First and second dashboards that provide a visual representation of respective intelligence information for a firewall may be generated. An indicator of correspondence between a first data element of the respective intelligence information for the first dashboard and a second data element of the respective intelligence information for the second dashboard may be displayed as an overlay of the first and second dashboards. Additionally, a guidance indicator that indicates an order to access respective values of the first dashboard, the second dashboard, and a third dashboard may be displayed based on an identifier of the first data element mapped to an identifier of the second data element and an identifier of the second data element mapped to an identifier of a third data element for the third dashboard. A summary window that provides a summary of intelligence dashboards of a user interface may be displayed.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
H04L 41/22 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets comprenant des interfaces utilisateur graphiques spécialement adaptées [GUI]
2.
TRANSFORMER-BASED ADVERSARIAL ACTIVE LEARNING SYSTEM
System and method for transformer-based adversarial active learning system. A machine learning system includes a generator, a transformer encoder, a classifier, and a discriminator all working in combination to generate and select unlabeled data points for labeling. The system utilizes a generative adversarial network paired with an active learning framework to optimize text embedding and feature encoding according to distribution of training data.
A method and system for generating a privilege based segmented instruction prompt has been developed. Trusted instructions defining the trusted instructions as having a first privilege level, program instructions as having a second privilege level, and data instructions as having a third privilege level are received. The program instructions to implement tasks associated with the data instructions are received. The data instructions are received. The generated privilege based segmented instruction prompt includes the trusted instructions, the program instructions, and the data instructions. The privilege based segmented instruction prompt enables a generative LLM to determine whether the privilege based segmented instruction prompt is an instruction injection attack based on whether there is a conflict between the trusted instructions, the program instructions, and the data instructions in violation of the first, second, and third privilege levels.
Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products for digital content auditing in a group based communication repository, where the group based communication repository comprises a plurality of enterprise-based digital content objects organized among a plurality of group-based communication channels. In one embodiment, a computing entity or apparatus is configured to receive an enterprise audit request, where the enterprise audit request comprises an audit credential and digital content object retrieval parameters. The apparatus is further configured to determine if the audit credential satisfies an enterprise authentication protocol. In circumstances where the audit credential satisfies the enterprise authentication protocol, the apparatus is configured to retrieve and output digital content objects based on the digital content object retrieval parameters, receive a violating digital content object identifier, and replace a violating digital content object with a temporary digital content object based on the violating digital content object identifier.
Methods and systems are provided for generating an interactive simulation representing one or more assets based on one or more asset records. Based on information from asset records stored at a database system of a cloud-based computing system, an asset simulator module, executed at a cloud-based computing system, can generate one or more simulated representations of the assets. A simulator application executed at the cloud-based computing system can augment the simulated representations of the assets with (at least) additional information from the asset records stored in the database system, and generate a user interface that presents an interactive simulation of the assets. The user interface can include the simulated representations of the assets with the additional information from the asset records stored in the database system.
G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
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
In some embodiments, a method provides first data for a first reporting object that is determined by performing a first operation using respective first values associated with first records to generate a second value for the first reporting object. The first records are determined from a relationship in a data model that specifies a defined set of fields to the first reporting object for a sustainability metric. The method retrieves second records that are tagged with a custom label not used in the defined set of fields. The second records is a different set of records than the first set of records. The method provides second data for a second reporting object that is determined by performing a second operation, using respective first values associated with the second records that are associated with the custom label, to generate a third value for the second reporting object for the sustainability metric.
A method by one or more electronic devices for creating an inference container on demand. The method includes receiving, over a network, a request to create the inferencing container, wherein the inferencing container is configured to provide inferencing functionality, creating the inferencing container responsive to receiving the request to create the inferencing container, and providing, over the network, a response to the request to create the inferencing container, wherein the response includes a uniform resource locator (URL) to use to submit inferencing requests to the inferencing container, wherein the URL includes a unique identifier (ID) of the inferencing container.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
A computer system monitors for a change in a first data output generated by execution of a predefined dataflow. In accordance with a determination that the first data output has changed and the first data output meets triggering criteria, the computer system triggers execution of a predefined second dataflow distinct from the first dataflow. The execution of the second dataflow is dependent on the change in the first data output generated by the first dataflow. In accordance with a determination that the first data output has changed and the first data output does not meet triggering criteria, the computer system forgoes triggering execution of the second data flow. In accordance with a determination that the first data output has not changed, the computer system forgoes triggering execution of the second dataflow.
Embodiments described herein provide a diffusion-based framework that is trained on a dataset with limited text labels, to generate a distribution of data samples in the dataset given a specific text description label. Specifically, firstly, unlabeled data is used to train the diffusion model to generate a data distribution of data samples given a specific text description label. Then text-labeled data samples are used to finetune the diffusion model to generate data distribution given a specific text description label, thus enhancing controllability of training.
Techniques are disclosed relating to managing database queries. In some embodiments, a server system receives a query from a computer system and determines a set of aspects for the query, including at least a number of columns specified in the query and a computational cost of executing the query. The system generates a query vector based on the set of aspects determined for the query. The system then compares the query vector with a plurality of clusters, ones of the plurality of clusters comprising two or more previously generates query vectors generated based on aspects of queries previously received by the server system. Based on the comparing, specifically a distance between the query vector and the plurality of clusters of previously generated query vectors, the system classifies the query. Based on a classification of the query determined during the classifying, the system manages the query.
A computing device displays, in a graphical user interface corresponding to a data visualization application, a dashboard having one or more data visualizations related to a data source. The device receives a user interaction with a first data visualization of the dashboard. The device compares the user interaction to a set of stored trigger actions and determines, based on the comparing, that the user interaction corresponds to a predefined trigger to initiate a workflow action to be executed by an external service, distinct from the data visualization application. In accordance with the determination, the device identifies parameters of a predefined action template corresponding to the workflow action. The device extracts a subset of data from the data source, corresponding to the parameters. The device maps the subset of data to the parameters of the action template and initiates execution of the external service.
Disclosed herein are system, method, and computer program product embodiments for implementing variable Sankey charting. The system receives a dataset for charting and various charting parameters. Using the information provided, the system identifies starting and ending categories that will be illustrated in the chart. For each of these categories, the system then calculates a starting and ending height, and corresponding positions in the chart. The heights may be based on a percentage of the total value of data that is included within a particular category. The system then calculates positions of the various bars on the chart based on information provided by the user, or automatically based on the analysis of the data corresponding to the different categories. One or more curves are then calculated for each of the different categories to illustrate the transition of the data from a starting point to an ending point on the chart.
An automated data extraction pipeline for large language model (LLM) training may include extracting a set of code segments from a set of natural language question-answer (Q&A) combinations that each include a provided input, a provided output, and a provided code segment formatted to transform the provided input into the provided output. The data extraction pipeline may then generate a predicted output from a question portion of a first natural language Q&A combination using a first LLM. A first extracted code segment from the extracted set of code segments may then be executed to generate a first actual output of the first extracted code segment. One or more data samples may then be generated for training a second LLM based on a comparison of the first actual output to the predicted output. The second LLM may then be trained using the one or more data samples.
Techniques are disclosed pertaining to layered filtering. A computer system may store records in a hierarchy of levels. The computer system may receive a request to perform a key range search to locate records that fall within a key range and satisfy selection criteria. The computer system may perform the key range search. As part of processing a particular level, the computer system may receive a first set of records associated with another level and select a second set of records from the particular level that fall within the key range and satisfy the selection criteria. The computer system may merge the first and second sets of records into a third set of records, which may include not inserting, into the third set, any record of the first set of records for which there is a newer version in the particular level that does not satisfy the selection criteria.
In accordance with embodiments, there are provided mechanisms and methods for managing business deals. The mechanisms and methods for managing business deals may enable embodiments to provide a dynamic and interactive user-interface including any combination of contacts, accounts, opportunities, allowing users to create tasks, events, leads (e.g., from Data.com), reports, dashboards, instant messenger, external deal spaces, email service (e.g., Outlook), a cloud-based productivity suite for businesses that allows work on any device (e.g., Google apps), mobile access, private messaging, lead management, mass email templates, social media monitoring (e.g., from Radian6), role-based sharing and security, and/or additional storage, for example. In an embodiment, the number of contacts may be unlimited.
Embodiments described herein provide a method of predicting an action by a plurality of language model augmented agents (LAAs). In at least one embodiment, a controller receives a task instruction to be performed using an environment. The controller receives an observation of a first state from the environment. The controller selects a LAA from the plurality of LAAs based on the task instruction and the observation. The controller obtains an output from the selected LAA generated using an input combining the task instruction, the observation, and an LAA-specific prompt template. The controller determines the action based on the output. The controller causes the action to be performed on the environment thereby causing the first state of the environment to change to a second state.
Embodiments described herein provide a method for training a recommendation neural network model using multiple data sources. The method may include: receiving, via a data interface, time series data indicating a user-item interaction history; transforming the time series data into a user-item graph; encoding, by a neural network encoder, the user-item graph into user embeddings and item embeddings; generating a plurality of losses according to a plurality of training tasks performed based on the user embeddings and, item embeddings; training the recommendation neural network model by updating the user embeddings and the item embeddings via backpropagation based on a weighted sum of gradients of the plurality of losses; and generating, by a neural network decoder, one or more recommended items for a given user based on the updated user embeddings and the updated item embeddings.
Embodiments described herein provide for optimizing a language model (LM) agent. In at least one embodiment, and LM agent comprises an “actor” LM and a “retrospective LM which provides reflections on attempts by the actor LM. The reflections are used to update subsequent prompts to the actor LM. Optimizing the LM agent comprises fine-tuning parameters of the retrospective LM while keeping parameters of the actor LM frozen. A gradient may be determined by a change in reward from the environment based on actions taken by the actor LM with and without a reflection of the retrospective LM. Using this gradient, parameters of the retrospective LM may be updated via backpropagation.
A method for configuring the operation of the software of a data as a service (DAAS) system during run time is described. The configuring includes receiving a match query from a customer relationship management system that transmitted the match query responsive to a user using an interface to trigger an update of records in the customer relationship management system that were previously imported from the DAAS system, querying for records in the dataset that match records in the customer relationship management system previously imported from the DAAS system, the querying configured at run time according to metadata that identifies, for records in the dataset, a field to match on and a match threshold, and producing a match query result that includes records in the dataset to be imported to update records that were previously imported from the DAAS system.
Disclosed are systems, apparatus, methods and computer-readable media for updating information stored in a database system over a network. In some implementations, first contact data is retrieved from a first virtual portion of a database system, where the first contact data provides first contact information associated with at least one entity. In some instances, the first contact data is compared with second contact data, where the second contact data provides second contact information associated with the at least one entity. In some instances, at least some of the second contact information is retrieved from a social networking system. In various implementations, at least one difference between the first contact data and the second contact data is identified, where the at least one difference is capable of being presented in a user interface displayed at a computer system. In some instances, a selection identifying contact data to store is received.
Disclosed herein are example embodiments that describe how a narrative generation techniques can be used in connection with data visualization tools to automatically generate narratives that explain the information conveyed by a visualization of a data set. In example embodiments, new data structures and artificial intelligence (AI) logic can be used by narrative generation software to map different types of visualizations to different types of story configurations that will drive how narrative text is generated by the narrative generation software.
Disclosed are examples of systems, apparatus, methods and computer program products providing network security orchestration and management across different clouds. In some implementations, network security information includes a set of security policies indicating permitted communications between or among computing resources. The network security information is converted to a cloud-independent representation. From the cloud-independent representation, policy sets can be generated, where each policy set is specific to a different cloud.
A computer-implemented method for exposing a software component through a predetermined protocol is disclosed. The method may include receiving a software component including at least one of a configuration, an operation, a trigger, and a parameter, and receiving a metamodel describes the configuration, the operation, the trigger, and the parameter. The method may also include generating a microservice and an API specification entirely based on the metamodel without additional coding. The computer-implemented method may further include deploying the microservice such that the microservice accepts incoming requests described by the API specification, and receiving a formatted response from the deployed microservice. The method may also include receiving a new configuration of the software component created on the deployed microservice.
Implementation(s) for multi-factor network segmentation are described. A plurality of packets at a higher layer of a network stack is processed, where at least one packet of the plurality of packets was previously determined, as part of processing the at least one packet at lower layers of the network stack, to be authorized to be processed by the higher layer. Specifically, responsive to successful authentication of a cryptographic certificate received during the handshake process, a second service is identified from the cryptographic certificate. It is determined, based on a security policy, that the second service is authorized to access the first service. Responsive to the determination, a configuration is caused such that packets sent using the source address are now authorized to be processed by the higher layer.
The present disclosure is related to automatically, based on contextual information and without needing explicit input from a user, modifying one or more settings associated with presenting a notification. In examples, settings may include automatically suspending notification presentation or automatically overriding a notification setting that suspends notification presentation. In addition, contextual information may include, among other things, information related to a computing device (e.g., device location or network signal strength), a rate of user interaction or engagement with an application (e.g., rate of information sharing, user reactions, etc.), and/or a calendar or schedule of a user. In examples, the contextual information may be analyzed (e.g., based on comparison to a threshold) to determine whether a condition is met, and based on the analysis, the one or more settings may be modified.
H04L 51/222 - Surveillance ou traitement des messages en utilisant des informations de localisation géographique, p. ex. des messages transmis ou reçus à proximité d'un certain lieu ou d'une certaine zone
H04L 51/224 - Surveillance ou traitement des messages en fournissant une notification sur les messages entrants, p. ex. des poussées de notifications des messages reçus
H04M 1/72451 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques basés sur des horaires, p. ex. utilisant des applications de calendrier
H04M 1/72454 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques en tenant compte des contraintes imposées par le contexte ou par l’environnement
H04M 1/72457 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques en s’appuyant sur la localisation géographique
H04M 1/72463 - Interfaces utilisateur spécialement adaptées aux téléphones sans fil ou mobiles avec des moyens permettant d’adapter la fonctionnalité du dispositif dans des circonstances spécifiques pour limiter la fonctionnalité du dispositif
H04W 4/02 - Services utilisant des informations de localisation
H04W 68/02 - Dispositions pour augmenter l'efficacité du canal d'avertissement ou de messagerie
H04W 72/54 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de qualité
H04W 72/563 - Critères d’affectation ou de planification des ressources sans fil sur la base de critères de priorité des ressources sans fil
Techniques are disclosed relating to a database system. The database system includes multiple coordinator nodes storing replicas of a partition. Each partition describes the state of locks and transactions for keys covered by that partition of keys. Each partition is, in turn, replicated. The multiple coordinator nodes receive, from multiple worker nodes, requests to grant a lock for a key to permit a worker node to write a record for the key as part of executing a transaction. A given coordinator node of the multiple coordinator nodes sends an approval response for the lock to at most one of the worker nodes. A single worker node acquires the lock in response to receiving approval responses from a majority of the multiple coordinator nodes, and none of the multiple worker nodes acquire the lock in response to none of them receiving approval responses from a majority of the multiple coordinator nodes.
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 16/22 - IndexationStructures de données à cet effetStructures de stockage
Applied Artificial Intelligence Technology for Performing Natural Language Generation (NLG) Using Composable Communication Goals and Ontologies to Generate Narrative Stories
Artificial intelligence (AI) technology can be used process natural language statements to facilitate the automated generation of narratives about data sets that achieve a desired communication goal without any need for a user to directly author computer code. This AI technology permits NLG systems to determine the appropriate content for inclusion in the narrative in a manner that will satisfy the desired communication goal.
Techniques described herein support component maintenance that accounts for a similarity between characteristics of different components. To identify components with similar characteristics, one or more techniques described herein support generation of a data structure (e.g., a tree) that represents a component, where each characteristic may be represented in a different leaf node. The system may generate a similarity score, or value (e.g., as a percentage), between multiple components based on comparing individual nodes of a tree representing each component, respectively. If the similarity score satisfies a threshold, then the system may display, at the UI, a message indicating to a user to preferentially implement one component over another.
A method generates analytic asset recommendations using graph neural networks. The method obtains a data graph that includes a plurality of nodes. Each node stores metadata for a respective analytic asset of a plurality of analytic assets. The data graph encodes relationships between the plurality of analytic assets. The method extracts a set of features for each node of the data graph. Each node has the same features as other nodes. The method derives corresponding node embeddings for two nodes of the data graph using a two-layer graph neural network based on the data graph and the set of features. The method predicts a link between the two nodes of the data graph based on the corresponding node embeddings. The method also generates a recommendation for an analytic asset when the probability for the link is above a predetermined threshold.
A method generates data visualizations for interactive recommender systems for analytic assets. The method obtains recommendations to destination nodes for a source node of an input graph, which includes nodes including the source node and a destination node. Each node stores metadata for a respective analytic asset. The input graph encodes asset lineage that captures relationships between the analytic assets. The method also generates a data visualization for the recommendations. The data visualization includes (i) a summary of the recommendations, (ii) a comparison of the destination nodes, and (iii) a set of factors that contributed to one or more recommendations. The method also includes displaying the data visualization using a graphical user interface. The graphical user interface includes a data region that includes the summary, a recommendation overview region that includes the comparison, and a recommendation detail region that includes the set of factors.
Disclosed herein are system, method, and computer program product embodiments for automatic non-code test suite generation of an application programming language (API) specification. An embodiment operates by receiving a specification of an API, wherein the API comprises a plurality of endpoints. The embodiment generates, using a parser, an abstraction model corresponding to the specification of the API, wherein the abstraction model comprises a plurality of entities corresponding to the plurality of endpoints. The embodiment identifies, based on the abstraction model, an operation that is applicable to an entity of the plurality of entities. The embodiment then generates a functional test based on a use case corresponding to the entity and the operation.
Methods and systems for distributed denial of service (DDoS) protection management are described. The system may aggregate, from a web application firewall (WAF) bridge service that interfaces with one or more WAF services, one or more DDoS event records associated with one or more DDoS events. The system may analyze the one or more DDoS event records via an analysis of one or more headers and one or more payloads of the one or more DDoS event records, logging information, and a threat intelligence feed. The system may generate a security configuration that indicates one or more parameters of the one or more WAF services to be set. The system may validate the security configuration and may transmit the security configuration to the one or more WAF services based at least in part on the validation.
A computing platform is configurable to cause initiating a communication session with a user, the user having a user account associated with a workflow data object implemented in an on-demand application hosted by the computing platform, the workflow data object being configured to represent a plurality of operations associated with the user and an organization, and further associated with a vaccination status of the user. The computing platform is configurable to cause identifying a verified status indicator used by at least one of the plurality of operations represented in the workflow data object, the verified status indicator comprising a verified credential associated with at least one of the plurality of operations. The computing platform is configurable to cause identifying a transfer operation associated with the verified status indicator and identifying a target entity based on the user account, and implementing the identified transfer operation based on the identified target entity.
A computer-implemented method of decision optimization in a multi-record environment is disclosed. The method includes receiving a request to make a recommendation in relation to a data record and defining the recommendation in terms of an optimization problem including decision objectives including objective contribution functions and constraints including constraint contribution functions. The method also includes extracting input data from a data source, the input data including individual instances of data and attributes describing the individual instances of data. The method also includes identifying a context of the optimization problem based upon the individual instances of data. The context relates to a behavior of the input data given the decision objectives and the constraints. The method further includes solving the optimization problem by satisfying the decision objectives and the constraints, in the context, to generate a solution and providing the recommendation based on the solution.
In view of the need for a conversational recommender system (CRS) in guiding purchasing processes of complex items, embodiments described herein provide a CRS system that creates a realistic purchase scenario and agent evaluation for fulfilling the recommendation objective. Specifically, the CRS system utilizes existing buying guides as a knowledge source for the recommendation model.
Embodiments described herein provide a system for training a neural network model using a teacher-student framework. The system includes a communication interface configured to communicate with a teacher model; a memory storing a student model and a plurality of processor-executable instructions; and a processor executing the processor-executable instructions to perform operations. The operations include: generating, by the student model, a first task output in response to a task input; obtaining, from an evaluation environment, a feedback relating to an accuracy of the first task output; obtaining a refinement output generated by the teacher model based on an input of the first task output and the feedback; and training the student model based on a training input of the first task output and the feedback and a training label of the refinement output.
A computer system receives, from a programmatic interface of a client device via one or more external API calls, a query that specifies a data source and one or more data fields of the data source. The computer system, in accordance with receiving the query, generates a query specification according to the one or more data fields of the data source, wherein the query specification is an extended version of the API calls. The computer system transmits the query specification to a data service and causes the data service to execute one or more database queries to retrieve data against a database to retrieve query results from the data source, according to the query specification. The computer system receives the query results from the data service, configures the query results to obtain configured data, and transmits the configured data to the client device for display in the programmatic interface.
A non-transitory computer readable medium having computer instructions stored therein that when executed by a computer system cause the computer system to perform operations including receiving a first user input defining a dialog session comprising one or more steps of a natural language conversation flow, receiving a second user input defining a positive outcome of the dialog session, receiving, via a chat interface, a natural language input, initiating the dialog session in response to an association between the natural language input and the dialog session, receiving, via the chat interface, a subsequent natural language input, and updating a data entry associated with the custom metric in an outcome log in response the subsequent natural language input being indicative of the positive outcome of the dialog session.
A database with virtual partitioning. A computer system used to implement the database receives a request for a database operation to be performed on data stored in a portion of the database, where the data has a group of logical partitions (e.g., tenants of a multi-tenant database), and where the portion of the database is not further physically partitioned. The computer system identifies a virtual partitioning scheme for the database operation, the virtual partitioning scheme defining sub-groups of the group of logical partitions. The computer system then performs the database operation for the sub-groups defined by the virtual partitioning scheme. Multiple virtual partitioning schemes can be active at the same time, and virtual partitioning schemes can be created dynamically in some instances.
Embodiments described herein provide a framework that integrates a retriever model and the LLM to feed retrieved passages to an LLM to generate an answer conditioned on the retrieved passages in response to a query. For example, in one embodiment, a single-round approach is implemented, which involves directly transmitting the retrieved passages to the LLM. For another example, a multi-round methodology is implemented, which involves initially presenting the retrieved passages to the Language Model, collecting its responses, and then adjusting our interaction with the Language Model based on this acquired feedback.
G06N 3/006 - Vie artificielle, c.-à-d. agencements informatiques simulant la vie fondés sur des formes de vie individuelles ou collectives simulées et virtuelles, p. ex. simulations sociales ou optimisation par essaims particulaires [PSO]
A client device receives one or more inputs for generating a data visualization according to a data source. The device determines one or more requirements for generating the data visualization. The device sends a request to a network gateway that is communicatively connected to the client device and a plurality of data servers, and receives, from the network gateway, capabilities of each data server. The device determines, according to the received capabilities, that a first data server of the plurality of data servers includes a first set of capabilities that satisfies the requirements for generating the data visualization. The device sends, via the network gateway, one or more queries to the first data server and receives, from the first data server, one or more data sets from the data source. The device generates the data visualization according to the retrieved data sets and displays the data visualization.
Media, methods, and systems are provided for screen sharing. A user may initiate a video recording. A recording preview interface may be displayed for the user to preview the video recording before beginning the recording. The recording preview interface may comprise a live video preview of the user and of a window or application being shared. When the user selects a window or application for previewing that may cause an infinity mirror effect to occur, a screenshot of the window or application may be generated. The screenshot may be rendered over the live video preview of the window or application to obscure the infinity mirror effect. When the user initiates recording, the screenshot may be removed to expose the live video. The screenshot may be cached and retrieved if the user navigates away and then returns to the preview of the window or application causing the infinity mirror effect.
A system may receive, via a cloud-based platform supporting a plurality of tenants, one or more access events from a user of a host platform associated with a tenant, the one or more access events comprising one or more keystroke events at the host platform and one or more commands inputted by the user at the host platform, wherein the one or more access events are captured by a continuous authentication agent associated with the host platform. The system may identify fraudulent access events based at least in part on executing a machine learning model to perform a pattern matching between previously authenticated browsing behavior of the user and the one or more access events at the host platform. The system may generate a challenge question for reauthenticating the user of the host platform based at least in part on identifying the at least one fraudulent access event.
Techniques are disclosed pertaining to performing upgrades by upgrade controllers. A node upgrade controller determines to upgrade a first set of nodes, of a plurality of nodes, on which executes a first set of pods that facilitate access to an instance of a particular component. The node upgrade controller obtains a lock on the plurality of nodes to prevent a pod upgrade controller from upgrading a second set of pods that execute on a second set of the plurality of nodes and facilitate access to another instance of the particular component. The unavailability of the first and second sets of pods causes a requisite number of instances of the particular component to be unavailable. The node upgrade controller upgrades the first set of nodes and releases the lock to allow the pod upgrade controller to obtain a lock on the plurality of nodes.
A method, system and computer program product for aggregate query optimization. A dataset with plurality of values divided into dimensions and measurements is received. Pre-calculated values obtained by aggregates of measurements' values respective of plurality of combinations of dimensions' values are calculated and stored for one or more aggregate measurements of interest. Responsive to an input received of a first set of one or more dimensions and a second set of one or more aggregate measurements of interest, an aggregate result value of a respective member of the second set is calculated and outputted by retrieval of the pre-calculated value therefor respective of members of the first set.
Disclosed herein are system, method, and device embodiments for creating an improved mobile interface of a messaging application. The mobile interface displays unread conversations as a stack of tiles. With the top tile displayed, a user may efficiently mark the conversation as read or unread by swiping left or right. The interface then moves to the next tile in the stack. This allows a user to quickly triage unread messages while in the mobile application. The mobile interface ranks unread messages in an intuitive fashion in determining the ordering of the tiles. The interface may generate these rankings using a trained artificial intelligence based on a user's past behaviors and signals in unread messages. Messages received during the user's review of the stack of tiles may be dynamically inserted in a thoughtful manner. A summary may be displayed that indicates the number of messages, an estimated time to complete the review of the unread messages, and a summary of the unread messages that may be generated by sending a generative pre-trained transformer prompt to a trained neural network.
H04L 51/21 - Surveillance ou traitement des messages
G06F 3/04883 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels pour l’entrée de données par calligraphie, p. ex. sous forme de gestes ou de texte
A method of data processing is described. The method includes receiving, at a server host, a request to access a web domain associated with a tenant of a multi-tenant cloud platform; retrieving, from a database, a tenant private key and a certificate associated with the tenant, where the tenant private key is encrypted with a secret key derived from a key agreement public key associated with the tenant and a private key provisioned to a key protection component of the server host; providing, to the key protection component, the encrypted tenant private key and the key agreement public key; receiving, from the key protection component, an API response including a signature associated with the tenant private key; and providing, to a client device associated with the request to access the web domain of the tenant, the certificate and the signature, where the certificate is used to verify the signature.
Methods, systems, apparatuses, devices, and computer program products are described. A system may input a first audio stream (e.g., audio recording) and a corresponding text sting into a machine learning model. The first audio stream and the text string may correspond to a first identity (e.g., person). Based on an output of the machine learning model, the system may generate a second audio stream associated with a second identity and mimics the first audio steam. For example, the second audio stream may be a generated recording of the second identity speaking the first text string. In addition, the system may generate a video depicting the second identity speaking the first text string (e.g., the second audio stream) based on combining the second audio stream with some image or previous video of the second identity. For example, the system may generate the video based on generating a head motion sequence.
G10L 21/10 - Transformation en information visible
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
51.
SYSTEMS AND METHODS FOR A CONVERSATIONAL FRAMEWORK OF PROGRAM SYNTHESIS
Embodiments described herein provide a program synthesis framework that generates code programs through a multi-turn conversation between a user and a system. Specifically, the description to solve a target problem is factorized into multiple steps, each of which includes a description in natural language (prompt) to be input into the generation model as a user utterance. The model in turn synthesizes functionally correct subprograms following the current user utterance and considering descriptions and synthesized subprograms at previous steps. The subprograms generated at the multiple steps are then combined to form an output of program in response to the target problem.
Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
G06F 16/21 - Conception, administration ou maintenance des bases de données
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
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
53.
HARDWARE-BACKED PASSWORD SECURITY FOR CLOUD SYSTEMS
Methods, systems, and devices for data processing are described. A server host may receive a login request that includes a clear text password for an account associated with a tenant of a multi-tenant cloud platform. The server host may retrieve an encrypted payload associated with the account. The encrypted payload may include a hash value of a user-configured password for the account and an indication of a hashing algorithm used to transform the user-configured password into the hash value. The server host may obtain a wrapped symmetric key provisioned by a symmetric key distribution service. The server host may transmit a request that includes the encrypted payload, the clear text password, and the wrapped symmetric key. The server host may receive a response that indicates whether a hash value of the clear text password from the login request corresponds to the hash value of the user-configured password.
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
Methods, systems, and devices for data processing are described. A server host may receive a request to access a web domain associated with a tenant of a multi-tenant cloud platform. The server host may retrieve a digital certificate and an encrypted private key associated with the tenant, where the digital certificate includes a public key associated with the tenant. The server host may obtain a symmetric key that is wrapped using an asymmetric public key associated with the server host. The wrapped symmetric key may be provisioned by a symmetric key distribution service. The server host may transmit a request that includes the encrypted private key and the wrapped symmetric key. The server host may receive a response that includes a cryptographic signature associated with the private key of the tenant. The server host may provide the digital certificate and the cryptographic signature to a client device associated with the request.
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
55.
HARDWARE-BACKED PASSWORD SECURITY FOR CLOUD SYSTEMS
A method of data processing is described. The method includes receiving, at a server host, a login request that includes a clear text password for an account. The method further includes retrieving, from a database, a payload stored in association with the account. The payload may indicate a hash value of a user configured password for the account, a hashing algorithm used for generation of the hash value, an initialization vector, and a key agreement public key associated with the account. The payload may be encrypted using a secret key derived from the key agreement public key and a private key provisioned to a key protection component of the server host. The method further includes transmitting a request that includes the payload and the clear text password. The method further includes receiving a response that indicates whether the clear text password corresponds to the user configured password.
Disclosed herein are system, method, and device embodiments for programmatically generating and deploying an integration application based on a natural language request without requiring any coding by a user. The application generator infers the sources, targets, connectors, operations, entities, and data mappings needed to build the requested integration application. An exposed web service or API may receive natural language input, determine the meaning of the request, and generates and deploys the resulting integration application without requiring any coding by a user.
Embodiments described herein provide a training framework for generative NLP models that operate on previously learnt knowledge from pretrained large language models. Specifically, to train an NLP model to generate a response to a user utterance (e.g., “resolve login issue”), document embeddings of support IT documents encoded by a pretrained LLM are fed to an NLP decoder together with a training dialogue (e.g., a dialogue between the chat agent on how to “resolve login issue”). The NLP decoder can thus be trained by a causal language modeling loss computed based on the predicted next token and the ground-truth token from the training dialogue.
Embodiments described herein provide a training framework for generative NLP models. Specifically, the training input, e.g., in the form of a sequence of tokens representing a user-agent dialogue, may be randomly masked for a few spans, which can be one or more tokens, one or more words, one or more sentences, or one or more paragraphs. These masked spans are replaced with their embeddings generated from pre-trained large language models are then used for training the NLP model.
An application server or other processing entity may receive, via a cloud-based platform, user input that may include at least one request for data. The application server may classify the user input into a first of a plurality of deterministic-stochastic spectrum classifications based on the user input and a probability of mapping the at least one request for data to at least one data location. The application server may retrieve the data from the at least one data location and based on the first deterministic-stochastic spectrum classification. The application server may transmit, based on the first deterministic-stochastic spectrum classification and the user input, an input to a large language model. The application server may present a response to the user input, where the response is based on a combination of an output of the large language model and the data retrieved from the at least one data location.
Some embodiments comprise integrating information from a social network into a multi-tenant database system. A plurality of information from the social network is retrieved, using a processor and a network interface of a server computer in the multi-tenant database system, wherein the plurality of information is associated with a message transmitted using the social network. Metadata related to the transmitted message is generated, using the processor. A conversation object is generated, using the processor, based on the plurality of information associated with the transmitted message and the metadata related to the transmitted message. The conversation object is then stored in an entity in the multi-tenant database system, using the processor of the server computer.
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
G06F 16/958 - Organisation ou gestion de contenu de sites Web, p. ex. publication, conservation de pages ou liens automatiques
G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
H04L 51/216 - Gestion de l'historique des conversations, p. ex. regroupement de messages dans des sessions ou des fils de conversation
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
G06F 16/21 - Conception, administration ou maintenance des bases de données
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
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
62.
DATA RETENTION IN GROUP-BASED COMMUNICATION PLATFORM
Techniques for modifying a period of time that data, associated with a characteristic, transmitted via a communication platform is retained are described. A data retention rule can include a first period of time for retaining data transmitted via the communication platform, in association with an organization. The first user can additionally establish a specific data retention rule associated with data associated with a particular characteristic. The specific data retention rule can include an instruction to store communications including the particular characteristic for a second time period that is different from the first time period associated with the data retention rule. The communication platform can receive data from a second user computing device associated with the second user of the organization. Based on a determination that the data is associated with the characteristic, the communication platform can store the data according to the data retention rule specified for such data.
Database systems and methods are provided for initiating an action at a database system by an instance of a native application at a client device coupled to the database system over a network. One method involves a service associated with a field service application at a client device monitoring a location of the client device to determine the location satisfies update criteria including a field of a data record associated with a service appointment when the location is within a threshold distance of a value for the field of the data record corresponding to an address for the service appointment. The service automatically provides an indication to automatically update a status field of the data record associated with the service appointment at the database system in accordance with a configuration associated with the instance of the field service application when the location of the client device satisfies the update criteria.
Embodiments described herein provide A method for training a neural network based model. The methods include receiving a training dataset with a plurality of training samples, and those samples are encoded into representations in feature space. A positive sample is determined from the raining dataset based on a relationship between the given query and the positive sample in feature space. For a given query, a positive sample from the training dataset is selected based on a relationship between the given query and the positive sample in a feature space. One or more negative samples from the training dataset that are within a reconfigurable distance to the positive sample in the feature space are selected, and a loss is computed based on the positive sample and the one or more negative samples. The neural network is trained based on the loss.
In some embodiments, a method selects a set of fields for a record in a database system. A set of prompt templates is retrieved that is associated with the set of fields. A prompt template comprises text and a variable. The method searches information that is associated with the record to determine context information and inserts the context information into the prompt templates to generate a set of prompts. The set of prompts is input into a generative model to output a generated result. The generative model is trained to output text based on prompts. The method outputs enrichment data for the record on an interface, wherein the enrichment data is based on the text of the generated result.
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 method and apparatus for collecting and supporting querying of multi-dimensional data pertaining to usage of software and/or hardware to service tenant requests in a multi-tenant cloud computing system where the multi-dimensional data is initially captured on a per request basis and recorded in objects of a first type that store data pertaining to a specific request, specific tenant, specific host and specific time. The objects of the first type are combined by time windows to form objects of a second type. The objects of a second type are stored in another system as separate text files. Responsive to a query for multi-dimensional data for a specific tenant that spans an interval of multiple time windows, the objects of the second type for the specific tenant and time interval are combined across all hosts to generate a query result, and the query result is returned.
A computing device receives a first user interaction with a graphical user interface (GUI) of the computing device. In response to the user interaction, the device sends, to a server system, a request for data corresponding to a first component of the GUI. The device initializes the first component concurrently with the sending. The device receives, from the server system, the data corresponding to the first component and corresponding metadata for the first component. The device generates the first component based on the corresponding metadata and at least a first subset of the received data and displays the first component in a first portion of the GUI. Concurrently with the generating and displaying, the device generates a second component of the GUI based on at least a second subset of the received data, and displays the second component simultaneously with the first component.
Database systems and methods are provided for augmenting a received conversational user input to provide an augmented conversational user input to a chatbot or other artificial intelligence (AI) system configurable to generate a personalized conversational response to the received conversational user input using the augmented conversational user input. One or more personal models or other user data associated with the user providing the received conversational user input are utilized to identify a relevant subset of data associated with the user for generating the augmented conversational user input, where the personalized conversational response is influenced by the relevant subset of data associated with the user.
Database systems and methods are provided for personalized automation agents. One method involves determining an action to be performed on behalf of a user, identifying a relevant subset of data in a database of the database system associated with the user based on the action, generating a personalized input prompt for an execution plan for the action using the using that subset of data, providing the personalized input prompt to a service configurable to generate a personalized conversational response, receiving the personalized conversational response comprising textual content indicative of a sequence of steps of the execution plan from the service, automatically executing the execution plan in accordance with the sequence using the service to perform the action with respect to a data record in the database, and automatically providing a response to the client device indicative of the action with respect to the data record.
G06F 40/35 - Représentation du discours ou du dialogue
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
Embodiments described herein provide systems and methods for training neural network based language models using human feedback. An existing (or generated) summary of a document is provided, and that summary may be used to generate a number of other summaries. A human annotator may reject the summary if there is any factuality issue with the summary. Summaries which are agreed to have no factuality problems are used as baseline summaries. Small atomic edits are made to the baseline summaries (e.g., replacing a single word or phrase) to create a group of summaries. Human annotators label each of these summaries as factual or not. The annotated summaries are used to train a summarization model and/or a factual detector model.
Apparatus and method for dynamic and persistent data sharing between cloud services. To address limitations in existing systems, resource provisioning and application deployment pipelines are configured with calls to share data using a configuration service. In some implementations, the configuration service includes an API, which is called by one or more stages of the resource provisioning pipeline to write configuration data in key-value pairs (e.g., data related to resource provisioning). One or more stages of the application deployment pipeline are configured with calls to access the configuration data. The stages then use the configuration data for application deployment. The configuration service manages the key-value store using versioning, repeatability, and immutability, to ensures that a configuration generated by any pipeline execution can be automatically re-used by another pipeline, at execution time. Thus, the configuration service is a dynamic, single source of truth for sharing pipeline configuration data.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
72.
SYSTEMS AND METHODS FOR CONTROLLABLE IMAGE GENERATION
Embodiments described herein provide a method of image generation. The method includes a fixed diffusion model, and a trainable diffusion model. The fixed diffusion model may be pretrained on a large training corpus. The trainable diffusion model may be used to control the image generation of the fixed diffusion model by modifying internal representations of the fixed diffusion model. A task instruction may be provided in addition to a text prompt, and the task instruction may guide the trainable diffusion model together with the visual conditions. The visual conditions may be adapted according to the task instruction. During training, a fixed number of task instructions may be used. At inference, unseen task instructions may be used by combining convolutional kernels of the visual condition adapter.
G06T 5/20 - Amélioration ou restauration d'image utilisant des opérateurs locaux
G06V 10/771 - Sélection de caractéristiques, p. ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
73.
SYSTEMS AND METHODS FOR RECONSTRUCTING A THREE-DIMENSIONAL OBJECT FROM AN IMAGE
Embodiments described herein provide a 3D generation system from a single RGB image of an object by inferring the hidden 3D structure of objects based on 2D priors learnt by a generative model. Specifically, the 3D generation system may reconstruct the 3D structure of an object from an input of a single RGB image and optionally an associated depth estimate. For example, a radiance field is formulated to depict the input image in one viewpoint of the target 3D object, based on which other viewpoints of the 3D object can be inferred. Based on the visible surface depicted by the input image, points between the reference camera and the surface are assigned with zero density, and points on the surface are assigned with high density and color equal to the corresponding pixel in the input image.
G06T 19/20 - Édition d'images tridimensionnelles [3D], p. ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
G06T 7/194 - DécoupageDétection de bords impliquant une segmentation premier plan-arrière-plan
G06T 7/50 - Récupération de la profondeur ou de la forme
H04N 13/279 - Générateurs de signaux d’images à partir de modèles 3D d’objets, p. ex. des signaux d’images stéréoscopiques générés par ordinateur les positions des points de vue virtuels étant choisies par les spectateurs ou déterminées par suivi
74.
SYSTEMS AND METHODS FOR RECONSTRUCTING A THREE-DIMENSIONAL OBJECT FROM AN IMAGE
Embodiments described herein provide a 3D generation system from a single RGB image of an object by inferring the hidden 3D structure of objects based on 2D priors learnt by a generative model. Specifically, the 3D generation system may reconstruct the 3D structure of an object from an input of a single RGB image and optionally an associated depth estimate. For example, a radiance field is formulated to depict the input image in one viewpoint of the target 3D object, based on which other viewpoints of the 3D object can be inferred. Based on the visible surface depicted by the input image, points between the reference camera and the surface are assigned with zero density, and points on the surface are assigned with high density and color equal to the corresponding pixel in the input image.
Techniques are described herein for a method of determining a similarity of each neuron in a layer of neurons of a neural network model to each other neuron in the layer of neurons. The method further comprises determining a redundant set of neurons and a non-redundant set of neurons based on the similarity of each neuron in the layer. The method further comprises fine tuning the set of non-redundant neurons using a first set of training data. The method further comprises training the set of redundant neurons using a second set of training data.
A computing device displays, in a user interface, data field icons corresponding to a plurality of data fields. Each of the data fields is associated with a respective object in an object model. In response to receiving (i) user selection of a first data field icon corresponding to a first data field, and (ii) placement of the first data field icon in a shelf region of the user interface, where the first data field is associated with a first object of the object model, the computing device generates a first data visualization and updates a visual characteristic of a subset of the data field icons from a first visual characteristic to a second visual characteristic. Each data field icon in the subset is associated with a second object of the object model. The data field icons in the subset are user-selectable independently of the first or second visual characteristic.
A computing device receives user input specifying a first dimension data field and a second dimension data field. The device constructs a dimension subquery according to characteristics of the first dimension data field, the second dimension data field, a first object to which the first dimension data field belongs, and/or a second object to which the second dimension data field belongs, including determining a join type for combining (i) first data rows that include data values of the first dimension data field and (ii) second data rows that include data values of the second dimension data field. The device constructs the dimension subquery according to the determined join type, and executes the dimension subquery to retrieve first tuples. The device constructs measure subqueries and executes the measure subqueries to retrieve second tuples. The device forms extended tuples, and generates and displays the data visualization according to the extended tuples.
Database systems and methods are provided for assigning structural metadata to records and creating automations using the structural metadata. One method of assigning structural metadata involves determining a candidate group of semantically similar conversations based on unassigned conversations, determining a clustering performance metric associated with the candidate group based on a relationship between the candidate group and a plurality of existing groups of semantically similar conversations, and when the clustering performance metric is greater than a threshold, automatically assigning one or more unassigned conversations to the candidate group based on the representative utterances associated therewith and automatically updating one or more associated records at a database system to include metadata identifying the candidate group.
A system receives an access token generated by a user performing authentication via an authentication device, for example, a smart card. The system obtains a personalized virtual machine assigned to the user. The system exchanges the access token for a temporary certificate having an expiry time. The system provides the temporary certificate that includes verifiable user identity to a personalized virtual machine. The system provides the user with access to the personalized virtual machine. The system allows the user to present verifiable user identity and connect to any of a plurality of systems without requiring the user to authenticate again using the authentication device. After the expiry time of the temporary certificate is exceeded, the system denies subsequent requests from the user to connect to any of the plurality of systems.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
80.
Creation and Consumption of Data Models that Span Multiple Sets of Facts
A computing device displays a first object icon representing a first object of a first data source and a second object icon, representing a second object of the first data source. The first object icon is connected to the second object icon via a first connector representing a relationship between the first object and the second object. In response to receiving a first user input to add a third object, the computing device displays a third object icon representing the third object. In response to receiving a second user input on the third object icon, in accordance with a determination that the second object and the third object include at least one common data field, the computing device displays a second connector, connecting the third object icon to the second object icon.
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
G06F 3/04812 - Techniques d’interaction fondées sur l’aspect ou le comportement du curseur, p. ex. sous l’influence de la présence des objets affichés
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
81.
Automatic structure selection and content fill within a group-based communication system
Media, methods, and systems for automatically selecting and prefilling template structures within a group-based communication system. A template structure is automatically selected based on a received user input. A prompt including one or more keywords from the user input is submitted to a content fill model. The content fill model returns a response with content output used to automatically populate one or more content fields within the template structure.
Techniques are disclosed that relate to truncating a subrange of records from a database table. A computer system receives a request to truncate the subrange of records. The request specifies a conditional expression that is usable to identify the subrange from other subranges of records of the database table. Before truncating the subrange of records, the computer system determines whether the subrange of records can be truncated from the database table with a single-record subrange truncate operation, regardless of a size of the subrange of records, based on whether the conditional expression satisfies a set of preconditions. Based on determining that the conditional expression satisfies those preconditions, the computer system performs the single-record subrange truncate operation that includes generating a truncate record that causes the subrange of records to be truncated from the database table.
Embodiments described herein provide a method of generating a multi-modal task output to a text instruction relating to inputs of multiple different modalities (e.g., text, audio, video, 3D). The method comprises receiving, via a data interface, a first input of a first modality, a second input of a second modality and the text instruction relating to the first and the second inputs; encoding, by a first multimodal encoder adapted for the first modality, the first input of the first modality into a first encoded representation conditioned on the text instruction; encoding, by a second multimodal encoder adapted for the second modality, the second input of the second modality into a second encoded representation conditioned on the text instruction; and generating, by a neural network based language model, the multi-modal task output based on an input combining the first encoded representation, the second encoded representation, and the text instruction.
Embodiments described herein provide a query-focused summarization model that employs a single or dual encoder model. A two-step approach may be adopted that first extracts parts of the source document and then synthesizes the extracted segments into a final summary. In another embodiment, an end-to-end approach may be adopted that splits the source document into overlapping segments, and then concatenates encodings into a single embedding sequence for the decoder to output a summary.
Systems, devices, and techniques are disclosed for a horizontally scalable system for managing container clusters. A monolithic management system may perform a first task on a first level of a cloud computing server system. The monolithic management system may perform a second task on a second level of a cloud computing server system. The monolithic management system may invoke instances of a container manager on a level of the cloud computing server system below the second level. The instances of the container manager may update container clusters of the cloud computing server system. The instances of the container manager may be associated with container clusters and the instances of the container manager update their associated container clusters.
A computer-implemented method for monitoring and control of a network traffic in a cloud server environment is disclosed. The method includes receiving network traffic at a cloud service account that includes a corresponding local security enforcement module configured to enforce security policies for data processed by the cloud service account and forwarding a part of the network traffic from the cloud service account to a centralized security monitoring hub that includes a hardware-based security component. The method also includes detecting, by the hardware-based security component, offending traffic that includes traffic from an unwanted source or with malicious content. The method further includes sending a notification of the offending traffic to the localized security enforcement module, by the centralized security monitoring hub, and responsive to the notification, implementing a security enforcement strategy in the cloud service account based on the security policy, by the corresponding localized security enforcement module.
A computing platform configurable to allow users to graphically represent relationships between database records may be provided to a plurality of organizations. A request to generate a customizable visualization for graphically representing relationships between a root database record and child database records in a customizable format may be processed. Graphical representations of the root database record and the child database records may be caused to be displayed in accordance with the customizable format.
G06F 16/26 - Exploration de données visuellesNavigation dans des données structurées
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
88.
CONTENT-OBLIVIOUS FRAUDULENT EMAIL DETECTION SYSTEM
A system supporting one or more machine learning models may receive, via a cloud-based platform that supports a multi-tenant system, metadata associated with a set of electronic communication messages for a tenant of the multi-tenant system. The system may normalize the metadata by extracting fields of the metadata into a format readable by the machine learning model to identify a set of fraudulent users associated with the set of electronic messages. The system may utilize the machine learning model to identify the set of fraudulent users based on executing a set of detection models and performing pattern matching between a set of previously authenticated user activity logs and a set of newly generated user activity logs in the metadata. Upon detection of the set of fraudulent users, the system may generate and transmit a report indicating the set of fraudulent users and the respective electronic message corresponding to the respective fraudulent user.
A computing device receives a natural language input specifying a first search term and a second search term, directed to a dataset. The device (i) executes, for the first search term, first queries against a search index to retrieve a first set of labeled trend events; and (ii) executes for the second search term, second queries against the search index to retrieve a second set of labeled trend events. Each labeled trend event has a respective chart identifier. The device constructs sequences of labeled trend events based on the retrieved sets of labeled trend events, assigns each sequence into groups according to the respective chart identifier, and ranks the groups. The device retrieves data corresponding to a subset of line charts having the respective chart identifiers of the ranked groups, generates the subset of line charts, and displays one or more line charts of the subset.
System, method and interface for interpreting natural language comparisons during visual analysis are provided. The system includes obtaining a natural language utterance that includes a comparison query and a dataset of attributes and values relevant to interpreting the comparison query. The system also includes interpreting the natural language utterance based on the dataset using multi-step chain-of-thought reasoning prompting to generate a response to the comparison query. The system also includes generating a visualization based on the response and a text summary describing the multi-step chain-of-thought reasoning for the comparison query.
A computing device receives user interaction with a portion of a data visualization that is displayed on the computing device. In response to receiving the user interaction, the computing device generates a first prompt that includes (i) a first parameter specifying a visualization type of the data visualization, (ii) a second parameter specifying a data array corresponding to data marks of the data visualization, and (iii) a third parameter specifying a title of the data visualization. The computing device inputs the first prompt into a large language model (LLM) and obtains, from the LLM, a text narrative for the portion of the data visualization. The device generates a second prompt in accordance with the text narrative, inputs the second prompt into the LLM, and obtains from the LLM a title for the text narrative. The device generates a self-contained story based on the text narrative and the title.
A computing device receives a natural language input specifying search terms directed to a dataset. The device parses the input into tokens and executes queries against a search index to retrieve a plurality of labeled trend events. Each labeled trend event has a respective chart identifier. The device determines a respective composite score for each labeled trend event and individually assigns each labeled trend event to a respective group. For each group, the device sorts the respective labeled trend events within the respective group according to respective composite scores, determines a respective final score for each group, and ranks the groups according to one or more determined final scores. The device retrieves data corresponding to a first subset of line charts having the respective chart identifiers of the ranked groups, generates the first subset of line charts, and displays one or more line charts of the first subset with annotation.
Methods, apparatuses, and computer-program products are disclosed. A method may include activating, in a processing entity, a connection agent and a manifest, the manifest including a data signature and an endpoint type that are associated with the processing entity. The method may include generating, based on the data signature, the endpoint type, or both, one or more load balanced dynamic endpoints configured for access, by the connection agent and via one or more application programming interfaces, to a repository including access configurations for the processing entity. The method may include retrieving, via the one or more load balanced dynamic endpoints and from the repository, one or more first access configurations of the plurality of access configurations and the one or more first access configurations may be associated with the processing entity.
Techniques are disclosed relating to storing location information about storage nodes in cookies. A cloud-based service may send location requests to an orchestration service that instantiated storage nodes included in a storage cluster of the cloud-based service. The cloud-based service may receive location information that identifies in which computer zone that a given storage node is located. The cloud-based service may store the location information in cookies at a metadata store that is shared among the storage nodes. The cloud-based service may receive, from a client node, a search request to identify ones of the storage nodes that store particular data. The cloud-based service may return a set of cookies corresponding to identified storage nodes. The set of cookies may enable the client node to determine whether there is a storage node that stores the particular data and is within the same computer zone as the client node.
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
Online meeting software typically generates a flow of data. A server system is configured to receive the flow of data, which may include metadata. The data may include metadata of online meetings. Different types of metadata are generated by online meetings. Such different types of metadata are provided in different patterns. Different types of metadata are provided throughout the online meeting session or at various points of the session and are provided to various different elements of the server system. The various different metadata received are then parsed and certain specific metadata elements are identified to match the different metadata streams.
System and methods are presented for configuring and managing metadata switches and platform licenses in a distributed system. Using metadata switches, a platform license can be developed for a software product without the need for an engineer to develop the platform license by hand. A software application depot can be used to configure metadata switches that provide configuration information for a particular aspect of the software product and, when associated to a platform license that utilizes metadata switches, generate an accessible platform license for use by tenant organizations.
Systems and methods are provided for parsing, at a server, a design file including code for a user interface, where the code is readable by the server into a tree representation having nodes, the nodes represent design elements of the user interface and includes one or more design properties, a unique identifier, and references to child elements. The server traverses the tree representation and comparing the design elements of the tree representation to a set of factors to determine when the design elements and meet a criteria to be a subcomponent for one or more components of the code of the design file. The server adds the design elements to a list of subcomponent candidates that meet at least one of the set of factors to be a subcomponent. The server generates a tree structure for the one or more components using the list of subcomponent candidates.
Techniques for locating information previously shared via a virtual space of a communication platform are disclosed herein. For example, the communication platform may receive, at the virtual space associated with a first user and a second user, a message containing one or more keywords. Based at least in part on receiving an indication from one of the first user or the second user, the communication platform may determine that the message is a searchable message. In some examples, the communication platform may then receive, from a third user of the communication platform unassociated with the virtual space, a request to access one or more messages associated with a keyword of one or more keywords. Based at least in part on receiving the request, the communication platform may cause presentation, to the third user, of at least a portion of the searchable message.
Disclosed are examples of systems, apparatus, methods and computer program products for sharing and publishing files. In one aspect, the database system can maintain a user database, a file database and a library. The database system can receive a first request initiated by a first user to share a first file with one or more second users and, responsive to the first request, enable a second set of one or more permissions for each of the second users. The database system also can receive a second request initiated by the first user to publish the first file to the library and, responsive to the second request, publish the first file to the library. The database system additionally can restrict access to the published file based on permissions associated with the library.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
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
Techniques are disclosed that relate to manipulating a chain of database objects without locking the chain. A computer system may maintain a chain that orders a set of database objects stored in a cache of the computer system. The computer system may receive a set of requests to perform database transactions. Based on those received set of requests, the computer system may determine to perform a plurality of chain operations that involve modifying the chain. The computer system may perform two or more of the plurality of chain operations at least partially in parallel using a set of atomic operations without acquiring a lock on the chain.
