Abstract: Improving utilization of network devices includes detecting that a first network device is added to a network system comprising a plurality of network devices associated with a service map, wherein at least one of the plurality of network devices corresponds to one or more activities of a workflow for the service map, determining a first activity of the workflow that utilizes data from the first network device, and in response to determining that the first activity of the workflow utilizes data from the first network device, determining sensor attributes of the first network device that are tied to key performance indicators for the first network device, and adding the first network device to the service map such that the determined sensor attributes provide input for the first activity.

Abstract: A system includes a database containing database tables. The system also includes one or more processors configured to: (i) determine, for a software application, a set of the database tables containing information used by the software application; (ii) for an item associated with the software application, query the set of the database tables for entries related to the item, wherein the entries are in a first language; (iii) generate, for display, a representation of a first pane and a second pane, wherein the first pane contains the entries, and wherein the second pane contains data input elements for translations of the entries into a second language; (iv) transmit the representation; (v) receive data entered into the data input elements of the second pane; and (vi) store, in the set of the database tables, the data entered into the data input elements as a translation to the second language.

Abstract: Persistent storage contains a parent table and one or more child tables, the parent table containing: a class field specifying types, and one or more filter fields. One or more processors may: receive a first request to read first information of a first type for a first entity; determine that, in a first entry of the parent table for the first entity, the first type is specified in the class field; obtain the first information from a child table associated with the first type; receive a second request to read second information of a second type for a second entity; determine that, in a second entry of the parent table for the second entity, the second type is indicated as present by a filter field that is associated with the second type; and obtain the second information from a set of additional fields in the second entry.

Abstract: A natural language understanding (NLU) framework includes an 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.

Abstract: An example embodiment may involve determining, based on a predefined policy, one or more configuration settings, wherein the predefined policy specifies a permitted value of a key within the configuration settings; obtaining, from a cloud-based service provider, an actual value of the key; determining, by applying the predefined policy, that the actual value of the key does not match the permitted value of the key; identifying a remediation for the key that includes determining an updated value of the key, wherein the updated value of the key satisfies the predefined policy; and causing the updated value to be applied to the key in the cloud-based service provider.

Abstract: An embodiment may involve storage containing incident logs and mappings between incident logs and vector representations generated by a machine learning (ML) model.

Abstract: A chat message is received from a user to a primary virtual agent service. A secondary virtual agent service to handle the chat message is automatically evaluated and selected. The secondary virtual agent service is selected from a plurality of candidate secondary virtual agent services that includes at least one virtual agent service provided by a third-party entity external to an entity providing the primary virtual agent service. The chat message is transformed from a first format of the primary virtual agent service to a second format of the selected secondary virtual agent service. The chat message is forwarded in the second format to the selected secondary virtual agent service.

Abstract: An indication associated with a request to access a protected object by a subject is received. Using one or more processors, application level behavioral patterns of the subject, context of the request by the subject, usage patterns associated with the protected object, and a current system state are automatically analyzed using one or more machine learning models to determine an analysis result associated with whether to grant the subject access to the protected object. An access control mechanism for the protected object is automatically modified based on the analysis result.

Abstract: 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.

Abstract: 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.

Abstract: Present embodiments are directed to a virtual agent with improved natural language understanding (NLU) capabilities. The disclosed virtual agent enables topic selection and topic changes during natural language exchanges with a user. The virtual agent is designed to select suitable topic flows to execute based on intents identified in received user utterances, including selection of an initial topic flow in response to a topic identified in a first user utterance, as well as switching between topic flows mid-conversation based on identified topic changes. The virtual agent is also capable of considering all intents and entities conveyed during the conversation, which enables the virtual agent to avoid prompting the user to provide redundant information. Furthermore, the virtual agent is capable of executing topic flows as part of a global topic flow, which enables the virtual agent to perform a number of predefined activities as part of each interaction with the user.

Abstract: 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.

Abstract: A natural language understanding (NLU) framework includes a lookup source system having one or more lookup sources. Each lookup source includes a respective source data representation that is compiled from respective source data. Once compiled, a user utterance can be submitted to the lookup source system, which generates segmentations of the user utterance. Each segmentation generally includes a collection of non-overlapping segments, and each segment generally describes how tokens of the user utterance can be grouped together and matched to the states of the source data representations. During lookup source inference, matches can be made to produced states or using fuzzy matchers that have corresponding of scoring adjustments. These scoring adjustments may be used by a segmentation scoring subsystem, potentially in combination with one or more additional segmentation scoring plugins, to score and rank the segmentations determined by the lookup source system for the user utterance.

Abstract: A natural language understanding (NLU) framework includes a modeling and optimization system that enables enhanced understanding and explainability to the operation of the NLU framework. The NLU framework includes a configuration vector storing settings of various components that may be applied during NLU inference of an utterance, such as which components should be activated or deactivated, as well as which numerical values (e.g., threshold values, coefficients, weight values) that are used by these components during operation. By using this configuration vector to systematically disable and adjust numerical parameters of the components of the NLU framework, and then determining the performance of the NLU framework in these configurations, the modeling and optimization system determines relationships between, as well as the relative importance of, the components of the NLU framework.

Abstract: 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.

Abstract: An identification of a specification that identifies one or more data sources is received. The one or more data sources are respectively associated with one or more database queries. Each of the one or more database queries is associated with a different embedded screen. An end-user application that is configured to generate selectable user interface elements for the one or more different embedded screens is generated. Generating the end-user application is based on the specification. In response to selection of a particular selectable user interface element of the selectable user interface elements, an embedded screen associated with the particular selectable user interface element is identified, and a user interface including the identified embedded screen is provided.

Abstract: A determination is made whether a received database query is to be processed by either a first database, a second database, or at least in part by both the first and second databases including by determining whether the query meets criteria to split the query for processing across the first and second databases. The first and second databases store shared synchronized records, the first database configured to store the records in a column-oriented format and the second database configured to store the records in a row-oriented format. In response to a determination that the query meets the criteria to split the query, a first and second component query of the database query are generated for the first and second databases, respectively, the second component query based at least in part on a result of the first component query. The execution of the first and second component queries is pipelined.

Abstract: 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.

Abstract: Systems and methods involving data structures for efficient management of paragraph vectors for textual searching are described. A database may contain records, each associated with an identifier and including a text string and timestamp. A look-up table may contain entries for text strings from the records, each entry associating: a paragraph vector for a respective unique text string, a hash of the respective unique text string, and a set of identifiers of records containing the respective unique text string. A server may receive from a client device an input string, compute a hash of the input string, and determine matching table entries, each containing a hash identical to that of the input string, or a paragraph vector similar to one calculated for the input string. A prioritized list of identifiers from the matching entries may be determined based on timestamps, and the prioritized list may be returned to the client.

Abstract: One or more associated identifiers are determined based on one or more associated tag types of an interactable element of web content. The determined one or more associated identifiers are associated with the interactable element. Based on the association of the determined one or more associated identifiers with the interactable element, one of the interactable element is matched to a received speech input. An action is performed with respect to the interactable element based on the matching.