN, determining, for each of a plurality of domains, a risk score for the domain based on the security events, determining possible next level domains for a CDN instance of the CDN, determining an updated order of an auto-adjusting list maintained by the CDN instance based on risk scores for the domains included in the auto-adjusting list and the possible next level domains for the CDN instance, and sending an update to the CDN instance to cause the CDN instance to update the order of the auto-adjusting list to reflect the updated order, wherein the order of the auto-adjusting list indicates an eviction priority for the domains included in the auto-adjusting list.
A runtime agent that is executable on a virtual machine may obtain one or more identifiers that correspond to one or more software classes from a first configuration file that is configured for the runtime agent. The runtime agent may monitor for loading of the one or more software classes by a first computer program that is being executed on the virtual machine. Further, the runtime agent may execute one or more actions based on detecting the loading of the one or more software classes by the first computer program where the one or more actions may impact the execution of the first computer program on the virtual machine.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/53 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée
A computer-implemented method is disclosed for predicting, based on a previous usage of a cloud-based computing resource by a number of users, a future usage of the cloud-based computing resource and then predicting, based on the predicted future usage, an anomaly event at the computing resource. The method also includes identifying a top contributing user that is responsible for the anomaly event and throttling an access of the top contributing user to the computing resource. The method further includes evaluating a speed of data requests received at the computing resource from the top contributing user after the throttling, and a utilization level of the computing resource. The method also includes dynamically adjusting the speed of data requests received at the computing resource, based on the evaluation of the utilization level of the computing resource, to maintain the utilization level of the computing resource within a predetermined target range.
Embodiments described herein provide a method for content transmission using a cryptographic signature. The method includes: generating, by a neural network model employing a plurality of state parameters and implemented on one or more processors, an output content; generating a string of Hash values based on the output content; creating a cryptographic signature by encrypting the string of Hash values and one or more state parameters of the neural network model using a private key; embedding the cryptographic signature in the output content; and transmitting, via a communication interface, the output content embedded with the cryptographic signature to a destination server.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
A computer-implemented method is disclosed for predicting a future usage of a cloud-based computing resource based on a previous usage of the resource by users, and predicting an anomaly event at the resource. The method also includes identifying a top contributing user responsible for the anomaly event, throttling an access of the top contributing user, evaluating a speed of data requests received from the top contributing user, and maintaining a utilization level of the resource within a predetermined target range. The method further includes dynamically controlling the speed of data requests based on the evaluation of the speed of data requests and a controlling speed of data request recommended by a first artificial intelligence model. The recommendations of the first artificial intelligence model may be validated by a human reasoning based model configured to monitor and mitigate a risk associated with a counter-intuitive recommendation of the first artificial intelligence model.
Techniques are disclosed relating to database query optimizers. In some embodiments, a system receives, from a query optimizer, a plurality of query plans for a database maintained by the database system. The system retrieves a set of database statistics for the database and generates, via a data synthesizer, a plurality of synthetic datasets, where generating a given synthetic dataset is performed based on a given query plan of the plurality of query plans and the set of database statistics, and includes generating a plurality of synthetic data tuples. The system executes the plurality of query plans on the plurality of synthetic datasets and updates the query optimizer based on results of executing the plurality of query plans on the plurality of synthetic datasets. The disclosed data synthesis may advantageously improve query performance due to more efficient query plans being selected for execution of requested queries.
Disclosed herein are system, method, and computer program product embodiments for implementing variable a declarative authentication engine. The system generates a schema that includes a field and has a format defined by an authentication protocol associated with a service. The system then validates a connection request based on comparing the field of the generated schema to a field of the connection request for the service, wherein the connection request is formatted according to the schema and received from a client device. The system then provides the client device access to the service according to the connection request based on a result of the validating.
A method and apparatus for autonomous configuration-based release orchestration that supports staggered feature releases across a plurality of container clusters. A release seeking goal is obtained. An unprocessed stagger is selected as a current stagger based on a stagger order. The current stagger is processed by attempting to cause a deployment of the feature release to the container clusters in the current stagger, receiving an indication of success or failure of the attempted deployment, and determining whether to roll back the current stagger based on the indication. A determination is made whether the release seeking goal can still be met. If the release seeking goal can no longer be met, a release level rollback is caused, and otherwise the selecting, processing, and determining is repeated for the next unprocessed stagger based on the stagger order.
A method and apparatus for autonomous release orchestration that supports staggered releases across a plurality of container clusters. A representation of a risk level for a current release is obtained. Based on the risk level, a set of one or more attributes of a stagger configuration is determined. An attempt to deploy the current release to the plurality of container clusters in accordance with the stagger configuration is caused.
Techniques are disclosed relating to storing database extents in physical storage nodes. To store the extents, a physical storage node of a computer system first accesses assignment metadata, which includes determining 1) virtual groupings of database extents assigned to the physical storage node and 2) database extents associated with the determined one or more virtual groupings. For a given database extent, a corresponding virtual grouping is determinable by performing a first hashing operation that uses an identifier for the given database extent. The physical storage node then accesses and stores the determined database extents. The physical storage node can now service requests for data of the database system that are stored at the first physical storage node.
A method and apparatus for autonomous configuration-based release orchestration. A first engine obtains stagger configuration data that includes an indication of container clusters in each stagger and a stagger order, selects a current stagger based on the order, and attempts to deploy the feature release to the current stagger by causing an app config update to be sent to a second engine within each container cluster of the current stagger, and receives an indication of success or failure of the attempted deployment of the feature release to the current stagger. Responsive to the indication of success or failure, the first engine performs one of a plurality of actions that include attempting to deploy the feature release to a next one of the staggers according to the order responsive to the indication indicating success, and causing a roll back of the current stagger responsive to the indication indicating failure.
Techniques are disclosed relating to determining query plans for execution by database systems. In various embodiments, a query optimizer determines a first query plan to implement a query requesting data from a database system. The determining includes selecting one of a plurality of query plans evaluated based on a cost analysis and caching plan fragments of the unselected query plans. The database system can then determine a second query plan for the query by replacing a plan fragment in the first query plan with one of the cached plan fragments of the unselected query plans.
A method for testing connectivity comprises receiving, by one or more computing devices, a request for a connectivity test, and determining, by the one or more computing devices, whether a point-to-point connectivity test or a service-to-service connectivity test is to be performed. The method further comprises initiating, by the one or more computing devices, the connectivity test in response to the request and based on the determining, where initiating the connectivity test comprises invoking a connectivity testing mechanism. The method further comprises displaying, by the one or more computing devices, a location of a connectivity issue based on the connectivity test, and displaying, by the one or more computing devices, a next step to solve the connectivity issue based on the connectivity test.
Techniques are disclosed relating to implementing automated retries during orchestration of a datacenter on a cloud platform. Generating an orchestration workflow for the datacenter may include generating an aggregate pipeline for the orchestration. The aggregate pipeline includes instances of datacenter entity pipelines that include stages for provisioning and deployment of datacenter entities. The disclosed techniques include adding retry stages to the datacenter entity pipelines that are automatically invoked in the event of failure of a datacenter entity pipeline. The retry stages are placed at the end of individual datacenter entity pipelines and conditional expressions are included that invoke retry strategies defined by owners of the datacenter entity.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
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
31.
DETECTING MISCONFIGURATION OF GUEST ACCOUNT SECURITY PERMISSIONS
Systems, devices, and techniques are disclosed for detecting misconfiguration of guest account security permissions. User personas may be generated from user activity data generated by access using guest accounts to controllers of a cloud computing server system. Clusters of user personas may be generated from the user personas. Anomalous user personas may be identified based on the clusters of user personas. A database query that was made to a database of the cloud computing server system, is associated with an identified user persona, and requested sensitive data may be identified from database query logs. A size of a response from the database to the identified database query may be identified from the database query logs. The size of the response may indicate that the response included the sensitive data. The cloud computing server system may prevent use of the guest account associated with the user persona.
Techniques for determining video transcoding setting(s) for a video content based on information associated with a video content request and encoding the video contents into one or more encoded video contents based on the video transcoding settings are discussed herein. For example, a communication platform may receive a request associated with a video content. The communication platform may determine, based at least in part on the request, device information associated with one or more receiver devices. The communication platform may determine, based at least in part on the device information associated with the receiver devices provided by the communication platform, one or more video transcoding settings associated with the video content. The communication platform may further send one or more encoded video contents encoded based on the one or more video transcoding settings to the receiver devices.
Techniques are disclosed relating to migrating database extents between physical storage nodes. A database system stores current and new assignment metadata mapping virtual groupings of database extents physical storage nodes, the new assignment metadata reflecting a data migration of extents between the plurality of physical storage nodes. During the migration, the database system receives 1) read requests, which it responds to by reading data from a first physical storage node identified using the current assignment metadata and 2) write requests, which it responds to by writing data to a second physical storage node identified using the new assignment metadata. Upon the migration being complete, the system identifies physical storage nodes accessed by subsequent read and write requests using the new assignment metadata.
G06F 16/21 - Conception, administration ou maintenance des bases de données
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
A computer system may determine to perform an upgrade operation to deploy a second database application that is a different version than a first database application associated with a first database catalog that stores catalog objects. The computer system performs the upgrade operation, including preparing a second database catalog and deploying the second database application to manage a database based on the second database catalog. To prepare the second database catalog, the computer system may create the second database catalog and store, in the second database catalog, system catalog objects that are associated with the second database application. The computer system may further identify, from the catalog objects stored in the first database catalog, user catalog objects that were created by users of the database and then copy the identified user catalog objects from the first database catalog to the second database catalog.
A method and apparatus for autonomous container management configuration changes to container clusters during runtime and autonomous configuration-based release orchestration. A release manager manages a staggered feature release that includes staggers, stagger order, and container clusters included in each stagger. A logging service manages logs generated by the container clusters and/or app containers. An update service determines container management configuration changes based on analysis of data provided by the logging service. A shared engine attempts to implement instructions provided by the release manager and the update service at different times. The release manager receives an indication of success or failure of the attempted deployment of the feature release to the current stagger. The release manager, responsive to the indication of success or failure, determines to perform one of a plurality of actions, including attempting to deploy the feature release to the next stagger, and rolling back.
H04L 41/082 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant des mises à jour ou des mises à niveau des fonctionnalités réseau
H04L 41/0859 - Récupération de la configuration du réseauSuivi de l’historique de configuration du réseau en conservant l'historique des différentes générations de configuration ou en revenant aux versions de configuration précédentes
H04L 43/062 - Génération de rapports liés au trafic du réseau
36.
MACHINE LEARNING BASED ON GRAPHICAL ELEMENT GENERATOR FOR COMMUNICATION PLATFORM
Techniques for generating graphical elements via a communication platform are discussed herein. For example, one or more machine-learning models associated with a communication platform may be configured to receive, as input and from a user of the communication platform, a sentiment and/or a graphical element. The machine-learning model may be trained, using prior natural language statements and prior confidence levels associated with previous graphical elements, to output one or more graphical elements associated with the input. The one or more graphical elements may be shared via the communication platform and used to accurately and effectively convey thoughts, emotions, reactions, and ideas, for example.
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
A method and system for classifying a triage-related message related to a software application security technical problem is provided. A triage-related classification is generated for the triage-related message by applying a processor-implemented machine learning model that has been trained to analyze the text of the triage-related message. The generated triage-related classification is sent to a user for remediating the software application security technical problem.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
38.
VERIFICATION OF BACKUP DATA ACROSS A DATA PIPELINE
Systems, devices, and techniques are disclosed for verification of backup data across a data pipeline. Records from a first storage may be received at a first end of a data pipeline. The records may be hashed to generate first hashes. A first hash tree may be generated from the first hashes. The records may be received at a second end of the data pipeline. Bits of bitmaps that correspond to the records may be set. The records may be hashed to generate second hashes. The records may be stored in a second storage. A second hash tree may be generated form the second hashes. Using the bitmaps, whether all of the records or any duplicate records were received may be determined. The first hash tree and the second hash tree may be compared to determine if any of the records stored in the second storage are corrupt.
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
39.
Display screen or portion thereof with animated graphical user interface
Techniques are disclosed relating to a monitoring service executing in a public cloud computer system. A method may include receiving metrics for a database system implemented on a single instance of a virtual machine in the public cloud computer system. The metrics may include a set of metrics indicative of status of the database system, a set of metrics indicative of status of the virtual machine, and a set of metrics indicative of status of the public cloud computer system. The method may also include continuously determining a primary database candidate from a set of standby databases, and detecting that metrics correspond to one of a plurality of disruption scenarios. The method may further include issuing, based on the detecting, a command to trigger a failover to the primary database candidate.
Techniques are disclosed relating to query planning and execution. A computer system can receive a database statement that comprises a LIKE predicate that defines a set of pattern parameters. The computer system may generate first and second query paths for a query plan associated with the database statement. The first query path utilizes an index associated with a database table specified by the database statement while the second query path does not utilize the index. The computer system executes the database statement in accordance with the query plan and values that are provided for the set of pattern parameters. As a part of executing the database statement, the computer system may evaluate those values to determine whether they are prefix constants and execute the first query path instead of the second query path if all the values are prefix constants.
Methods, apparatuses, and computer-program products are disclosed. The method may include training a generative artificial intelligence (AI) model on a plurality of data sources and generating, based on the training, training log metadata indicating individual data sources of the plurality of data sources. The method may include receiving, from a user device, a generative AI query and generating, using the trained generative AI model and based on one or more data sources of the plurality of data sources, a response to the generative AI query. The method may include mapping one or more portions of the response to the one or more data sources of the plurality of data sources based on the training log metadata and transmitting, to the user device, the response and one or more indications of the one or more data sources based on the mapping and the training log metadata.
Systems, methods, and devices provide on-demand environment simulation. A computing platform may be implemented using a server system, where the computing platform is configurable to cause receiving a message from a graphics engine, the message identifying at least one object included in a graphics rendering environment, and further identifying status information associated with the at least one object, and identifying, based on the received message, an instance of an on-demand application associated with the graphics rendering environment. The computing platform may be further configurable to cause mapping the status information to an operation associated with the instance of the on-demand application based on a designated mapping of graphics engine assets to the instance of the on-demand application.
Methods and systems are provided for managing environmental conditions and energy usage associated with a site. One exemplary method of regulating an environment condition at a site involves a server receiving environmental measurement data from a monitoring system at the site via a network, determining an action for an electrical appliance at the site based at least in part on the environmental measurement data and one or more monitoring rules associated with the site, and providing an indication of the action to an actuator for the electrical appliance.
F24F 11/80 - Systèmes de commande caractérisés par leurs grandeurs de sortieDétails de construction de tels systèmes pour la commande de la température de l’air fourni
G05B 15/02 - Systèmes commandés par un calculateur électriques
G05F 5/00 - Systèmes de régulation de variables électriques par détection des écarts du signal électrique à l'entrée du système et par commande par ces écarts d'un dispositif intérieur au système pour obtenir un signal de sortie régulé
G06F 16/951 - IndexationTechniques d’exploration du Web
H02J 13/00 - Circuits pour pourvoir à l'indication à distance des conditions d'un réseau, p. ex. un enregistrement instantané des conditions d'ouverture ou de fermeture de chaque sectionneur du réseauCircuits pour pourvoir à la commande à distance des moyens de commutation dans un réseau de distribution d'énergie, p. ex. mise en ou hors circuit de consommateurs de courant par l'utilisation de signaux d'impulsion codés transmis par le réseau
H04L 12/28 - Réseaux de données à commutation caractérisés par la configuration des liaisons, p. ex. réseaux locaux [LAN Local Area Networks] ou réseaux étendus [WAN Wide Area Networks]
48.
Applied Artificial Intelligence Technology For Natural Language Generation Using A Graph Data Structure And Configurable Chooser Code
Natural language generation technology is disclosed that applies artificial intelligence to structured data to determine content for expression in natural language narratives that describe the structured data. A graph data structure is employed, where the graph data structure comprises a plurality of nodes. Each of a plurality of the nodes (1) represents a corresponding intent so that a plurality of different nodes represent different corresponding intents and (2) is associated with one or more links to one or more of the nodes to define relationships among the intents. A processor executes chooser code based on a plurality of operating rules and/or parameters that control how the chooser code traverses the graph data structure to determine which of the nodes to use for content to be expressed in the natural language narratives, wherein the operating rules and/or parameters are configurable to change strategies for choosing which nodes are used for the content to be expressed in the natural language narratives.
Techniques are disclosed relating to managing database queries. In some embodiments, a server system receives a query from a computer system and determines a set of aspects for the query, including at least a number of columns specified in the query and a computational cost of executing the query. The system generates a query vector based on the set of aspects determined for the query. The system then compares the query vector with a plurality of clusters, ones of the plurality of clusters comprising two or more previously generates query vectors generated based on aspects of queries previously received by the server system. Based on the comparing, specifically a distance between the query vector and the plurality of clusters of previously generated query vectors, the system classifies the query. Based on a classification of the query determined during the classifying, the system manages the query.
Database systems and related customization methods are provided. One exemplary method of modifying a database to support a new functionality involves receiving user input indicative of the new functionality from a client device coupled to a network, identifying existing customizations associated with a user of the client device in the database, determining a plurality of different solutions for implementing the new functionality based at least in part on the existing customizations associated with the user, providing a graphical user interface display at the client device including graphical indicia of the plurality of different solutions for implementing the new functionality, and in response to receiving indication of a selected solution of the plurality of different solutions from the client device, automatically instantiating a new customization corresponding to the selected solution in the database.
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
51.
DATABASE SYSTEM INCIDENT EVALUATION, CLASSIFICATION, AND RESOLUTION SYSTEM
A computing services environment may include a database system, a vector store, a generative language model interface, and/or an incident response system. The database system may be configured to detect a database system incident affecting database system availability or performance and to generate a database incident report characterizing the database system incident. The generative language model interface may be configured to determine a textual description of the database system incident and identify one or more records of the plurality of records by completing an incident evaluation prompt via a generative language model. An incident response engine may be configured to determine an instruction to resolve the database incident based on the textual description and the one or more records, wherein the database system is configured to execute the instruction to update one or more configuration parameters.
Techniques for generating a prebuilt workflow using one or more machine learning models are discussed herein. In some examples, a user may request to generate a workflow configured to automatically perform a series of steps to facilitate the completion of a task(s). In response, the communication platform may present a workflow builder associated a machine learning model(s). In some examples, the machine learning model(s) may receive, as input, a prompt defining a task(s) to be completed and generate, as output, a prebuilt workflow including a suggested series of steps to complete the task(s). The communication platform may receive user input to publish the prebuilt workflow.
Techniques for providing application contextual information. One or more sets of database context identifiers corresponding to events that occur within the database are generated by the database. The one or more sets of database context identifiers have at least one application context field. A session identifier corresponding to a session to be monitored is sent from the application to the database. Information to be stored in the database with the session identifier is sent to the database. Database logs and application logs are correlated using at least the session identifier.
Techniques are disclosed relating to updating a database schema. A computer system may store database schema versions for a database schema. A given schema version may have an active state or one of multiple non-active states. One of the schema versions may be a first schema version that is in the active state and the remaining schema versions may be in the non-active states. The computer system may receive updates to apply to the database schema. The computer system may transition a second schema version from a first non-active state that does not permit structural or content updates to a second non-active state that permits structural and content updates. The computer system may apply the updates to the second database schema version and then transition the second database schema version into the active state and the first database schema version into the first non-active state.
Techniques are disclosed relating to implementing database trigger firing criteria to reduce unnecessary trigger firings. In one embodiment a computer system stores trigger information relating to initiating execution of at least one trigger instruction for a database, in connection with a particular database operation specified by a database operation statement. The trigger information includes a set of one or more database field identifiers for a set of one or more fields in the database. The computer system receives a first database operation statement and makes a determination that at least one field within the set of fields is not specified by the first database operation statement. Based at least in part on the determination, the computer system initiates execution of the at least one trigger instruction.
Techniques are disclosed for managing metadata of a distributed database system in a hybrid manner. A computer system may receive, from a computing device, a request to access a set of data stored in nodes of a distributed storage system that is a caching layer of the system. The system retrieves metadata for a set of data specified in the request, including accessing a reversemap storing a reverse-ordered copy of original metadata stored in a metadata store of the system, where the reversemap is stored on durable storage of the system. Based on retrieving the metadata from the reversemap, the system accesses nodes of the distributed storage system, where the reversemap specifies the nodes of the distributed storage system that store the set of data. The system transmits, to the computing device, information indicating a result of accessing data stored in nodes of the distributed storage system.
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
The disclosed techniques automatically ingest new documents and store data extracted from the documents in a database for conversion into a different format. The disclosed techniques identify, via a backend API, newly released documents that include data for users and, based on the identifying, automatically ingest, via an ingestion call executed made by the backend API, the newly released documents. The disclosed techniques extract, using a computer vision model trained on different types of documents, a data from the newly released documents, where the extracting includes identifying locations within the documents from which to extract data. The disclosed techniques store the extracted data in the database storing data extracted from previously ingested documents for users in a text-based object format and convert, using a machine learning model trained on a plurality of metatags, data corresponding to a given user from the text-based object format to a queryable file format.
An application server may receive user input indicating a plurality of provisioning parameters for provisioning resources on a cloud substrate. The application server may transmit, to a first artificial intelligence (AI) model, the plurality of provisioning parameters and a request to generate, based on the plurality of provisioning parameters, provisioning code associated with the cloud substrate. The application server may transmit, to one or more second AI models, the provisioning code generated by the first AI model, the plurality of provisioning parameters, and a request to analyze the provisioning code based on the plurality of provisioning parameters. The application server may update respective reputation values associated with the first AI model and the one or more second AI models based on one or more analysis results associated with output of the one or more second AI models.
Predicting the salience of one or more data entities to a particular (target) data entity from among a plurality of data entities may comprise generating a graph of the plurality of data entities and a machine-learned model architecture that predicts the salience of the one or more data entities output by the machine-learned model architecture using the graph. For example, the machine-learned model architecture may comprise a first machine-learned model for generating an embedding using the content of the target data entity, a second machine-learned model for generating a vector using the data type indicated by the target data entity, and a third machine-learned model (e.g., a graph neural network or other feed-forward neural network) for generating a contextual representation of the target data entity to which other contextual representations associated with the plurality of data entities may be compared (e.g., using Euclidean distance, cosine similarity, dot product).
Database systems and methods are provided for supporting offline operation of a process flow associated with a native application at a client device. In an offline mode, the method creates a junction object at a client device maintaining an association between a flow and a record, generates a GUI display associated with the flow using downloaded flow configuration metadata, creates a second record comprising input information for the one or more fields for a form associated with the flow via the GUI element(s) of the GUI display, and updates the junction object to maintain an association with the second record. In response to exiting the offline mode, the method automatically creates a form record associated with the record at the database system using the junction object, where the form record includes the input information for the one or more fields from the second record at the client device.
Techniques for updating event data in a calendar are described herein. The communication platform may determine that a user profile has departed from a group. In response, the communication platform may identify a list of groups of which the user profile was a member. Further, the communication platform may use such information to identify a list of events with which the user profile is associated and that correspond to the list of groups. The communication platform may generate a recommendation that may include event(s) to update based on the departure of the user profile. In such cases, the communication platform may display the recommendation to an administrative user profile. The communication platform may receive input data from the administrative user profile indicating a manner in which the event may be modified. Accordingly, the communication platform may modify the data of the event based on the user input data.
Techniques for generating productive meetings are discussed herein. In some examples, a user may request to generate an event. That is, when creating the event invitation, the organizing user may specify meeting criteria that are to be fulfilled for the event to be considered productive. As such, the communication platform may determine whether the event is predicted to be productive by determining whether there is a sufficient number of users that can fulfill the meeting criteria. The communication platform may generate a recommendation including a confidence level indicative of whether the event is likely to be productive. The communication platform may display the recommendation to the organizing user. In response, the communication platform may receive user input data from the organizing user that may indicate an intent of the organizing user to generate the event. Accordingly, the communication platform may generate the event based on the user input data.
Techniques for generating calendar events based on historical data are described herein. A communication platform may evaluate historical data and suggest one or more calendar events to a user profile. In some examples, the communication platform may receive historical data representative of previous activity between a user profile and other user profile(s). The communication platform may analyze the historical data to generate a recommended calendar event. That is, the communication platform may input the historical data into a machine-learned model trained to output one or more recommended calendar events. In such cases, the communication platform may display the recommended calendar event(s) to the user profile. In response to displaying the recommended calendar event, the communication platform may receive user input data representing an intent to generate one or more events corresponding to the recommended calendar event(s). Accordingly, the communication platform may generate the event(s) based on the user input data.
One or more observed database metric values characterizing observed database performance information about a database system implemented in a computing services environment may be determined. One or more observed application metric values characterizing observed performance information about a network-accessible application implemented on an application server in the computing services environment may be determined. The application server may store information in the database system generated while providing computing services via the computing services environment. An updated database system configuration setting for the database system may be determined by applying a machine learning prediction model to a dataset including the one or more observed database metric values and the one or more observed application metric values. An instruction to update the database system may be transmitted based on the updated database system configuration setting.
Implementations for probabilistic wildcard-based DNS resolution are described. A request to validate a first subdomain is received from a domain name system (DNS) service attempting to resolve a DNS request that identifies the first subdomain. A validation outcome that indicates a guess regarding validity of the first subdomain may be determined based on a probabilistic data structure representing a set of valid subdomains. The validation outcome may be sent to the DNS service to cause the DNS service to resolve the first subdomain based on the validation outcome. In the case of the validation outcome indicating a guess of the first subdomain being valid, the first subdomain is caused to be resolved to a first common subdomain. In the case of the validation outcome indicating a guess of the first subdomain being invalid, the first subdomain is caused to be resolved to a second common subdomain.
H04L 61/4511 - Répertoires de réseauCorrespondance nom-adresse en utilisant des répertoires normalisésRépertoires de réseauCorrespondance nom-adresse en utilisant des protocoles normalisés d'accès aux répertoires en utilisant le système de noms de domaine [DNS]
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
H04L 101/345 - Types de noms de réseau contenant des caractères génériques
A method includes: receiving, from a user device, a user request for a graphical user interface (GUI) page containing a plurality of calculated performance indicators that are derived from entity data stored in a secured database system; retrieving a first listing of objects from the entity data containing information for use in calculating the performance indicators; filtering the first listing of objects based on user scope to identify first objects from the first listing of objects that are within scope; generating a first query to retrieve objects identified in the first listing of objects from the database system; instructing the database system via the first query to skip security measures directed to ensuring user access rights to the first objects; calculating the performance indicators based on retrieved objects; generating the GUI page containing the plurality of calculated performance indicators; and signaling the user device to display the generated GUI page.
Methods, computer readable media, and devices for dynamic personalized API assembly are provided. One method may include receiving a data query from a client by a CDN, parsing the data query to generate a modified data query, transmitting the modified data query to an origin server, receiving a content from the origin server, generating a modified content based on the content, and sending the modified content to the client. Another method may include receiving an API call by an origin server, generating an API response by creating a payload file and adding markup directives indicating whether content is cacheable, and transmitting the API response.
Methods, systems, and devices for data processing in a computing system are described. The computing system may receive a notification of an update to network security objects hosted in diverse substrates within the computing system. The computing system may retrieve a network security policy for a service instance impacted by the update. The computing system may update the network security policy for the service instance according to a network security configuration of the hosting substrate. The computing system may translate the updated network security policy into access control lists (ACLs) for network entities managing communications between service instances within the computing system. The computing system may store the ACLs in respective data repositories that are accessible to the network entities. The computing system may transmit a notification that the ACLs are available for deployment, thereby causing the network entities to retrieve the ACLs from the respective data repositories.
Disclosed are examples of systems, apparatuses, methods, and computer program products for dynamic traffic throttling. A server system can receive, via an edge worker associated with a content delivery network (CDN), a first set of requests to access a first site. The server system can determine that traffic to the first site is to be throttled. The server system can determine a throttling rate. The server system can transmit instructions to the edge worker, the instructions configured to cause the edge worker to direct at least a portion of a second set of requests to access the first site to a waiting room site prior to being directed to the first site, the direction of the at least the portion of the second set of requests to the waiting room site being subject to the throttling rate.
H04L 47/122 - Prévention de la congestionRécupération de la congestion en détournant le trafic des entités congestionnées
H04L 41/0816 - Réglages de configuration caractérisés par les conditions déclenchant un changement de paramètres la condition étant une adaptation, p. ex. en réponse aux événements dans le réseau
H04L 41/0896 - Gestion de la bande passante ou de la capacité des réseaux, c.-à-d. augmentation ou diminution automatique des capacités
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
H04L 43/062 - Génération de rapports liés au trafic du réseau
H04L 43/0876 - Utilisation du réseau, p. ex. volume de charge ou niveau de congestion
H04L 43/0882 - Utilisation de la capacité de la liaison
H04L 47/25 - Commande de fluxCommande de la congestion le débit étant modifié par la source lors de la détection d'un changement des conditions du réseau
H04L 47/30 - Commande de fluxCommande de la congestion en combinaison avec des informations sur l'occupation de mémoires tampon à chaque extrémité ou aux nœuds de transit
78.
Data management in a large scale distributed cloud service
A computer-implemented method is disclosed for storing source data related to targeted and untargeted tenants on several publishing servers. The method includes sending metadata related to a first part of the source data related to the targeted tenants from the publishing servers to an aggregating server and storing the metadata in a first database including metadata segments arranged in a first sequenced array and having corresponding state-indicating cursors arranged in a second sequenced array beginning with a first cursor and ending with a last cursor. The method also includes storing the second sequenced array on a second database, querying the first cursor of the second sequenced array from a subscribing server including targeted data related to at least a part of the tenants, querying the metadata segment corresponding to the first cursor, and performing a predetermined operation on at least a part of the targeted data.
Techniques are disclosed relating to a database recovery routine to start up a database system in response to a database failure. The database system accesses checkpoint information identifying a set of active database transactions that were active at a flush point that occurred before the database failure. As a part of the database recovery routine, the database system replays database transactions that occurred between a recovery point and the flush point. The database transactions include the set of active database transactions but exclude any committed or aborted database transactions that occurred between the recovery point and the flush point such that less than a total number of database transactions occurring between the recovery point and the flush point are replayed. The database system further replays, without excluding committed or aborted database transactions, database transactions occurring between the flush point and a recovery end point at which the database failure occurred.
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
Techniques are disclosed in which a computer system implements schema changes for existing database objects by maintaining a logical name and a current physical name corresponding to an existing database object, where the logical name points to the current physical name. The system receives a schema change request specifying the logical name and format changes for the existing object. The system performs a schema change operation in response to the request, including: creating a new database object having a new physical name, copying and transforming data from the existing object to the new object according to the format changes, mirroring new writes directed to the logical name to both the existing and new objects, and causing the logical name to point to the new physical name instead of the current physical name after completing the copying. The system responds to subsequent queries, specifying the logical name, from the new object.
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
A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data.
3. The method also includes initializing the first, second and third modulus reduction arrays with dummy values, storing the source data objects in a source data object array, and storing the first, second and third modulus reduction arrays in a short term memory.
The various implementations described herein include methods and devices for providing an instant messaging interface for data analytics. In one aspect, a method includes displaying a user interface for a communication application, including displaying a shared link to a graphical data visualization. A snapshot button near the link is used to generate a link snapshot comprising a version of the graphical data visualization. In response to user activation of the snapshot button, the method generates the link snapshot. To generate the link snapshot the method first determines if the user or users have proper security access to view the data contained in the graphical data visualization. If a user has proper security access to a subset of the data from the data source, the method dynamically generates the link snapshot for the subset of data to which the user has security access.
A server may execute a communication process flow that controls electronic communications between a tenant of a multitenant system and a set of users corresponding to the tenant. A set of electronic communications that are transmitted to a particular user of the set of users is determined based at least in part on a set of actions defined by the communication process flow. The server may monitor web behavior data associated with the set of users in accordance with a first action of the set of actions, detect that a first user of the set of users satisfies a rule defined by the first action based at least in part on monitoring of the web behavior data, and route the first user to a next action of the set of actions in the communication process flow based at least in part on detecting that the first user satisfies the rule.
Techniques for generating structured data containers via templates associated with a communication platform are described herein. For example, the communication platform may, in response to receiving a request from a first user, generate an object in a virtual space, wherein the request is received via a template or workflow and the object contains at least one field of a plurality of fields. The networking system may generate a structured data container associated with the communication platform, wherein the structured data container comprises the plurality of fields. The communication platform may receive, from a second user, an input to at least one field and may associate the input to at least one field of the plurality of fields of the structured data container. The communication platform may then present, via a graphical interface and to the first user, the input to the at least one field of the plurality of fields.
Message moderation is described herein. In an example, a message posted to a virtual space of a communication platform can be flagged for review by a reviewer (e.g., an administrator or other user permissioned to review messages). In some examples, such a reviewer can review a flagged message and determine one or more actions to be performed. Such actions can include removing the message from presentation via the communication platform, modifying presentation of the message via a user interface of the communication platform, replying to the message (e.g., to suggest taking the conversation offline or to another virtual space), disabling interaction with the message, and/or the like. Message moderation, as described herein, can streamline resolution of conversations that become out of hand and/or off topic.
H04L 51/212 - Surveillance ou traitement des messages utilisant un filtrage ou un blocage sélectif
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 40/166 - Édition, p. ex. insertion ou suppression
88.
Methods and systems for stateful workflow execution
Computing systems and methods are provided for executing steps of a workflow in a stateful and parallelizable manner. A worker computing system receives indication of an assigned step of the workflow and downloads, to its local storage, a snapshot of changes from a preceding step of the workflow from a distributed storage on a network, where the snapshot includes data indicative of the changes associated with execution of the preceding step. The worker computing system performs the assigned step using the data from the snapshot to generate a second snapshot of changes associated with execution of the assigned step and uploads the second snapshot of changes associated with the assigned step to the distributed storage.
G06F 11/10 - Détection ou correction d'erreur par introduction de redondance dans la représentation des données, p. ex. en utilisant des codes de contrôle en ajoutant des chiffres binaires ou des symboles particuliers aux données exprimées suivant un code, p. ex. contrôle de parité, exclusion des 9 ou des 11
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
89.
SELECTION OF STORAGE SERVERS BASED ON CLUSTERING BANDS
In some embodiments, a method receives a request for accessing a database and selects a band from a plurality of bands for the request based on a characteristic of the request. A band is associated with a set of characteristics. The method selects a storage server for the band and determines whether the storage server can process requests from the band. When the storage server can process requests from the band, the method causes processing of the request by the storage server to access the database. When the storage server cannot process requests from the band, a traffic limiting indication is set for the storage server to limit processing of requests for the band on the storage server.
In accordance with embodiments disclosed herein, there are provided mechanisms and methods for automating deployment of applications in a multi-tenant database environment. For example, in one embodiment, mechanisms include managing a plurality of machines operating as a machine farm within a datacenter by executing an agent provisioning script at a control hub, instructing the plurality of machines to download and instantiate a lightweight agent; pushing a plurality of URL (Uniform Resource Locator) references from the control hub to the instantiated lightweight agent on each of the plurality of machines specifying one or more applications to be provisioned and one or more dependencies for each of the applications; and loading, via the lightweight agent at each of the plurality of machines, the one or more applications and the one or more dependencies for each of the one or more applications into memory of each respective machine.
Examples include a system and computer-implemented method to receive a notification from an application programming interface (API) of creation of a just in time (JIT) grant, the JIT grant defining a request for a user to be authorized to access a cluster according to a JIT policy; determine if access to the cluster by the user is authorized according to the JIT policy; grant access to the user to the cluster when access is authorized according to the JIT policy; and send a notification to the API that access by the user to the cluster is granted.
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 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 16/13 - Structures d’accès aux fichiers, p. ex. indices distribués
G06F 21/10 - Protection de programmes ou contenus distribués, p. ex. vente ou concession de licence de matériel soumis à droit de reproduction
92.
SEAMLESS COMMUNICATION RESOURCE TRANSITION BETWEEN A GROUP-BASED COMMUNICATION SYSTEM AND AN EXTERNAL COMMUNICATION SYSTEM
Method, apparatus and computer program product for seamless communication resource transition are described herein. A user may wish to share an external communication resource within a group-based communication system. Settings may be provided allowing the user to more effectively share the external communication resource. The user may select the appropriate settings such that the external communication resource can be transmitted to the group-based communication system for display in accordance with the selected settings.
Techniques are provided for copying data from a source database to a target database in a database replication system which includes a database event mining system, an event interceptor process and an event receptor process. In one aspect, the event interceptor detects a failure in the event receptor and switches to a mode in which it rejects new database events from the database event mining system. The event interceptor can also request that the database event mining system resend the event after a specified delay. The event interceptor can also shut itself down for a specified period of time, then restart and listen for a pairing request from the event receptor. In another aspect, the event receptor can request that the database event mining system send event data from a specified system change number.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 11/20 - 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
Embodiments described herein provide a framework designed to enable personalized image generation capabilities in a pretrained text-to-image generation model. The architecture comprises two replicas of the pretrained text-to-image model—a reference UNet dedicated to extracting visual features from reference images and a base UNet for the actual image generation process. The reference UNet processes reference images to collect the features before each Self-Attention (SA) layer of the reference UNet. The base UNet's SA layers are modified to “Reference Self-Attention” (RSA) layers that allow conditioning on extra features. Using the collected reference features as input, the base UNet equipped with the RSA layers estimates the noise in the input to guide the image generation towards the reference objects.
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
97.
SYSTEMS AND METHODS FOR CONTROLLABLE VIDEO GENEATION
Embodiments described herein provide a video generation framework built on a decoupled multimodal cross-attention module to simultaneously condition the generation on both an input image and a text input. The video generation may thus be conditioned on the visual appearance of a target object reflected in the input image. In this way, zero-shot video generation may be achieved with little fine-tuning efforts.
Techniques are described herein for a method of generating a synthetic chat between a customer module and an agent module, wherein: the customer module receives a first prompt and determines a first chat response, and the agent module receives a second prompt and determines a second chat response; generating, by a summarizer module, a summary of the synthetic chat; scoring, by a scorer module, the synthetic chat by comparing the summary of the synthetic chat to the first prompt and the second prompt; adjusting, based on the score, a parameter associated with the synthetic chat.
A message batching configuration may be determined for transmitting a message to recipients. The message batching configuration may include two or more message batches, a respective recipient count for each message batch, a respective time delay between each message batch, and a performance metric for evaluating the message. The message is transmitted in accordance with the message batching configuration. The transmission of subsequent message batches is halted when it is determined that the designated performance metric fails to meet a designated performance metric threshold.
H04L 65/612 - Diffusion en flux de paquets multimédias pour la prise en charge des services de diffusion par flux unidirectionnel, p. ex. radio sur Internet pour monodiffusion [unicast]
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
100.
DATABASE SYSTEMS WITH AUTOMATED STRUCTURAL METADATA ASSIGNMENT
Database systems and methods are provided for assigning structural metadata to records and creating automations using the structural metadata. One method of assigning structural metadata to a record associated with a conversation involves obtaining a plurality of utterances associated with the conversation, identifying, from among the plurality of utterances, a representative utterance for semantic content of the conversation, assigning the conversation to a group of semantically similar conversations based on the representative utterance, and automatically updating the record associated with the conversation at a database system to include metadata identifying the group of semantically similar conversations.
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
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
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 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
