Disclosed herein are systems and techniques for centralized data retention and deletion. Data can be ingested from multiple external data sources and saved internally for use to process data modification (e.g., deletion) requests via a data processing pipeline, which may apply eligibility checks and modification logic to determine the appropriate modifications to the relevant data items to comply with the data modification request. Various user interfaces may be generated to provide a user with oversight of the data processing pipeline and the data modifications. The user may review and trigger the modification of data stored at the external data sources and/or internally.
A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
G06F 30/00 - Conception assistée par ordinateur [CAO]
G06F 111/20 - CAO de configuration, p. ex. conception par assemblage ou positionnement de modules sélectionnés à partir de bibliothèques de modules préconçus
G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques
3.
ENHANCED PROCESSING OF TIME SERIES DATA VIA PARALLELIZATION OF INSTRUCTIONS
Systems and methods are provided for enhanced processing of time series data via parallelization of instructions. An example method includes receiving a query indicating time series datasets and operations to be performed on the time series datasets. Nodes associated with the query are identified, with each node associated with a time series dataset. Nodes associated with operations to be performed are generated. The nodes are assembled into query tree, with parent nodes of the query tree indicating operations that are to be applied to children nodes. Instructions for processing the query tree are generated. At least a subset of the instructions is provided to one or more compute systems for processing in parallel. Results are received, and presented in a user interface.
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
4.
CONTINUOUS BUILDS OF DERIVED DATASETS IN RESPONSE TO OTHER DATASET UPDATES
A method comprises creating and storing a dependency graph representing at least one derived dataset and one or more raw datasets or intermediate derived datasets on which the at least one derived dataset depends; reading configuration data specifying one or more periods; detecting, at a first unscheduled time, a first update to a first dataset among the one or more raw datasets or intermediate derived datasets, the first dataset being a beginning of a series of derived datasets ending with a final dataset; initiating a first transformation of the first dataset to generate a first intermediate derived dataset; detecting, at a second unscheduled time, a second update to the first dataset; determining that a throttle condition specified in the configuration data is not met; initiating, when the final dataset is not yet built in response to the first update, a second transformation of the first dataset.
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
5.
GENERALIZABLE ENTITY RESOLUTION BASED ON ONTOLOGY STRUCTURES
A system for managing entity resolution processes is disclosed. The system is programmed to determine whether incoming records correspond to known entities within an ontology framework. The system is also programmed to manage a graphical user interface that allows customizing entity resolution operations and providing feedback on the determination results. The system is further programmed to use the provided feedback to improve machine learning for the entity resolution processes.
An asset owner may be interested in determining risks associated with physical assets, such as to damage or other loss associated with the assets. Accurately identifying such risks may be useful in determining preventative actions that may be taken to reduce data or loss associated with the assets. The systems and methods described herein generally relate to automating a process of obtaining data regarding physical assets, such as from sensors associated with the assets, determining one or more risk indicators associated with the assets, and initiating some actions based on the determined risk indicators.
A system for automated processing and analysis of audio files for large data sets in a cloud environment. A unified analytic environment can integrate audio machine learning models for processing and analysis with a knowledge management system, including graph presentations of tracked entities, linked to audio files and/or associated translations and transcripts. Entities within such data can be searched or filtered and proposed for tracking, or identified as tracked objects. These features can allow triage and prioritization of audio files for analysis. User interfaces can facilitate feedback on transcription and translation outputs, thereby improving present outputs and future inputs and outputs. Entities speaking or referred to can be found, tagged, and distinguished in audio files (e.g., using speaker identification in audio files, text searching in transcripts, etc.) Users can provide feedback and input on various aspects of a system, to enhance or adjust initial automated or other machine learning outputs.
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
G10L 17/04 - Entraînement, enrôlement ou construction de modèle
G10L 21/028 - Séparation du signal de voix utilisant les propriétés des sources sonores
8.
RESOURCE DEPENDENCY SYSTEM AND GRAPHICAL USER INTERFACE
A resource dependency system displays two dynamically interactive interfaces in a resource dependency user interface, a hierarchical resource repository and a dependency graph user interface. User interactions on each interface can dynamically update either interface. For example, a selection of a particular resource in the dependency graph user interface causes the system to update the dependency graph user interface to indicate the selection and also updates the hierarchical resource repository to navigate to the appropriate folder corresponding to the stored location of the selected resource. In another example, a selection of a particular resource in the hierarchical resource repository causes the system to update the hierarchical resource repository to indicate the selection and also updates the dependency graph user interface to display an updated graph, indicate the selection and, in some embodiments, focus on the selected resource by zooming into a portion of the graph.
A method of managing decoupled front-end and back-end processes is disclosed. The method comprises receiving a first result of user interaction with a first front-end interface; determining that the first result represents a validation of a data item entered via the first front-end interface; mapping the data item in a validated form to a back-end object; causing storing the data item in a database system in association with the back-end object; receiving a second result of user interaction with a second front-end interface; determining that the second result represents a state transition corresponding to executing a query entered via the second front-end interface against the database system; mapping the state transition to a set of back-end commands; causing executing the set of back-end commands over the database system of back-end objects.
A computer system provides transaction-level data retention policy inheritance. The system may perform operations including storing a first dataset comprising a plurality of transactions, each of the plurality of transactions comprising one or more data items; receiving a first transaction to the first dataset, the first transaction comprising one or more data items; determining a first retention policy for the first transaction; and storing the first retention policy with the first transaction. The system may further perform operations including calculating a deletion date for the first transaction based on the first retention policy; and storing the deletion date with the first transaction in the first dataset.
Computer-implemented systems and methods including language models for explaining and resolving code errors. A computer-implemented method may include: receiving or accessing a log comprising an error message, the error message indicating an error in code; determining the error message from the log; determining a context associated with the error; generating a prompt for a large language model (“LLM”), the prompt comprising at least: the error message, and the context associated with the error; transmitting the prompt to the LLM; and receiving an output from the LLM in response to the prompt, the output comprising at least: an explanation of the error message, and a suggested fix for the error.
Systems are provided for managing access to a log of dataset that is generated when the dataset is accessed. A system stores, with respect to each of a log producer and a log accessor, an encrypted symmetric key for dataset that is encrypted using a corresponding public key. The system returns the encrypted symmetric key for the log producer, such that the log producer can decrypt the dataset that is encrypted using the symmetric key. A log of the dataset is generated when the log producer accesses the dataset.
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
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
Systems, methods, and non-transitory computer readable media are provided for using linked documents. A system may receive, from a computing device, a request for a document. Content of the document may be defined based on state information and stateless information. A system may determine a local replica of the document in a local database. The local replica of the document may be linked to a primary replica of the document. The local replica of the document may include a snapshot of the primary replica of the document. The primary replica of the document may be stored in a remote database which may be accessible through a remote server. The system may subscribe to the primary replica of the document through the remote server, and may provide access to the document to the computing device based at least in part on the subscription to the primary replica of the document.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
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 17/14 - Transformations de Fourier, de Walsh ou transformations d'espace analogues
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
14.
SYSTEMS AND METHODS FOR CREATING AND MANAGING A DATA INTEGRATION WORKSPACE
Systems and methods are provided for creating and managing a data integration workspace. The workspace may comprise one or more views of data (or datasets) stored in or accessible by the system. Models may be generated and updated based on the plurality of datasets and presented via a graphical user interface. Feedback received via a graphical user interface presenting a model may be used to annotate an underlying dataset associated with the model. Responsive to a modification of the underlying dataset or the rules for using the underlying dataset to generate the model, other related datasets and/or models may be automatically updated accordingly. Templates associated with one or more types of users may be defined. Each template may comprise one or more specific models related to a specific type of user.
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 16/21 - Conception, administration ou maintenance des bases de données
Computing systems methods, and non-transitory storage media are provided for receiving a first representation of an unstructured data entity. The first representation includes an indication of a detection. The unstructured data entity is part of a corpus. Next, second representations of the unstructured data entity are received and resolved according to a consensus. Next, any discrepancies between the first representation and the resolved second representations are determined. The any discrepancies include any difference in an existence or an absence of the detection, in a relative position of the detection, or in a type or a classification of the detection. Next, feedback regarding the any discrepancy is received. Next, the first representation is selectively modified, or selectively prompted to be modified, based on the any discrepancy and the feedback.
A user interface for working through workflows can include a dual-region approach. The first display region can display a series of workflows that an assigned worker (“assignee”) may have. Each of the workflows can have one or more tasks associated therewith. Each workflow and/or task can be associated with one or more triggers that initiate the assignment of that workflow and/or task. In response to selection of a workflow or task, the second display region can display information associated with the workflow or task.
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
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.
Systems and methods are provided for obtaining a media, the media including an image, audio, video, or combination thereof. An input may be received regarding one or more features or frames of the media to be maintained in or removed from the media. One or more criteria of a lossy compression technique may be inferred based on the received input, using a machine learning model, based on the received input. The inferred criteria of the lossy compression technique may be applied to the media.
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
G10L 19/00 - Techniques d'analyse ou de synthèse de la parole ou des signaux audio pour la réduction de la redondance, p. ex. dans les vocodeursCodage ou décodage de la parole ou des signaux audio utilisant les modèles source-filtre ou l’analyse psychoacoustique
A method may comprise receiving a query for performing one or more computational operations on one or more multi-dimensional data sets representing multi-dimensional time series data collected in real-time from one or more sensors associated with one or more technical systems. The method may also comprise identifying the location of the one or more multi-dimensional time series data sets in one or more databases, retrieving the one or more multi-dimensional time series data sets from the identified one or more databases, and performing the one or more computational operations on the retrieved one or more multi-dimensional time series data sets. The method may also comprise generating output based on the result of the one or more computational operations indicative of one or more states of the one or more technical systems with respect to time.
Disclosed herein are methods and systems for interacting with data in a data repository. After automatically populating one or more display elements with data items from a first dataset, one or more unpopulated display elements can be identified that can be populated with one or more additional data items from another dataset in a data repository. A second dataset that is joined to the first dataset can be identified based on template definitions associated with the display elements. The second dataset can include the one or more additional data items corresponding to the one or more unpopulated display elements. The one or more unpopulated display elements can be populated with the one or more additional data items retrieved from the second dataset to update the graphical user interface.
Systems and methods provide an interface for accessing a data analysis workbook through which data is accessed and manipulated using a plurality of programming languages and application programming interfaces (APIs). Input data on which one or more data transformations are to be performed within the data analysis workbook is accessed, wherein the input data corresponds to a first object representation of a dataset, and wherein the one or more data transformations require the dataset to be a different, second object representation of the dataset. The second object representation of the dataset can be extracted from the first object representation of the dataset through a first language delegate that manages data associated with the first object representation. The one or more data transformations can be applied to the extracted second object representation of the dataset through a different, second language delegate that manages data associated with the second object representation.
Systems and methods are provided for generating and storing data snippets. A data file can be obtained from a data source through a plug-in interface. The data file can be played to a user through an application running on a computing device. An indication can be received from the user, through the application, to tag an entity depicted in the data file during playback of the data file. A snippet of the data file can be stored, wherein the snippet is a portion of the data file corresponding to the entity tagged by the user.
H04N 21/84 - Génération ou traitement de données de description, p. ex. descripteurs de contenu
G06F 16/48 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/483 - 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
H04N 21/845 - Structuration du contenu, p. ex. décomposition du contenu en segments temporels
23.
SYSTEM AND METHOD FOR SELECTING MACHINE LEARNING TRAINING DATA
Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.
Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
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 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
A collaborative planning system facilitates sharing of critical plans (e.g., a military mission plan) within an organization and managing authorizations of the plans from reviewers at multiple levels within the organization. Once the plans are approved, a data object representative of the plans is created and stored in an ontology of data objects (with objects of various types and associations between related data objects) so that the plans may be identified as associated with related data objects via searches of the data objects in the ontology.
A method of handling a dataset for a build pipeline comprises receiving, from a build service, a query for information related to a dataset being in a first format not managed by the build service for a build pipeline; providing, to the build service, first information related to change in the dataset since a last build performed by the build service in a second format managed by the build service, the first information indicating a version of the dataset used in the last build; transmitting, to the build service, a request for information regarding a new build performed based on the first information; receiving, from the build service, second information regarding the dataset generated from the new build in the second format; storing a new version of the dataset in the first format based on the second information.
A system architecture for linking one or more derived objects to existing data objects in a data structure can be organized in a variety of forms. A method for establishing the architecture may include linking first and second data objects. linking first and second data objects. The first and second data objects may be associated with corresponding first and second pluralities of properties. The method may include receiving a first user limitation associated with at least one of the first or second pluralities of properties and receiving a second user limitation associated with at least one of the first or second pluralities of properties. The method can include deriving a conclusion object comprising a third plurality of properties comprising a subset of one or more of the first or second pluralities of properties and linking the conclusion object to the first and second data objects.
Systems and methods for a central user interface for accessing, and upgrading of, dataset integrations. An example method includes accessing, by a system of one or more processors, datasets stored via respective outside devices or systems. The datasets are integrated by the system according to respective integration tiers, with each integration tier being associated with, at least, a respective subset of search functionality enabled via the system. An interactive user interface is presented via a user device, with the interactive user interface presenting summary information. The interactive user interface further enables adjustment of a particular dataset from a first integration tier to a second integration tier.
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/26 - Exploration de données visuellesNavigation dans des données structurées
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
The present disclosure relates to methods and systems for querying data in a data repository. According to a first aspect, this disclosure describes a method of querying a database, comprising: receiving, at a computing device, a plurality of keywords; determining, by the computer device, a plurality of datasets relating to the keywords; identifying, by the computer device, metadata for the plurality of datasets indicating a relationship between the datasets by examining an ontology associated with the datasets; providing, by the computer device, one or more suggested database queries in natural language form, the one or more suggested database queries constructed based on the plurality of keywords and the metadata; receiving, by the computing device, a selection of the one or more suggested database queries; and constructing, by the computer device, an object view for the plurality of datasets based on the selected query and the metadata.
Computer-implemented systems and methods are disclosed, including systems and methods for automatically solving problems. A computer-implemented method may include: by an agent service configured to interact with an LLM to complete a run: providing an LLM with access to a state machine, executing an initial state of the state machine with the LLM, determining a subsequent state of the state machine based on at least an initial LLM output, and executing the subsequent state of the state machine.
Computer-implemented systems and methods are disclosed, including systems and methods for automatically solving computational tasks or problems. A computer-implemented method may include: providing an agent service that utilizes a plurality of agents to process one or more tasks; receiving, by a first agent, a request to handle a first task; obtaining, by the first agent, a first accessory to handle the first task; assigning, by the first agent, at least a portion of the first task to a second agent; sharing, by the first agent, the first accessory to the second agent; and processing, by the second agent, at least the portion of the first task using the first accessory to generate a processing result.
A computer system may be configured to: execute a first query associated with a first panel; display the first panel in a user interface based on first display settings of the first panel, the first panel displaying at least a portion of the result of the first query, the result of the first query associated with a variable; execute a second query associated with a second panel, wherein the second query refers to the variable associated with the first query; display the second panel in the user interface based on second display settings of the second panel, the second panel displaying at least a portion of the result of the second query; and in response to user input changing the displayed result in the first panel: re-execute the second query; and update the display of the second panel in the user interface based on results of the re-executed second query.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 40/14 - Documents en configuration arborescente
A system is configured to provide a dashboard creation system. Panels associated with queries for retrieving information from a database are shown in a user interface. Various other user interfaces show query code, panel display settings, function code, dependencies, etc. Queries in a first query format access a data source. Queries in a second query format access a cache database that is synchronized with the data source.
G06F 40/143 - Balisage, p. ex. utilisation du langage SGML ou de définitions de type de document
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 16/172 - Mise en cache, pré-extraction ou accumulation de fichiers
G06F 16/178 - Techniques de synchronisation des fichiers dans les systèmes de fichiers
Methods, apparatuses and computer programs for manipulating data structures are provided. A method includes: receiving an indication of a target outcome, where the target outcome defines a transformation of a first dataset; providing to a first artificial intelligence model one or more requests to generate candidate functions; receiving, in response to the one or more requests, a plurality of distinct candidate functions from the first artificial intelligence model; providing, to a second artificial intelligence model, a request to generate the transformation on a first subset; receiving, from the second artificial intelligence model, an AI transformation of the first subset; executing each of the plurality of candidate functions on the first subset to generate a plurality of test; validating one or more of the candidate functions; and executing one of the validated candidate functions on the first dataset to achieve the transformation of the first dataset.
A system architecture can be used to facilitate communication among applications that are native and/or non-native to an application environment. The system architecture can include a first application environment executed on a client-side computing device. The first application environment can execute software applications that are native thereto. The first application environment can further execute software applications that are native thereto, but which software applications themselves comprise second application environments of types different from the first application environment, and which software applications can therefore execute additional software applications that are non-native to the first application environment. The first application environment can further execute a computation engine that is configured to store and execute instructions received from the first software application, the second software application, or both.
Methods and systems for structuring, storing and displaying time series data in a user interface. One system includes processors executing instructions to determine, from time series data from a first sensor, a first subset of time series data for the first batch from the first start time and the first end time, determine, from the time series data from the first sensor, a second subset of time series data for the second batch from the second start time and the second end time, generate a time series user interface comprising a chart, the chart including a first plot for the first subset of time series data and a second plot for the second subset of time series data, the first plot being aligned to the second plot, and cause presentation of the time series user interface.
G06F 11/32 - Surveillance du fonctionnement avec indication visuelle du fonctionnement de la machine
G06F 16/36 - Création d’outils sémantiques, p. ex. ontologie ou thésaurus
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
Systems and methods for dynamically generating application programming interfaces and managing functions associated with a data object type. In an aspect, the system accesses an object definition for a type of data object. The system generates an application programming interface associated with the type of data object, based at least partly on the object definition. The system determines a change to the object definition for the type of data object and updates the application programming interface based at least partly on the change to the object definition.
A system may use a large language model (“LLM”) to generate a data pipeline. The system can receive a natural language query and a selection of a plurality of data sets for generating a data pipeline and generate a prompt comprising at least: the natural language query, indications of the plurality of data sets, an indication of a format of a first computer language, and an indication of available data transformations. The system can transmit the prompt to an LLM and receive, from the LLM, a response to the prompt in the format of the first computer language. The system can parse the response in the first computer language to identify at least an indication of one or more recommended data transformations. The system can generate, based on the indication of the one or more recommended data transformations, the data pipeline using a second computer language.
Devices, systems, and methods for generating summaries are disclosed. In some implementations, a method can include receiving a plurality of event logs, at least one event log of the plurality of event logs including unstructured data and a corresponding event time. In addition, the method can include generating a series of event logs according to event times of the plurality of event logs. The method can include receiving a time window of interest corresponding to one or more event logs in the generated series of event logs. Moreover, the method can include generating a text summary by applying a language model to unstructured data corresponding to the one or more event logs in the time window of interest. Also, the method can include transmitting the text summary to a computing device.
At least some embodiments of the present disclosure are related to methods and systems for evaluating, generating, and/or prototyping data pipelines. In certain embodiments, a system is configured to perform operations include: receiving an input dataset, the input dataset including a data schema; generating a first prompt based on the input dataset and a first prompt structure having one or more text strings and one or more blanks; providing the first prompt to a language model; receiving a use case generated by the language model for the input dataset, the use case including a description of how to use the input dataset; generating a data pipeline based on the use case; and applying the data pipeline to the input dataset to generate an output dataset.
A method of determining and displaying metadata that represents provenance of columns in a data store comprises receiving query data expressed in a human-readable language and describing one or more transformations of data tables of a distributed database system or columns of the data tables; parsing the query data to create a data structure for unresolved transforms in which the data tables are not matched with the columns; based in part upon table schema metadata describing the columns of the data tables, creating an additional data structure for resolved transforms, the additional data structure matching the data tables with the columns and specifying inputs and outputs of each transformation of the one or more transformations; based on information in the additional data structure, creating and causing display of a visual graph of the columns of the data tables and relationships between the columns, relating to the one or more transformations.
G06F 16/26 - Exploration de données visuellesNavigation dans des données structurées
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de 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
Disclosed herein are systems and techniques for centralized data retention and deletion. Data can be ingested from multiple external data sources and saved internally for use to process data modification (e.g., deletion) requests via a data processing pipeline, which may apply eligibility checks and modification logic to determine the appropriate modifications to the relevant data items to comply with the data modification request. Various user interfaces may be generated to provide a user with oversight of the data processing pipeline and the data modifications. The user may review and trigger the modification of data stored at the external data sources and/or internally.
An example method of determining geolocations of objects based on information retrieved from heterogeneous data sources comprises: receiving, from a first data source associated with an object by an ontology-defined relationship, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the object; receiving, from a second data source associated with an object by an ontology-defined relationship, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the object and a corresponding time identifier.
G06F 16/338 - Présentation des résultats des requêtes
G06F 16/387 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G06N 5/025 - Extraction de règles à partir de données
Systems and methods for data hydration are provided. In some examples, a method includes accessing a compiler. In some examples, the compiler is associated with a source graph, a domain graph, and a mapping profile. In some examples, the domain graph includes one or more domain data schemas. In some examples, the method further includes receiving a source dataset from a source system, and applying the compiler to the source dataset from the source system to generate a domain dataset. In some examples, the domain dataset uses at least one of the one or more domain data schemas. In some examples, the method is performed using one or more processors.
Computer-implemented systems and methods are disclosed that query collections of documents. Disclosed embodiments may include receiving, via a user interface, a first search query comprising a text string. Disclosed embodiments may include, responsive to receiving the first search query, initializing a first query object based on the text string. Further, disclosed embodiments may include translating the first query object to match the formatting of a search engine, the translated first query object capable of searching a plurality of collections of documents. Disclosed embodiments may also include receiving aggregated query results from a search engine based on the translated first query object. Some disclosed embodiments may include reformatting the aggregated query results based on respective configuration files of the collections. Additionally, disclosed embodiments may include rendering a graphical user interface that facilitates user interaction with the reformatted aggregate query results.
An apparatus, computer-implemented method and computer program are disclosed for synchronising dataset updates. For example, the method may comprise providing a first code branch associated with a plurality of code sets which, when executed, produce respective time-series datasets for provision to a downstream process linked to the first code branch. The method may also comprise generating a second code branch, based on the first code branch, the second code branch executing the plurality of code sets as part of an updating process and, if successful, storing respective time-series datasets to respective memory locations associated with the second code branch. Another part of the method may comprise determining if all code sets executed by the second code branch have successfully committed. Responsive to a positive determination, one or more pointers, e.g. all pointers, associated with the first code branch may be updated to point to the respective memory locations associated with the second code branch in order that the respective successfully-committed time-series datasets are provided to the downstream process.
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 system for managing a web application is disclosed. The system is programmed to enable graphically building a web application having one webpage with multiple views, where a view can have multiple sections and can contain a section from another view. The web application includes a hierarchical structure of nodes respectfully for generating the multiple views. Each node can be accessed separately and each node can reference certain other nodes.
Computing systems methods, and non-transitory storage media are provided for receiving a monitoring request. The monitoring request includes one or more entities or attributes to be monitored, one or more rules to be evaluated with respect to the entities or attributes, and one or more downstream actions to be selectively triggered based on the evaluation. Next, data regarding the entities or the attributes is obtained. Next, a log is generated. The log includes changes or updates, relative to a previous iteration, of the entities or the attributes. The changes or updates correspond to the rules. Next, the changes or the updates are evaluated against the one or more rules and based on the log. Next, one or more actions are selectively implemented based on the evaluation of the changes or the updates.
A computing system and methods are provided for georeferencing stabilization. An exemplary method includes: obtaining a video stream capturing an area from a camera of a drone, where the video stream includes a plurality of frames, each including a field of view of the image capturing device and metadata of the image capturing device when the frame is captured; constructing a geographic (geo) lattice for the field of view in each of the plurality of frames, the geo lattice comprises a plurality of points, each being associated with raw coordinates determined based on the corresponding metadata; and building a lattice map with stabilized geo coordinates by (1) aligning the frames, (2) averaging the raw geo coordinates for given intersection points, and (3) building the lattice map based on the averaged geo coordinates of the intersection points.
H04N 23/68 - Commande des caméras ou des modules de caméras pour une prise de vue stable de la scène, p. ex. en compensant les vibrations du boîtier de l'appareil photo
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
G06T 7/35 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images utilisant des procédés statistiques
A computing system generates user interface data renderable to display an interactive graphical user interface including a cell-based grid having a first axis and a second axis. The first axis corresponds to one or more assets. The second axis corresponds to one or more time periods. The cell-based grid comprises a plurality of cells indicating values of the one or more assets for the one or more time periods. The interactive graphical user interface displays information relating to the value indicated in the selected cell responsive to a user selection.
Systems and methods are disclosed herein for reducing a risk of associating with a client that may engage in illegal activity. A system accesses data associated with an entity for a given context, applies a plurality of AI models to the data based on the context to generate a plurality of AI assessments. Data for showing risk factors, assessments of the risk factors, and data for evaluating risk factors can be transmitted for rendering in a user interface in a display device. Analyst feedback can be received and used to update the AI models.
Various systems and methods are provided that display various geographic maps and depth graphs in an interactive user interface in substantially real-time in response to input from a user in order to determine information related to measured data points, depth levels, and geological layers and provide the determined information to the user in the interactive user interface. For example, a computing device may be configured to retrieve data from one or more databases and generate one or more interactive user interfaces. The one or more interactive user interfaces may display the retrieved data in a geographic map, a heat map, a cross-plot graph, or one or more depth graphs. The user interface may be interactive in that a user may manipulate any of the graphs to identify trends or current or future issues.
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
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 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
G06F 16/29 - Bases de données d’informations géographiques
G06T 11/20 - Traçage à partir d'éléments de base, p. ex. de lignes ou de cercles
A system is described for controlling access to resources using an object model. Users can specify use cases for accessing resources. The user may be granted access if the user satisfies qualifications required for accessing the resource, selected a use case permissible for accessing the resource, and satisfies qualifications required for the use case. Use cases, qualifications, resources, and/or links between them can be implemented using an object model. The system can be used in addition to authentication and authorization.
Computing systems methods, and non-transitory storage media are provided for receiving a first representation of an unstructured data entity. The first representation includes an indication of a detection. The unstructured data entity is part of a corpus. Next, second representations of the unstructured data entity are received and resolved according to a consensus. Next, any discrepancies between the first representation and the resolved second representations are determined. The any discrepancies include any difference in an existence or an absence of the detection, in a relative position of the detection, or in a type or a classification of the detection. Next, feedback regarding the any discrepancy is received. Next, the first representation is selectively modified, or selectively prompted to be modified, based on the any discrepancy and the feedback.
A system for managing firewall rules between different services. In certain instances, the method includes receiving a discovery graph comprising a plurality of services and at least one application programming interface (API) dependency, wherein the plurality of services comprises a first service and a second service. In some instances, the method further includes determining whether the second service is permitted to receive an initial communication from the first service based upon the at least one API dependency included in the discovery graph. And, in response to determining the second service is permitted to receive the initial communication from the first service, the method can include establishing a first rule for a firewall between the first service and the second service, the first rule allowing the second service to receive the initial communication from the first service.
A method of persisting results of executing search queries across multiple data sources comprises obtaining a first data object as a result of executing a first search query against one or more data sources of a plurality of heterogeneous data sources; receiving a first request to store the first data object in a repository, a specific data source of the one or more data sources and the repository having different data models; determining that a repository data object with which the first data object resolves does not exist; generating a specific repository data object as a stub data object for the first data object, comprising: creating a unique identifier based on one or more data object properties that uniquely identify the first data object; and utilizing the unique identifier in the repository as a key or index value for the specific repository data object; storing the specific repository data object.
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 16/248 - Présentation des résultats de requêtes
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
In some examples, systems and methods for managing cloud resources (e.g., distributed resources) are provided. For example, a method includes: receiving a request to create a data bucket from a client application, the request including a bucket template; generating a cryptographic key for the data bucket; generating the data bucket in a cloud platform based at least in part on the bucket template; associating the cryptographic key to the generated data bucket; generating metadata associated with the generated data bucket; and providing the metadata associated with the generated data bucket to the client application.
Systems and methods for georegistration are provided. An example method includes receiving a video stream including a plurality of video frames collected by an image sensor, presenting the video stream via a video player, and receiving user input associated with a first video frame of the plurality of video frames and a reference image. In some examples, the first video frame includes incomplete telemetry data. In some examples, the method further includes determining one or more coordinates associated with the first video frame based on user input associated with the first video frame and the reference image, determining the incomplete telemetry data associated with the first video frame based on the one or more determined coordinates, and generating a georegistration transform based on the determined telemetry data and the reference image.
G06V 10/24 - Alignement, centrage, détection de l’orientation ou correction de l’image
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 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images utilisant des procédés basés sur les caractéristiques
Systems and methods for georegistration are provided. An example method includes receiving a video stream including a plurality of video frames collected by an image sensor, presenting the video stream via a video player, and receiving user input associated with a first video frame of the plurality of video frames and a reference image. In some examples, the first video frame includes incomplete telemetry data. In some examples, the method further includes determining one or more coordinates associated with the first video frame based on user input associated with the first video frame and the reference image, determining the incomplete telemetry data associated with the first video frame based on the one or more determined coordinates, and generating a georegistration transform based on the determined telemetry data and the reference image.
G06T 3/14 - Transformations pour le recalage d’images, p. ex. ajustement ou mappage pour l’alignement d’images
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images utilisant des procédés basés sur les caractéristiques
63.
OBJECT-CENTRIC DATA ANALYSIS SYSTEM AND GRAPHICAL USER INTERFACE
Systems and methods for analyzing data stored using a data model. The system can receive a user selection of a first object type indicating to perform filtering operations on a first set of data objects, generate a list of object types linked to the first object type based on an ontology, receives a user selection of a second object type, generate a list of properties of the second object type based on an ontology, receive a user selection of a first property from the list of properties, perform a data query determining values associated with the first property, receive a user selection of a first value, and displays information of a subset of data objects being a portion of the first set of data objects that are linked to data objects in the second set of data objects that have a first property value of the first value.
Systems and methods for data propagation and mapping are provided. In an aspect, one or more data entries storing changed information in a first database using a first storage format are identified. The identified data entries are received by the data propagation and mapping system. The received data entries may be filtered to generate a subset of filtered data entries. The filtered data entries are transmitted to a mapping pipeline configured to map a data entry stored in the first storage format to a data entry stored in a second storage format. The mapped data entries are transmitted to a recipient second database storing data entries using the second storage format.
A computer system can receive one or more edits to be made to a canonical dataset and can temporarily store the one or more edits in a buffer. In response to receipt of a query of the canonical dataset, the computer system can rewrite the query to read from the canonical dataset and the buffer; combine the one or more edits from the buffer with the canonical dataset to form a combined dataset based on resolution policies to avoid conflicts between data; rewrite the query to execute on the combined dataset in lieu of the canonical dataset to optimize query performance; and execute the query on the combined dataset.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
A pipeline task verification method and system is disclosed, and may use one or more processors. The method may comprise providing a data processing pipeline specification, wherein the data processing pipeline specification defines a plurality of data elements of a data processing pipeline. The method may further comprise identifying from the data processing pipeline specification one or more tasks defining a relationship between a first data element and a second data element. The method may further comprise receiving for a given task one or more data processing elements intended to receive the first data element and to produce the second data element. The method may further comprise verifying that the received one or more data processing elements receive the first data element and produce the second data element according to the defined relationship.
Computing systems methods, and non-transitory storage media are provided for obtaining images, extracting layers from each of the images, extracting segments from each of the layers, generating a compressed version of the segments by storing a single copy of each segment and metadata to reconstruct the layers from the segments and the images from the layers, and simulating a reconstruction of the image from the compressed version.
A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.
An example method of enforcing granular access policy for embedded artifacts comprises: detecting an association of an embedded artifact with a resource container; associating the embedded artifact with at least a subset of an access control policy associated with the resource container; and responsive to receiving an access request to access the embedded artifact, applying the access control policy associated with the resource container for determining whether the access request is grantable.
A computer-implemented method enforces data security constraints in a data pipeline. The data pipeline takes one or more source datasets as input and performs one or more data transformations on them. The method includes using data defining one or more data security constraints to configure the data pipeline to perform a data transformation on a restricted subset of entries of the source datasets. The restriction is defined by the data defining one or more data security constraints. The method further includes performing the data transformation according to the configuration to produce one or more transformed datasets. The method further includes using the data defining one or more data security constraints to perform a verification on one or more of the transformed datasets to ensure that entries in the one or more of the transformed datasets are restricted as defined by the one or more data security constraints.
A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.
H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
An artificial intelligence system can be used to respond to natural language inputs (e.g., user submitted inputs) where the response involves a data processing workflow involving language models. The artificial intelligence system can use “profiles” associated with a user, role, cohort, and/or organization to bring additional operational context into user interactions within the artificial intelligence system.
Computer-implemented systems and methods are disclosed, including for evaluation of computer-based models in a management framework. A computer-implemented method may include, for example, receiving one or more inputs including requesting to add an evaluation configuration to a defined modeling objective, specifying at least a first evaluation data set for the evaluation configuration, specifying at least a first evaluation library for the evaluation configuration, and specifying at least a first subset definition for the evaluation configuration. A computer-implemented method may in response to the one or more user inputs include: creating, storing, and/or updating the evaluation configuration. A computer-implemented method may include evaluating, based on the evaluation configuration, the one or more models associated with the defined modeling objective.
One or more virtual machines are launched at an application platform. At each of the one or more virtual machines, a machine learning model execution environment is instantiated for an instance of a machine learning model. A respective instance of the machine learning model is loaded to each machine learning model execution environment. Each loaded instance of the machine learning model is associated with an application programming interface (API) endpoint which can receive input data for the loaded instance of the machine learning model from a client device and return output data produced by the loaded instance of the machine learning model based on the input data.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
Systems and methods are provided for data migration. The system may comprise one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to migrate at least one first table of a first database schema to at least one second table of a second database schema, determine a query for modifying the first table during the migration, modify the second table based at least in part on the query, and update a mutation table to describe the modification, wherein the mutation table at least describes the modification.
This disclosure relates to a system and method for data analysis. According to a first aspect, there is described a method, the method being performed using one or more processors, comprising: receiving one or more user inputs indicative of one or more relationships between data in a plurality of datasets; determining, based on the one or more user inputs, at least one object view for visualizing the data in the plurality of datasets; generating, based on the one or more user inputs, metadata comprising: an object graph indicative of the one or more relationships between two or more of the plurality of datasets; and information identifying the at least one object view; and in response to a query relating to the plurality of datasets, using the metadata to determine how response data responding to the query should be provided.
G06F 16/2458 - Types spéciaux de requêtes, p. ex. requêtes statistiques, requêtes floues ou requêtes distribuées
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, methods, and non-transitory computer readable media are provided for recursively searching a plurality of workspaces of the system for linked data associated with the seed data, initiating an endpoint process for each the seed data and the linked data, and, upon completion of the search, delete the seed data and the linked data identified based at least in part on the endpoint process. The process may be automatically repeated at a predetermined time interval to identify and remove future data that is stored in the plurality of datasets.
A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.
A system may receive a natural language query. A system may receive indications of one or more data object types, wherein each of the one or more data object types is associated with a respective one or more properties. A system may receive references to one or more data sets, wherein the one or more data sets are each associated with at least a respective data object type. A system may transmit a prompt to a large language model (“LLM”), the prompt comprising at least: the natural language query, the indications of the one or more data object types, and the references to the one or more data sets. A system may receive, from the LLM, a response to the prompt, wherein the response includes indications of: at least a first reference to a first data set and a query to be applied to the first data set.
Computer-implemented systems and methods are disclosed, including for integration and management of computer-based models in a model management. A computer-implemented method may include, for example, receiving one or more inputs including requesting to add a first model to a defined modeling objective, specifying a first model location, and/or providing a first model adapter configuration. In response to the one or more user inputs, the method may further include storing or providing access to information associated with the first model, associating the first model with a defined modeling objective, and/or implementing the first model adapter configuration to provide communication with the first model.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
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
81.
SECURING LARGE LANGUAGE MODEL OUTPUT BY PROPAGATING PERMISSIONS
Computer-implemented systems and methods are disclosed, including for determining permissions for nondeterministic model output. A computer-implemented method may include, for example, receiving one or more user inputs including a first user input providing at least a portion of a first prompt for a query for a first nondeterministic model. A computer-implemented method may in response to receiving the one or more user inputs include: executing the query, by the first nondeterministic model, to generate an output, determining a first one or more data inputs used by the first nondeterministic model during execution of the query, determining a first set of permissions associated with the first one or more data inputs; and applying a second set of permissions to at least a first portion of the output based on the first set of permissions.
The disclosure is directed to methods and systems for improving interactions with a Large Language Model (LLM). An artificial intelligence system (AIS) can receive user inputs via a graphical user interface indicating a task to be performed by the LLM, one or more tools which may be accessed by the AIS in response to tool calls from the LLM, and an output schema for structuring a format of a response from the LLM. The AIS can generate a prompt for the LLM based on the user input. The prompt can include indications of the one or more tools, one or more example tool operations, the task to be performed, and an indication of the output schema. The AIS can include a debugging application or module enabling rich debugging of language model interactions in a single view.
Systems and methods for correlating data (e.g., sensor data) with entities and/or tracking entities are provided. In some embodiments, a method includes displaying one or more indications of one or more entities, receiving a first input to select the target entity from the one or more entities, in response to receiving the first input, displaying an interactive element for associating one or more sensors to the target entity, displaying the one or more sensors that are active, receiving a second input associated with the interactive element, in response to receiving the second input, creating a link between the target entity and at least one sensor of the one or more sensors, and updating one or more entity properties of the target entity based on sensor data of the at least one sensor and the created link.
G01S 13/66 - Systèmes radar de poursuiteSystèmes analogues
G01S 15/06 - Systèmes déterminant les données relatives à la position d'une cible
G01S 17/06 - Systèmes déterminant les données relatives à la position d'une cible
G01S 19/03 - Éléments coopérantsInteraction ou communication entre les différents éléments coopérants ou entre les éléments coopérants et les récepteurs
84.
SYSTEMS AND METHODS FOR DYNAMIC GEOTEMPORAL DATA SCHEMAS
Systems and methods for managing and/or using observation schemas are provided. In some embodiments, a method includes receiving a data stream from one or more data sources; accessing a first observation schema including one or more built-in fields and one or more custom fields associated with the received data stream; receiving a configuration associated with at least one of the one or more custom fields; and generating a second observation schema based on the configuration and the first observation schema.
A method comprises receiving, at a host, a request to set new service configuration information for a target service in a distributed computing environment; retrieving a current revision identifier of a current revision of service configuration information for the target service from a revision index key in a local replica of a configuration store, the revision index key storing one or more key-value pairs, a key in a specific key-value pair identifying the target service; assigning a new revision identifier based on the current revision identifier; writing the new service configuration information into a new revision of the service configuration information in the local replica; updating the revision index key in an atomic compare-and-swap operation, the compare comprising verifying that the current revision identifier in the revision index key has remained the same since the retrieving, the swap comprising updating the specific key-value pair with the new revision identifier.
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
G06F 8/71 - Gestion de versions Gestion de configuration
G06F 9/44 - Dispositions pour exécuter des programmes spécifiques
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 9/46 - Dispositions pour la multiprogrammation
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
H04L 41/5054 - Déploiement automatique des services déclenchés par le gestionnaire de service, p. ex. la mise en œuvre du service par configuration automatique des composants réseau
86.
SYSTEMS AND METHODS FOR PROVIDING SECURITY LEVEL BASED GEOSPATIAL NOTIFICATION
Systems and methods for generating, managing, and/or providing notifications are provided. In some embodiments, a method includes displaying a map corresponding to a map security level to a user, receiving an indication of a geospatial area on the map, receiving a data stream, the data stream corresponds to a data security level, determining if the data security level satisfies a first security level threshold, in response to determining that the data security level satisfies the first security level threshold, in response to detecting the entity that satisfies the notification condition, generating a geospatial notification including information representing the geospatial area and the entity, determining if a user security level for the user satisfies a second security level threshold, and in response to determining that the user security level satisfies the second security level threshold, presenting the geospatial notification to the user.
A system may receive a natural language query and receive an indication of a format of a first computer language as well as an indication of one or more computer-based tools stored in and/or accessible by the system. The system can transmit a prompt to a large language model (“LLM”). The prompt may include the natural language query, the indication of the format, and the indication of the one or more computer-based tools. The system can receive, from the LLM, a response to the prompt in the format of the first computer language. The system can parse the response in the first computer language to identify at least: a computer-based tool of the one or more computer-based tools. The system can generate a second query in a second computer language and provide the second query in the second computer language to the computer-based tool.
An artificial intelligence system can be used to respond to natural language inputs. The AI System may, for example, receive a first user input for a LLM, generate a first prompt based on the first user input, transmit the first prompt to an LLM, receive an output from the LLM, and evaluate the output from the LLM with reference to one or more validation tests. Responsive to determining that the output from the LLM is not validated, generate a second prompt for the LLM, where the second prompt indicates at least an aspect of the output that caused the output to not be evaluated (e.g., a portion of the output that may need to be updated or corrected), transmit the second prompt to the LLM, and receive an updated output from the LLM. The AI system can include an application for testing functions that utilize interactions with language models.
Methods, apparatuses and computer programs are for executing complex computing tasks in a computing platform are provided. According to one aspect, a method comprises receiving, by a planning agent, a use case input indicating an objective for completion in the computing platform. The planning agent decomposes, by the planning agent, the use case input into a plurality of tasks for achieving the objective. The planning agent provides each of the plurality of tasks to a respective task agent for execution. For each task of the plurality of tasks, the respective task agent identifies a tool suitable for performing the task from a plurality of tools. The task agent uses the identified tool to execute an operation corresponding to the respective task in the computing platform.
A method of contextual modification of data sharing constraints is disclosed. The method comprises receiving a data sharing request to share a first data model with a database associated with a second data model; generating a shareable version of the first data model in response to the data sharing request; determining a parameter value used to perform a data model merging operation to merge the shareable version of the first data model with the second data model, the parameter value indicating whether to execute or skip a particular process during the data model merging operation; determining context data for the data model merging operation based on the generating; modifying the parameter value based on the context data; performing the data model merging operation using the modified parameter value.
G06F 16/248 - Présentation des résultats de requêtes
G06F 7/14 - Interclassement, c.-à-d. association d'au moins deux séries de supports d'enregistrement, chacun étant rangé dans le même ordre de succession, en vue de former une série unique rangée dans le même ordre de succession
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
91.
SYSTEMS AND METHODS FOR GENERATING AND MANAGING SECURITY LEVEL-AWARE MAP
Systems and methods for generating and/or managing maps are provided. In some embodiments, a method includes receiving a map request from a first user to generate a map with a map security level, in response to determining that the map security level satisfies the first security level threshold, generating the map with the map security level, receiving a query from the first user, identifying a data feed associated with the query, receiving the data feed from a data source, the data feed including a plurality of data items and each data item corresponding to a corresponding data security level, for each data item of the plurality of data items, determining whether the data item satisfies a second security condition, and adding one or more data items of the plurality of data items that satisfy the second security condition on the map.
A computing device, such as a server, has a sealed housing and runs one or more data extraction agents. In some embodiments, the computing device includes one or more processors and memory located inside the sealed housing, the memory stores instructions that when executed by the one or more processors causes the one or more processors to: authenticate with a data recipient system using a prestored security engine and using a shared registration secret uniquely associating the computing device with the data recipient system; retrieve an extraction job specification from an extraction job specification repository associated with the data recipient system; and using the extraction job specification, communicate to one or more client computing devices associated with a client system to extract data records from one or more data stores of the client system. Related methods are also disclosed.
Systems and methods are provided for improved auditing of user actions associated with a software application. The system includes functionality to log user actions in a structured, standardized way. The system includes interactive user interfaces for analyzing the logs. The logging is based on a well-defined categorization of available actions. The log information includes (and distinguishes among) user details, context details, user inputs, and/or system outputs (including identification of data objects). The interactive user interfaces enable a user to view structured log data in an efficient manner, such as by presenting logs in a tabular format, executing queries on the log data, and/or presenting visualizations that summarize the log data. The interactive user interfaces provide functionality that allows a user to investigate and/or audit user interactions with a data object. The interactive interfaces present log entries associated with the object(s) for further review by the reviewer.
Methods and systems for site prospecting includes the operations of: receiving a site request indicating a required use for a site; generating a plurality of capacity scores corresponding to a plurality of land parcels using a first machine learning model; filtering the plurality of land parcels into a subset of land parcels based on the plurality of capacity scores; and for at least one land parcel in the subset of land parcels: generating a parcel potential description using a first language model based at least in part on geographic information associated with the at least one land parcel; generating a parcel potential score using a second machine learning model based at least in part on the parcel potential description; and presenting the parcel potential description and the parcel potential score.
G06F 16/387 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G06F 16/335 - Filtrage basé sur des données supplémentaires, p. ex. sur des profils d’utilisateurs ou de groupes
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
95.
SYSTEMS AND METHODS FOR CROSS-DOMAIN SOFTWARE PRODUCT AND SOFTWARE PRODUCT METADATA DELIVERY
Systems and methods for software product deployment and/or compliance management are provided. In some embodiments, a method includes: receiving an indication of a first payload of a software deployment package; performing a first software scan of the first payload; generating a first integrity file including an indication of integrity based upon the first software scan; and triggering a transfer of the first payload and the first integrity file from a first network domain to a second network domain different from the first network domain.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
A data analysis system presents a user interface to allow a user to provide a natural language query pertaining to a dataset, wherein the dataset is associated with a data object model comprising a plurality of objects and receives, via the user interface, user input specifying the natural language query. The data analysis system further modifies, in the user interface, the user input to visually indicate one or more portions of the natural language query that each represent one of the plurality of objects and presents, in the user interface, a response to the natural language query, the response being based on data from the dataset, the data corresponding to the one of the plurality of objects.
A system may receive a representation of a process, wherein the representation of the process includes: a plurality of states, and one or more transitions among states of the plurality of states. A system may receive a plurality of data objects, wherein each of the data objects is associated with a respective set of properties. A system may determine for each of the plurality of data objects, respective state information associated with the data objects. A system may cause generation of an interactive graphical user interface including: a graph-based visualization of at least a portion of the plurality of states and the one or more transitions, wherein the graph-based visualization is generated based at least in part on at least a portion of the plurality of data objects and associated properties and state information.
A system may receive a representation of a process, wherein the representation of the process includes: a plurality of states, and one or more transitions among states of the plurality of states. A system may receive a plurality of data objects, wherein each of the data objects is associated with a respective set of properties. A system may determine for each of the plurality of data objects, respective state information associated with the data objects. A system may cause generation of an interactive graphical user interface including: a graph-based visualization of at least a portion of the plurality of states and the one or more transitions, wherein the graph-based visualization is generated based at least in part on at least a portion of the plurality of data objects and associated properties and state information.
Systems and methods for visual navigation are provided. An example method includes receiving a plurality of video frames from an image sensor disposed on an aircraft, and generating an image-based transform based on the plurality of video frames. In some examples, the image-based transform is associated with a movement of one or more image features and a movement of the image sensor. In some examples, the method further includes: determining an image-based motion associated with the aircraft based on the image-based transform, generating a georegistration transform based on at least one video frame of the plurality of video frames and a reference image, determining a georegistration-based geolocation associated with the aircraft based on the georegistration transform, and determining an aircraft geolocation by applying a non-linear Kalman filter to the image-based motion and the georegistration-based geolocation,
G06T 7/246 - Analyse du mouvement utilisant des procédés basés sur les caractéristiques, p. ex. le suivi des coins ou des segments
G01C 21/20 - Instruments pour effectuer des calculs de navigation
G06T 7/277 - Analyse du mouvement impliquant des approches stochastiques, p. ex. utilisant des filtres de Kalman
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images utilisant des procédés basés sur les caractéristiques
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
100.
MULTI-USER ACCESS CONTROLS IN ELECTRONIC SIMULTANEOUSLY EDITABLE DOCUMENT EDITOR
A system with an interactive user interface for a plurality of users to author an electronic document simultaneously is described. The system displays visual feedback on the interface to prevent the users from interfering with one another. The system displays data from a remote database linked into the document based on unique identifiers. The data is displayed as an “artifact.” The system monitors and tracks each user's access category level, as well as the access category level of each piece of data pulled from the remote database. The system compares a user's category level to the data from the database to make visible only the portions of the document the user has the appropriate access category level to view and/or modify. The portions of the document that have a higher category level than the user will be hidden from the user either in part or completely. Also, there may be an indicator to the user of such redacted or hidden content from the user's viewer.
