An example embodiment may involve receiving a representation of a parameter of a first clustering model (such as the cluster centroid in a k-means clustering model) where the representation of the parameter is associated with training data in accordance with a first set of software libraries. Possibly based on the parameter, a second clustering model in accordance with a second set of software libraries could be generated. As a consequence, the second clustering model could make a prediction result based on a received prediction request.
Example embodiments may include: obtaining a design specification of a graphical user interface (GUI), wherein the design specification is compatible with a GUI design tool and includes a layout of design artifacts; generating, through use of a component mapper, respectively corresponding GUI components for the design artifacts in accordance with the layout; populating, based on properties of the design artifacts, respectively corresponding properties of the GUI components; and generating, based on the layout, the GUI components, and their corresponding properties, a deployable software implementation of the GUI.
An example implementation may involve: obtaining a textual prompt; based on the textual prompt, generating, via at least a natural language processing (NLP) model, relational data indicating respective relationships between components of a graphical user interface (GUI); and generating, based on the relational data, an implementation-specific representation of the GUI that is compatible with a GUI design tool.
A specification of a user interface for a development of a web application is received. Program components to be executed by a client to load the user interface of the web application are identified. Metadata associated with the identified program components is stored in a database. Webpage computer code to be executed by the client to load the user interface is generated, wherein execution of the webpage computer code results in determining, based on the generated webpage computer code, satisfaction of an achievement of a threshold loading state, wherein the threshold loading state characterizes the user interface executing on the client based on execution progresses of the program components. The webpage computer code is provided to the client.
A description of a desired computer workflow is obtained. Based on the description of the desired computer workflow, a set of prospective components from a plurality of components is selected. A prompt is generated using the description of the desired computer workflow and the set of prospective components. Based on providing the prompt to a large-language-model, at least a portion of code associated with the desired computer workflow is generated.
A description of a desired computer workflow is obtained. Based on the description of the desired computer workflow, a set of prospective components from a plurality of components is selected. A prompt is generated using the description of the desired computer workflow and the set of prospective components. Based on providing the prompt to a large-language-model, at least a portion of code associated with the desired computer workflow is generated.
Configuration management persistent storage contains entries representing configuration items and relationships between pairs of the configuration items. Event management persistent storage contains entries representing alert records. Change request persistent storage contains change records respectively referring to changes made to the configuration items. One or more processors may be configured to: extract, from a particular alert, a particular configuration item referred to therein that is associated with a particular problem; determine, by way of the relationships, a set of configuration items within a topological distance of the particular configuration item; identify, by way of the change records, one or more change requests that refer to any of the set of configuration items; and calculate root cause scores for the one or more change requests, wherein the root cause scores respectively represent estimations of impacts that the changes of the one or more change requests had on causing the particular alert.
H04L 41/0631 - Management of faults, events, alarms or notifications using root cause analysisManagement of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
In the present application, a method and a system for providing licensing information are disclosed. A request regarding software licensing associated with one or more software products for one or more computing devices is received. Information associated with the one or more computing devices is obtained. One or more software licensing guides associated with the one or more software products are obtained. A prompt using at least a portion of the request, at least a portion of the obtained information, and at least a portion of the one or more software licensing guides is generated. A response is generated using an artificial intelligence (AI) model based on the prompt. At least a portion of the response is outputted.
A method including determining that a data quality value associated with an input to an artificial intelligence (AI) model, characterized by a plurality of features, satisfies a first threshold value. The method also includes identifying a particular feature of the plurality of features that is associated with the data quality value and determining a contribution level that indicates a relative contribution of the particular feature to an output of the AI model. Further, the method includes determining a risk score for the particular feature based on the contribution level and outputting an alert, identifying one or more models affected by the particular feature, in response to the risk score satisfying a second threshold value, wherein outputting the alert comprises outputting the alert to an external platform for display via a user interface.
G06F 21/52 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure
1. A connection request is received from a client to establish a first connection associated with a second connection of a virtual private network for selective network communications of a first group of one or more applications of the client. Network communications of a second group of one or more applications different from the first group of one or more applications of the client are to be routed outside the virtual private network. The second connection of the virtual private network is established between a proxy and a virtual private network server. The first connection is established between the proxy and the client. A network packet received from the client via the first connection is routed to the virtual private network server via the second connection of the virtual private network.
Techniques described herein relate to using one or more machine learning models to identify values of variables to be used in application commands for execution. For example, the one or more machine learning models may identify one or more values of variables that are used to replace a different set of one or more values of variables in an application command before executing the command on a host.
In various embodiments, a process for determining metrics including resource expenditures of a digital service includes discovering a plurality of configuration items of a computing infrastructure. The process includes identifying a subset of the plurality of configuration items utilized to provide a digital service, obtaining a plurality of resource expenditures respectively associated with at least a portion of the plurality of configuration items, and associating a subset of the plurality of resource expenditures with the subset of the plurality of configuration items. The process includes aggregating the subset of the plurality of resource expenditures to generate a metric of the digital service.
H04L 41/0826 - Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability for reduction of network costs
H04L 41/0896 - Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities
13.
REAL TIME UPDATES OF MULTIPLE VIEWS OF A COMPUTER PROCESS FLOW
An indication of a user interaction with a user interface element of a user interface is received, wherein the user interface enables generation of a computer process flow. A data change action associated with the user interaction is determined. The data change action is validated. Based on the data change action, a computer process flow state associated with the computer process flow is updated to reflect the data change action. In response to the computer process flow state being updated to reflect the data change action, one or more behaviors based on the data change action are triggered.
A specification of a condition to trigger detection of a specific issue of an information technology component is received. Computer usage data is collected via one or more computer agents on one or more clients. A portion of the computer usage data that satisfies the condition of the specific issue is identified. A prompt based on the portion of the computer usage data is determined. Using a generative machine learning model, a solution to the specific issue based on the prompt is generated.
An embodiment may involve obtaining a representation of portions of source code and the portions of the source code may be associated with a component of a software application, generating a code string based on the representation of portions of the source code, generating a hash digest based upon the code string, determining, based on the hash digest and a previous hash digest, that the portions of the source code satisfy a change condition, and in response to determining that the change condition is satisfied, updating the component of the software application in relation to the portions of the source code.
A plurality of correlations is determined including by applying a machine learning model to a first plurality of features extracted from a plurality of information technology and operations management alerts and information technology service management reporting data. Each correlation of the plurality of correlations is between a corresponding one of the plurality of information technology and operations management alerts and at least one corresponding portion of the information technology service management reporting data. The information technology service management reporting data includes at least one urgency indicator. A prioritized list of information technology and operations management alerts is generated based at least in part on the determined plurality of correlations and the at least one urgency indicator. The prioritized list of information technology and operations management alerts is organized based at least in part on relative priorities of the alerts.
H04L 41/0631 - Management of faults, events, alarms or notifications using root cause analysisManagement of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
H04L 41/069 - Management of faults, events, alarms or notifications using logs of notificationsPost-processing of notifications
A system for root cause analysis based on process optimization data is provided. The system receives log data associated with a first trace between a first activity and a second activity of a process. The system further determines a state of inefficiency between the first activity and the second activity based on the received log data. The system further applies a first machine learning (ML) model on the received log data. The system further determines a first label and a first value to be associated with the first trace of the process based on the application of the first ML model. The system further generates presentation data associated with the determined state of inefficiency of the first trace based on the determination of the first label and the first value and further transmits the generated presentation data on a user device.
An implementation may involve: obtaining a representation of a network event relating to a network, wherein the network enables operation of a plurality of services each involving one or more computing devices or software applications; obtaining information associated with the network event, wherein the information identifies one of the computing devices or the software applications; based on the information, identifying a subset of services of the plurality of services based on determining that each of the subset of services satisfies an impact criterion with respect to the network event, wherein the subset of services are associated with candidate service maps that were generated by a machine learning process; and providing an indication that the subset of services are related to the network event.
H04L 41/0631 - Management of faults, events, alarms or notifications using root cause analysisManagement of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
H04L 41/0604 - Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
21.
ROOT CAUSE AND IMPACT DETERMINATION BASED ON AUTOMATED SERVICE IDENTIFICATION
An implementation may involve: obtaining a representation of a network event relating to a network, wherein the network enables operation of a plurality of services each involving one or more computing devices or software applications; obtaining information associated with the network event, wherein the information identifies one of the computing devices or the software applications; based on the information, identifying a subset of services of the plurality of services based on determining that each of the subset of services satisfies an impact criterion with respect to the network event, wherein the subset of services are associated with candidate service maps that were generated by a machine learning process; and providing an indication that the subset of services are related to the network event.
Time-series data is received. Using an identifier of the time-series data, contextual reference anomaly detection parameters are identified from a repository. A data trend of the time-series data is classified. Based on the classified data trend, a type of model to be generated for the time-series data is selected and a model having generated anomaly detection parameters is generated. A history of anomaly detection parameters determined for the time-series data is identified, and the generated anomaly detection parameters are adjusted based on the contextual reference anomaly detection parameters and the history of anomaly detection parameters.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
Various implementations disclosed herein include detecting when a prioritized change task is queued, modifying any related change tasks to have the same priority, and executing the queue according to the modified priorities of the related change tasks.
Techniques described herein are related to updating streaming application software. For example, data from the streaming application software are transformed into a format for an engine to generate one or more results. The one or more results may comprise information related to the data from the streaming application software.
H04N 21/4722 - End-user interface for requesting content, additional data or servicesEnd-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content for requesting additional data associated with the content
G06F 16/953 - Querying, e.g. by the use of web search engines
G06F 40/40 - Processing or translation of natural language
25.
Reduced Memory Utilization for Data Analytics Procedures
An example embodiment may involve a main database; a main memory; and one or more processors configured to: retrieve, by a data collector application, records from the main database, wherein the data collector application includes an embedded database; aggregate, by the data collector application, values in the records relating to a key performance indicator (KPI) to form partial KPI data stored in one or more blocks of the main memory; determine, by the data collector application, that utilization of the main memory exceeds a pre-defined threshold; in response to the utilization of the main memory exceeding the pre-defined threshold, write, by the data collector application, the partial KPI data to a row of the embedded database; and release, by the data collector application, the one or more blocks of the main memory used to store the partial KPI data.
The present disclosure relates to a data augmentation system and method that uses a large pre-trained encoder language model to generate new, useful intent samples from existing intent samples without fine-tuning. In certain embodiments, for a given class (intent), a limited number of sample utterances of a seed intent classification dataset may be concatenated and provided as input to the encoder language model, which may generate new sample utterances for the given class (intent). Additionally, when the augmented dataset is used to fine-tune an encoder language model of an intent classifier, this technique improves the performance of the intent classifier.
A controller computing device may include one or more processors and memory containing controller data representing controller computing device capabilities. The one or more processors may be configured to transmit on a first instance of a request-response protocol, a controller request, including the controller data, to an agent computing device. The controller computing device may then receive, from the agent computing device, an agent request on a second instance of the request-response protocol. The agent request may include agent data representing agent computing device capabilities. The controller computing device may store the agent data in the memory, and transmit on the second instance of the request-response protocol, to the agent computing device, a controller response acknowledging receipt of the agent request. The controller computing device may then receive on the first instance of the request-response protocol from the agent computing device, an agent response acknowledging receipt of the controller request.
Embodiments are provided herein that include receiving, from a natural language model and based on a first textual prompt, a first output that represents a database entry, wherein the database entry includes a plurality of elements; obtaining a selection of a subset of the plurality of elements; determining a second textual prompt based on the selected subset of the plurality of elements; and generating, via the natural language model, a second output based on the second textual prompt, wherein the second output represents an update to the database entry. These embodiments provide for faster generation of catalog items or other types of database entries using generative natural language models in a manner that exhibits reduced memory requirements, computational cost, and/or amounts of training data.
A computer workflow including computer managed activities organized in an execution ordering and one or more conditional branching decision nodes is specified. One or more activity execution conditions associated with at least one of the plurality of computer managed activities are determined, wherein the one or more activity execution conditions comprise at least one branch execution condition associated with at least one of the one or more conditional branching decision nodes. The computer workflow is executed. Based on at least one of the one or more activity execution conditions, it is determined whether a condition to start an execution of the at least one of the plurality of computer managed activities is satisfied. Based on the at least one branch execution condition, it is dynamically determined whether the at least one of the plurality of computer managed activities is to be visualized.
In various embodiments, a process for providing a computer program specification builder includes receiving a specification of requirements to be implemented for a computer program. Based on the specification of requirements, the process automatically generates a plurality of stories, wherein each story included in the plurality of stories specifies a desired goal associated with a desired feature for the computer program. The process provides a computer user interface to manage and track implementation progress of the plurality of stories associated with the specification of requirements.
In various embodiments, a process for providing a configuration data analyzer includes ingesting a first configuration of a first deployment of an application service and ingesting a second configuration of a second deployment of the application service. The process includes comparing organizational structures and elements of the first configuration against the second configuration. The process includes providing, via a user interface, an interactive view indicating differences between the organizational structures and the elements of the first configuration and the second configuration for the first and second different deployments of the application service.
An update request is initiated to update a record of a management system. In response to the request, the record is updated in a storage of the management system. In response to the request, a digest of the update request is generated and the digest is signed. The signed digest is recorded on a blockchain different from the storage of the management system.
H04L 9/00 - Arrangements for secret or secure communicationsNetwork security protocols
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
In various embodiments, a process for providing a configuration data analyzer includes ingesting a first configuration of a first deployment of an application service and ingesting a second configuration of a second deployment of the application service. The process includes comparing organizational structures and elements of the first configuration against the second configuration. The process includes providing, via a user interface, an interactive view indicating differences between the organizational structures and the elements of the first configuration and the second configuration for the first and second different deployments of the application service.
A computer workflow including computer managed activities organized in an execution ordering and one or more conditional branching decision nodes is specified. One or more activity execution conditions associated with at least one of the plurality of computer managed activities are determined, wherein the one or more activity execution conditions comprise at least one branch execution condition associated with at least one of the one or more conditional branching decision nodes. The computer workflow is executed. Based on at least one of the one or more activity execution conditions, it is determined whether a condition to start an execution of the at least one of the plurality of computer managed activities is satisfied. Based on the at least one branch execution condition, it is dynamically determined whether the at least one of the plurality of computer managed activities is to be visualized.
A transcript of at least a portion of a discussion associated with a computer program development is received. At least a portion of the transcript is automatically analyzed to automatically identify a computer program development project associated with the discussion and managed by a computer program development project management software. At least a portion of the transcript and contextual information of the computer program development project tracked using the computer program development project management software is provided to a large language model to automatically generate a specification of a task of the computer program development discussed during the discussion. Based on the generated specification of the task, the task is automatically tracked using the computer program development project management software.
In various embodiments, a process for proactive problem detection using alert data and incident data includes receiving machine-generated alerts of an information technology environment and receiving user-specified incidents of the information technology environment. The process includes combining the machine-generated alerts and the user-specified incidents into a combined group, clustering elements of the combined group into one or more component clusters, and determining a relative priority between the one or more component clusters based on one or more properties of corresponding elements belonging to the one or more component clusters.
An identification of one or more computer-generated records in a first schema is received. A specification of a second schema different from the first schema is received. A prompt associated with mapping one or more fields and values of the first schema to corresponding one or more fields and values of the second schema is automatically generated for a pre-trained large language model. At least the specification of the second schema and the automatically generated prompt are provided to the pre-trained large language model. A result of the pre-trained large language model is automatically analyzed to determine the mapping between the first schema and the second schema. The determined mapping is used to manage in the second schema, a new computer-generated record received in the first schema.
Embodiments are provided herein that improve the automated generation and auditing of data-bearing reports. These embodiments include using metadata to represent the sources of data to be used to insert information at various locations within a report or other text record. To populate the report, the metadata is used to determine a source to query for the relevant information, a location to insert the relevant information within the text, and optionally a calculation to perform on the source data in order to determine the relevant information. These embodiments result in improved data security and reduced bandwidth and storage cost while also improving report accuracy and allowing for repeated report information updates as the underlying source data is accumulated and/or updated.
An example embodiment may involve determining that a configuration item has failed identification, wherein the configuration item represents computing hardware or software associated with a network; based on the configuration item failing identification, performing a reconciliation procedure, wherein the reconciliation procedure modifies an attribute of the configuration item; determining that the configuration item as modified passes identification; and writing, to a database, the configuration item as modified.
A method includes determining a definition of a capability, where the definition indicates an input, an output, and an operation performed by the capability on the input to generate the output. The method also includes determining models configured to provide the capability, providing the definition of the capability to an application builder configured to provide a model independent representation of the capability, and determining a mapping that indicates, for each respective model of the models, one or more attribute values that cause the respective model to be executed to provide at runtime the capability to a software application defined using the application builder, where the mapping is unmodifiable by the application builder. The method further includes, in response to reception from the software application of a request to provide the capability, providing the capability to the software application in accordance with the mapping.
An example embodiment may involve determining that a configuration item has failed identification, wherein the configuration item represents computing hardware or software associated with a network; based on the configuration item failing identification, performing a reconciliation procedure, wherein the reconciliation procedure modifies an attribute of the configuration item; determining that the configuration item as modified passes identification; and writing, to a database, the configuration item as modified.
H04L 41/0823 - Configuration setting characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability
H04L 41/12 - Discovery or management of network topologies
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
43.
CONCEPT SYSTEM FOR A NATURAL LANGUAGE UNDERSTANDING (NLU) FRAMEWORK
A natural language understanding (NLU) framework includes a concept system that performs concept matching of user utterances. The concept system generates a concept cluster model from sample utterances of an intent-entity model, and then trains a machine learning (ML) concept model based on the concept cluster model. Once trained, the concept model receives semantic vectors representing potential concepts extracted from utterances, and provides concept indicators to an ensemble scoring system. These concept indicators include indications of which concepts of the concept model that matched to the potential concepts, which intents of the intent-entity model are related to these concepts, and concept-relationship scores indicating a strength and/or uniqueness of the relationship between each concept-intent combination. Based on these concept-related indicators, the ensemble scoring system may determine and apply an ensemble scoring adjustment when determining an ensemble artifact score for each of the artifacts extracted from an utterance.
A computer program component configured to collect configuration item data from information technology resources of an air-gapped network for an information technology configuration management database is provided. Configuration item data collected from the information technology resources of the air-gapped network is obtained using the provided computer program component, wherein the obtained configuration item data is physically transferred between a device within the air-gapped network and a device outside the air-gapped network at least in part via a portable physical storage medium, and the collected configuration item data has been reviewed and filtered within the air-gapped network prior to being physically transferred via the portable physical storage medium. The obtained configuration item data is imported to the information technology configuration management database outside the air-gapped network. Information technology management services are provided for the air-gapped network using the imported configuration item data stored outside the air-gapped network.
An online cloud application platform for global navigation of multiple online cloud-based applications is provided. The online cloud application platform is configured to provide a plurality of online cloud-based applications. While providing a current application among the plurality of online cloud-based applications, an event identifying a function request decoupled from a static navigation route is received via a cross-application routing handler. Based on a set of dynamically modifiable configuration data of the online cloud application platform, which application among the plurality of online cloud-based applications to handle the function request is dynamically determined. Based on the set of dynamically modifiable configuration data of the online cloud application platform, a corresponding dynamically determined cross-application navigation route to handle the event is determined. The dynamically determined cross-application navigation route is provided within a context of the current application among the plurality of online cloud-based applications.
An embodiment may involve obtaining a configuration data component that is associated with a first configuration data library and the configuration data component may indicate one or more parameters of a software service, providing a request for the configuration data component to be used in a second configuration data library, and linking the configuration data component with the second configuration data library such that the configuration data component is used, across the first configuration data, library and the second configuration data library.
H04L 41/0853 - Retrieval of network configurationTracking network configuration history by actively collecting configuration information or by backing up configuration information
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
Online interaction data between one or more clients and a database server communicating via a network is received. The online interaction data is used to train a data protection machine learning model for detecting a malicious attack. An offline interface for accessing a database data structure is provided, wherein the offline interface is configured to apply the data protection machine learning model trained using the online interaction data to protect the database data structure accessed via the offline interface.
An embodiment may involve obtaining a configuration data component that is associated with a first configuration data library and the configuration data component may indicate one or more parameters of a software service, providing a request for the configuration data component to be used in a second configuration data library, and linking the configuration data component with the second configuration data library such that the configuration data component is used across the first configuration data library and the second configuration data library.
A method for storing and retrieving time-series data in a time-series database is disclosed. A digest associated with a document is obtained. The document is indexed in a search index including a plurality of index entries, wherein the plurality of index entries includes a first index entry having a key based on the digest and a value associated with a storage location of the document, and wherein each of the plurality of index entries has a common fixed key size and a common fixed value size. A search query is received. Whether any entry in the search index matches the search query is determined, including by searching at least a portion of the plurality of index entries of the search index addressable using an offset based on the common fixed key size and the common fixed value size.
A correlation request is received at a first application instance from a second application instance for a data record of the first application instance. A correlation index is updated with a directional correlation entry in response to a determination that the correlation request is approved. In response to determining that the data record has been modified, the updated correlation index is utilized to determine that the modified data record is to be provided for correlation to the second application instance. A version of the modified data record is provided to the second application instance.
H04L 67/53 - Network services using third party service providers
H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
Data from a plurality of data sources is received. A knowledge graph is generated using the received data to discover user relationships between elements of the data from the plurality of data sources. A query associated with a workflow is received from a user. Using an application programming interface, the knowledge graph is queried for data associated with the user and the query. A recommendation associated with the workflow is determined by analyzing a result of the query of the knowledge graph.
A query is received. The query is executed at a database instance that supports a first database service and a second database service. Based on historical performance data, it is determined that an optimal execution path of the query includes splitting the query across the first database service and the second database service. In response to determining the optimal execution path, the query is split into a first component query in a first query language compatible with the first database service and a second component query in a second query language compatible with the second database service. The first component query is executed at the first database service. The second component query is executed at the second database service.
In the present application, a system and method for storing and retrieving time-series data in a time-series database are disclosed. A data stream collected at a periodic collection time interval is stored. The stored data stream is indexed in an index, including by storing in the index a representative index entry corresponding to a plurality of data elements of the stored data stream collected during a period of time longer than the periodic collection time interval of the data stream.
In various embodiments, a process for providing an automation discovery platform includes obtaining training data indicating conversation utterances and labels that are associated with the conversation utterances, where each of the labels of at least a subset of the labels corresponds to a virtual agent automation topic. The process includes obtaining a language machine learning model, where the language machine learning model has been trained to a first trained state using unlabeled data. The process includes updating the language machine learning model from the first trained state to a second trained state by applying the training data to the language machine learning model, where updating the language machine learning model includes generating an automation discovery model configured to provide outputs corresponding to virtual agent automation opportunities.
An example embodiment may involve: receiving a request relating to a plurality of parallelizable jobs; obtaining a schedule of worker thread availability with respect to a fractionalized task distributor, wherein the fractionalized task distributor is operable according to a predefined number of worker threads; assigning, to the fractionalized task distributor, a plurality of worker threads for execution of the plurality of parallelizable jobs, wherein the plurality of worker threads is based on the predefined number of worker threads, and wherein assigning the plurality of worker threads is according to the schedule and one or more tasks not included in the plurality of parallelizable jobs; and directing the fractionalized task distributor to execute the plurality of parallelizable jobs via the plurality of worker threads.
A method includes obtaining an indication of a user interface (UI) component of a user interface, and determining an association between the UI component and a dynamic identifier. The method also includes, based on determining the association, determining one or more static properties of one or more parent UI components of the UI component, and generating a component selector for the UI component based on the one or more static properties. The method further includes outputting the component selector for the UI component.
An example embodiment may involve: receiving a. request relating to a plurality of parallelizable jobs; obtaining a schedule of worker thread, availability with respect to a fractionalized task distributor, wherein the fractionalized task distributor is operable according to a predefined number of worker threads; assigning, to the fractionalized task distributor, a plurality of worker threads for execution of the plurality' of parallelizable jobs, wherein the plurality' of worker threads is based on the predefined number of worker threads, and wherein assigning the plurality of worker threads is according to the schedule and one or more tasks not included in the plurality of parallelizable jobs; and directing the fractionalized task distributor to execute the plurality of parallelizable jobs via the plurality of worker threads.
A method includes obtaining a topic of a document and an information source associated with the document. The method also includes generating, using a generative machine learning (ML) model, the document based on the topic and the information source. The method additionally includes identifying a query that is associated with the topic and determining, using a validation model, that the query is not addressed by the document. The method yet additionally includes, based on determining that the query is not addressed by the document, generating an updated document using the generative ML model based on the topic, the information source, and the query. The method further includes determining, using the validation model, that the query is addressed by the updated document, and outputting the updated document.
The present disclosure relates to a method, medium and system for receiving a request to customize display of an application, wherein the request specifies a first component characteristic associated with a first user interface component the application. The disclosure further includes identifying, based on the first component, a second component characteristic associated with a second user interface component of the application, and updating, based on a spatial or hierarchical relationship between the first user interface component and the second user interface component, the second user interface component characteristic so that the second user interface component characteristic has at least a predefined contrast ratio with the first user interface component.
A chat message is received. A topic identifier that identifies a topic of the chat message is obtained. Based on the topic identifier, a first virtual agent of a plurality of virtual agents is selected according to a determination that the first virtual agent is configured to implement a first workflow that is associated with the topic. The chat message is processed via the first virtual agent.
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 40/103 - Formatting, i.e. changing of presentation of documents
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
61.
SECURITY-PRESERVING GENERATION AND PERFORMANCE OF CLOUD ACTIONS
Methods are provided for leveraging generative artificial intelligence to generate commands and other aspects of modification actions that can be used by users to create, delete, and/or modify virtual machines in a cloud computing environment or to interact with aspects of some other computing environment. The generation and execution of such modification actions can implicate extensive computational and other requirements and may also require the performance of multiple tasks requiring differing levels of access credential. For example, updating a database to reflect changes made to a computing environment by execution of a modification action may require a higher level of credential than performing the changes themselves. The action generation and execution methods described herein allow users with such lower-level credentials to enact such changes while also performing associated database updates or other higher-credential actions.
H04L 41/40 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using virtualisation of network functions or resources, e.g. SDN or NFV entities
H04L 41/28 - Restricting access to network management systems or functions, e.g. using authorisation function to access network configuration
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
A system and method for encrypting portions of data for storage in a remote network have been provided. The system comprises a memory with instructions executable by a processor to receive data for forwarding to a server device, wherein the received data comprises an indication of one or more portions of the received data to be encrypted; identify a portion comprising the one or more portions of the received data based at least in part on the indication; encrypt the identified portion of the data; generate a payload that comprises the encrypted portion and one or more unencrypted portions of the received data; and transmit, to the server device, the payload.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04W 12/088 - Access security using filters or firewalls
63.
Security-Preserving Generation and Performance of Cloud Actions
Methods are provided for leveraging generative artificial intelligence to generate commands and other aspects of modification actions that can be used by users to create, delete, and/or modify virtual machines in a cloud computing environment or to interact with aspects of some other computing environment. The generation and execution of such modification actions can implicate extensive computational and other requirements and may also require the performance of multiple tasks requiring differing levels of access credential. For example, updating a database to reflect changes made to a computing environment by execution of a modification action may require a higher level of credential than performing the changes themselves. The action generation and execution methods described herein allow users with such lower-level credentials to enact such changes while also performing associated database updates or other higher-credential actions.
Data communication between a plurality of computer processes are tracked. The data communication between the plurality of computer processes are analyzed to classify relationships between the plurality of computer processes. Based at least in part on the classified relationships between the plurality of computer processes, an existence of a service provided by a functional group of computer processes included in the plurality of computer processes are automatically discovered. A visual map of the discovered service is generated.
A method includes obtaining a request for data, and obtaining a security policy indicator that indicates a security policy. The security policy may include access conditions that define data access according to one or more attribute values of an attribute. The method also includes determining an attribute value of the attribute based on the request, and identifying a subset of the data based on the attribute value. The subset of the data may satisfy the security policy. The method further includes providing the subset of the data to a software application.
A discovery application on a computing system is provided. The discovery application receives a user input, which is for discovery of resources associated with a cloud operating system of a cloud computing system. The user input includes an authentication credential and account information associated with the cloud operating system. Based on the received input, the discovery application executes a discovery pattern comprising operations for the discovery of resources. The cloud operating system includes a group of services to access such resources. At least one of the operations corresponds to an API call to an API endpoint associated with a service of the group of services. The discovery application receives a response to the API call from the cloud operating system. The response includes a payload of information associated with the resources. The discovery application updates, based on the received response, one or more configuration items in a configuration management database.
An example implementation may involve: obtaining state information characterizing a software application, wherein the state information indicates a plurality of use states of the software application; identifying a current use state of the plurality of use states; determining, based on the state information and the current use state, an activity to perform via the software application or a further software application; and providing a message including the activity.
Persistent storage may contain a list of discovery commands, the discovery commands respectively associated with lists of network addresses. A discovery validation application, when executed by one or more processors, may be configured to: read, from the persistent storage, the list of discovery commands and the lists of network addresses; for each discovery command in the list of discovery commands, transmit, by way of one or more proxy servers deployed external to the system, the discovery command to each network address in the respectively associated list of network addresses; receive, by way of the one or more proxy servers, discovery results respectively corresponding to each of the discovery commands that were transmitted, wherein the discovery results either indicate success or failure of the discovery commands; and write, to the persistent storage, the discovery results.
An example may involve obtaining structured data that is characterized by a notification format; processing the structured data to determine a mapping between one or more fields of the notification format and one or more fields of a database schema, wherein the database schema is characterized by a database format; translating a notification from the notification format into the database schema according to the mapping; and storing the translated notification into a database that operates according to the database schema.
A method includes obtaining first data records associated with a first schema. Each respective data record of the first data records may include corresponding values of a plurality of fields. The method also includes obtaining a mapping representing a transformation of a field of the plurality of fields from the first schema to a training schema, and selecting, based on the mapping and for each respective data record of the first data records, a corresponding value of the field from the first data records. The method further includes generating second data records by transforming, based on the mapping and for each respective data record of the first data records, the corresponding value of the field from the first schema to the training schema. The method additionally includes training a machine learning model based on the second data records.
A method includes obtaining first data records associated with a first schema. Each respective data record of the first data records may include corresponding values of a plurality of fields. The method also includes obtaining a mapping representing a transformation of a field of the plurality of fields from the first schema to a training schema, and selecting, based on the mapping and for each respective data record of the first data records, a corresponding value of the field from the first data records. The method further includes generating second data records by transforming, based on the mapping and for each respective data record of the first data records, the corresponding value of the field from the first schema to the training schema. The method additionally includes training a machine learning model based on the second data records.
An agent is directed to engage in a chat session with a party via a messaging application. The chat session is within a first section of a user interface of the messaging application. While the agent is engaged in the chat session with the party, a web reference to content is generated. The web reference includes an application identifier associated with the messaging application. In response to receiving a request for the web reference including the application identifier, the content is displayed in a second section of the user interface of the messaging application that is different from the first section of the user interface.
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0483 - Interaction with page-structured environments, e.g. book metaphor
In various embodiments, a process for alert filtering based on service to facilitate triage includes receiving an alert, identifying a configuration item of a computer information technology configuration management system associated with the alert, and identifying a property of the configuration item stored separately from one or more properties included in the alert. The process includes enabling filtering of the alert based on the property of the configuration item.
H04L 41/0631 - Management of faults, events, alarms or notifications using root cause analysisManagement of faults, events, alarms or notifications using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
H04L 41/0604 - Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
Example embodiments relate to parallelized exception handling for large datasets. One example embodiment includes a method. The method includes retrieving one or more sets of entries to be analyzed. The method also includes selecting an available computing resource. In addition, the method includes causing the available computing resource to perform an analysis of each entry within the respective set of entries to identify previously defined exceptions. Further, the method includes causing, for each entry within the respective set of entries, a list of exceptions associated with the respective entry to be created or updated based on the analysis. Additionally, the method includes causing, for each entry within the respective set of entries, metadata associated with the respective entry to be updated when the list of exceptions associated with the respective entry indicates that no exceptions are associated with the respective entry.
In various embodiments, a process for alert filtering based on service to facilitate triage includes receiving an alert, identifying a configuration item of a computer information technology configuration management system associated with the alert, and identifying a property of the configuration item stored separately from one or more properties included in the alert. The process includes enabling filtering of the alert based on the property of the configuration item.
An embodiment may involve receiving, at a web server application, a query specifying a file, a block number of a block of data within the file, and a block size, wherein the file includes entries representing differences between snapshots of configuration data; identifying, based on the block size, the block of data within the file; storing the block in a non-transitory memory that is accessible to the web server application; and in response to the query, transmitting, by the web server application, a set of the entries within the block formatted for display in a list component of a graphical user interface.
G06F 7/08 - Sorting, i.e. grouping record carriers in numerical or other ordered sequence according to the classification of at least some of the information they carry
An example may involve determining that a first proxy server is to share security credentials with a set of one or more proxy servers, wherein the set of one or more proxy servers is associated with the security credentials, and wherein the set of one or more proxy servers includes a second proxy server; transmitting, to the second proxy server, a request for the first proxy server to have access to the security credentials; and receiving, from the second proxy server, a credential key in an encrypted form, wherein the credential key is configured to decrypt the security credentials.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
A specification of one or more steps of a digital workflow specified using a graphical user interface is received. An indication of a program transfer control step in the digital workflow to return to a previously specified step in the digital workflow is received. The already specified specification of the one or more steps of the digital workflow is analyzed to determine one or more constraints of the program transfer control step. Based on the determined one or more constraints of the program transfer control step, a configuration of the program transfer control step in the digital workflow is restricted in the graphical user interface.
An example may involve determining that a first proxy server is to share security credentials with a set of one or more proxy servers, wherein the set of one or more proxy servers is associated with the security credentials, and wherein the set of one or more proxy servers includes a second proxy server; transmitting, to the second proxy server, a request for the first proxy server to have access to the security credentials; and receiving, from the second proxy server, a credential key in an encrypted form, wherein the credential key is configured to decrypt the security credentials.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
Metrics that characterize one or more computing devices are received. A value associated with a performance of the one or more computing devices based on the received metrics is determined. A first scheduling parameter based on the value is determined, wherein the first scheduling parameter is associated with a first discovery process that is associated with at least a portion of the one or more computing devices. Execution of the first discovery process is directed according to the first scheduling parameter.
A text dialogue between a first user and a second user is obtained. Based on an analysis of the text dialogue, workflows that are relevant to the text dialogue are identified. A list of the workflows is provided to a client device associated with the first user. An indication of a selection of a particular workflow from the list of the workflow is received from the client device associated with the first user. Based on the particular workflow, a communication session is established between the second user and an automated chatbot associated with the particular workflow.
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
H04L 51/02 - User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
In various embodiments, a process for providing a dynamic Web component with configurable content includes receiving an instruction to move a component from a first portion of a user interface to a second portion of the user interface for application on the second portion of the user interface, wherein the second portion is configured to receive an input from a user. The process includes programmatically analyzing content of the second portion to select a machine learning model, and determining, for the user, the input to the second portion using the selected machine learning model.
An example may involve receiving a request to generate a user interface component, wherein the request indicates data usable to populate the user interface component; generating a prompt for a natural language model based on the request and the data; receiving, from the natural language model, a representation of the user interface component based on the prompt; and providing the representation of the user interface component for display.
A method is provided for efficiently providing sentiments or other manual labels for textual training data. The method includes using an embedding model to project acquired user text to an embedding vector in an embedding space. Distances (e.g., cosine similarities) between this embedding vector and the embedding vectors determined for a plurality of already-label user text training examples are then determined. The already-labeled user text that has the shortest distance is determined and the label thereof is prospectively applied to the acquired user text and presented to a user for approval. The user can approve the prospectively applied label, in which case the newly acquired text is added to the training data with the prospectively applied label associated therewith for later use in training a language model. Alternatively, the user can decline the prospectively applied label and apply an alternative label to the newly acquired text.
An example embodiment may include: obtaining, by a shortcut framework associated with a graphical user interface, a shortcut event; identifying a component of the graphical user interface based on the component being associated with the shortcut event; identifying a shortcut action associated with the shortcut event, wherein the shortcut action specifies a shortcut action identifier associated with a shortcut function that modifies the graphical user interface; and dispatching the shortcut action identifier to the component to cause the component to perform the shortcut function that modifies the graphical user interface.
G06F 3/04892 - Arrangements for controlling cursor position based on codes indicative of cursor displacements from one discrete location to another, e.g. using cursor control keys associated to different directions or using the tab key
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
86.
REQUEST MANAGEMENT USING MACHINE LEARNING MODELS TRAINED WITH SYNTHETIC DATA AND PSEUDO-LABELED DATA
A first machine learning model is trained using a synthetic training dataset. The first machine learning model is used to predict a plurality of pseudo-labels corresponding to an unlabeled dataset associated with a specific group. At least a portion of the unlabeled dataset and their corresponding pseudo-labels are selected to form a pseudo-labeled dataset. A second machine learning model is trained using the pseudo-labeled dataset and the synthetic training dataset as an improved version of the first machine learning model.
An example embodiment may include: obtaining, by a shortcut framework associated with a graphical user interface, a shortcut event; identifying a component of the graphical user interface based on the component being associated with the shortcut event; identifying a shortcut action associated with the shortcut event, wherein the shortcut action specifies a shortcut action identifier associated with a shortcut function that modifies the graphical user interface; and dispatching the shortcut action identifier to the component to cause the component to perform the shortcut function that modifies the graphical user interface.
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
G06F 16/955 - Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
G06F 3/0354 - Pointing devices displaced or positioned by the userAccessories therefor with detection of 2D relative movements between the device, or an operating part thereof, and a plane or surface, e.g. 2D mice, trackballs, pens or pucks
G06F 3/02 - Input arrangements using manually operated switches, e.g. using keyboards or dials
An example may involve receiving a request to generate a user interface component, wherein the request indicates data usable to populate the user interface component; generating a prompt for a natural language model based on the request and the data; receiving, from the natural language model, a representation of the user interface component based on the prompt; and providing the representation of the user interface component for display.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06F 9/451 - Execution arrangements for user interfaces
A method includes generating, for display by way of a graphical user interface (GUI), a graphical representation of an existing state of a plurality of computing resources that visually represents the plurality of computing resources and one or more relationships therebetween. The method also includes determining a target state of the plurality of computing resources based on a user modification of the graphical representation of the existing state. The user modification may be obtained by way of the GUI. The method additionally includes determining, based on a difference between the target state and the existing state, one or more operations configured to modify the plurality of computing resources to reach the target state from the existing state. The method further includes executing the one or more operations.
G06F 9/451 - Execution arrangements for user interfaces
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
90.
DETERMINING THE IMPACT OF MALICIOUS PROCESSES IN IT INFRASTRUCTURE
A method and system for detecting malicious activities in an IT infrastructure, determining its impact to the IT infrastructure, and determining the associated remedial actions are disclosed. Data communication between a plurality of computer processes is tracked. At least one process of the plurality of computer processes is identified as an anomalous process with respect to at least some of the plurality of computer processes. A first computer process of the plurality of computer processes that is affected by the anomalous computer process is identified based on at least a portion of the tracking. An indication of the identified first computer process that is affected by the anomalous computer process is provided.
H04L 41/16 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
A request to provide access to a computer program via an application programming interface is received. Based on the request, the computer program is analyzed and a schema for the application programming interface is generated based on the analysis. A resolver code that is operable with the application programming interface is determined. The schema and the resolver code are provided to enable the application programming interface for the computer program.
In various embodiments, a process for providing a cloud service provider request retry framework includes obtaining a request retry indicator that is associated with a cloud service provider, wherein the request retry indicator indicates a retry criterion that is based on a number of allowable discovery requests within a period of time. The process includes providing a discovery request to the cloud service provider; receiving an error response based on the discovery request, wherein the error response indicates the discovery request is unsuccessful based at least on the discovery request not satisfying the retry criterion; and determining a wait time based at least on the error response and the request retry indicator. The process includes retrying the discovery request according to the wait time.
H04L 69/40 - Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass for recovering from a failure of a protocol instance or entity, e.g. service redundancy protocols, protocol state redundancy or protocol service redirection
H04L 41/06 - Management of faults, events, alarms or notifications
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
Data communication between a plurality of computer processes are tracked. Relationships between the plurality of computer processes are classified including by analyzing the data communication between the plurality of computer processes using a machine learning model. Based at least in part on the classified relationships between the plurality of computer processes, an existence of a service provided by a functional group of computer processes included in the plurality of computer processes are automatically discovered.
A protection system, method, and a security device can protect an operational technology (OT) system having connected hardware equipment, including at least an interface that can receive a control communication and an industrial control device (ICD) for controlling at least one industrial device. They feature tasks/steps that receive control communication from the communication interface, determine whether the received control communication contains an undesirable control command, and either pass or block the received control communication to the ICD depending on whether the received control communication contains an undesirable control command. The security device can be disposed between a source of communication in an OT network and the ICD for protection.
H04L 41/06 - Management of faults, events, alarms or notifications
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
An identifier associated with a plurality of different collection groups of computer system attributes is obtained. The computer system attributes are associated with the plurality of different collection groups based at least in part on recency of changes to the computer system attributes. A discovery scan of the plurality of different collection groups is performed at a scan instance. A first digest value associated with a specific collection group included in the plurality of different collection groups is obtained. A second digest value associated with the specific collection group based on the discovery scan is determined. It is determined that the first digest value is different from the second digest value. An indication associated with the first and second digest values being different is provided.
A distribution of values of time-series data is obtained. Based on the distribution of the values, the time-series data is sampled to generate an anomaly preserving version of the time-series data. Via a trained machine learning model, a reconstructed version of the time-series data is generated based on the anomaly preserving version of the time-series data.
An agent automation system includes a memory configured to store a reasoning agent/behavior engine (RA/BE) including a first persona and a current context and a processor configured to execute instructions of the RA/BE to cause the first persona to perform actions comprising: receiving intents/entities of a first user utterance; recognizing a context overlay cue in the intents/entities of the first user utterance, wherein the context overlay cue defines a time period; updating the current context of the RA/BE by overlaying context information from at least one stored episode associated with the time period; and performing at least one action based on the intents/entities of the first user utterance and the current context of the RA/BE.
Improved methods for semi-supervised training are provided. These methods include using a model that has been trained used ground-truth labeled training examples to predict the class of a set of unlabeled training examples. A subset of the unlabeled training examples are then added to the labeled training dataset, labeled with the model-generated labels. The added subset are balanced across the predicted classes (e.g., an equal number added from each predicted class) in order to reduce bias in the augmented training dataset toward representation of ‘easy’ classes. Confidence scores used to select which training examples to add from each predicted class could be based on a confidence output of the model. Additionally or alternatively, the confidence scores could be determined based on distance, in an embedding space of the model, between the unlabeled training examples and labeled training examples whose class label match the predicted label of the unlabeled training examples.
An example embodiment may involve: obtaining a representation of an access control list (ACL), wherein the ACL includes an entry that defines user capabilities with respect to a computing resource; determining a user class based on the entry and one or more rules, wherein the one or more rules are based on whether the computing resource is a database table for a task-based application, and wherein the one or more rules are based on whether the computing resource is read accessible or write accessible; and providing, for display on a graphical user interface, an indication of the user class.
H04L 41/22 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
An example embodiment may involve receiving, via a user interface, a plurality of textual user feedback regarding operation of a software application; aggregating, via a trained machine-learning model, the plurality of textual user feedback into a discrete number of observations regarding the operation of the software application, wherein the observations are in textual form; determining a subset of the observations that satisfy a relevance criterion; and providing the subset of the observations for display.
