Abstract: Disclosed are techniques for increasing the speed of pairwise comparison operations in a database system. In an embodiment, a method is disclosed comprising receiving a network request identifying a user; identifying a plurality of segments associated with the user; loading a plurality of bitmaps associated with the plurality of segments, each bitmap in the plurality of bitmaps representing a set of users associated with a segment; comparing pairs of bitmaps from the plurality of bitmaps to generate a set of overlaps; filtering the plurality of segments based on the set of overlaps to generate an anonymized set of segments; and returning aggregated data associated with the anonymized set of segments in response to the network request.

Abstract: A disclosed computer-implemented method may include providing, by a processor, an artificial intelligence model (“predictive model”) pre-configured to infer, via a plurality of features included in the predictive model trained using data representative of computing resource requirements of current tenants of a multitenant computing platform, computing resource requirements for potential tenants of the multitenant computing platform. The method may also include receiving, by the processor, at least one query comprising data that describes an attribute of a potential tenant of the multitenant computing platform, and determining, by the processor, based on an inference of the predictive model generated based on the at least one query, an output comprising an estimated computing resource requirement of the potential tenant. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A system for automated model hyperparameter determination and serving includes an interface and a processor. The interface is configured to receive a request to determine optimal hyperparameters for a model. The processor is configured to determine a framework extension to implement the model; determine an optimization assembly to support the framework extension; determine a cluster to execute the optimization assembly; determine an optimization script for the optimization assembly; cause the cluster to execute the optimization script to determine the optimal hyperparameters; and build an optimal model using the optimal hyperparameters.

Abstract: In some implementations, the techniques described herein relate to a method including: receiving, at an API gateway, an API request from an API client; extracting, by the API gateway, a client identity associated with the API request; checking, by the API gateway, API Level Objectives (ALOs) associated with the client identity, the ALOs defining acceptable usage limits for the client identity; determining, by the API gateway, that the API request falls outside the acceptable usage limits defined by the ALOs; and applying, by the API gateway, an API Level Agreement (ALA) action, the ALA action specifying an action to be taken when an ALO is breached.

Abstract: A system for automatic model training and release includes a model storage system, an interface, and a processor. The interface is configured to receive an indication to create a model for release. The processor is configured to fetch data for creation of the model; validate the data to determine a data validation result; extract features based at least on part the data; validate the features using one or more feature quality metrics; build the model based at least in part on the features and the data; validate the model using one or more model quality metrics; store the model using the model storage system; and release the model for use.

Abstract: A computer-implemented method for designing a user interface application uses a visual flow language and a model view flow architecture. The visual flow language may include components, where components include blocks and nodes. Call streams and data flows may be defined by a user. An application flow logic graph is generated. The application flow logic graph may be used to generate a user interface application.

Abstract: A client manifest identifier is received from a client device. One or more features to include in a response to the client device are determined based on a client manifest corresponding to the client manifest identifier. A feature of the one or more features is associated with a capability indicated by the client manifest. The response is provided to the client device. The response has a particular structure based on the one or more features.

Abstract: A disclosed method may include receiving, via a user interface, a natural language query that describes a task. The method may also include classifying, via a classification machine learning model, the natural language query as a query type included in a predetermined plurality of query types. The method may also include generating, by the processor via a generative machine learning model pre-trained to generate responses to queries based on at least one predetermined task execution policy, a response based on the natural language query and the query type. The method may also include providing, via the user interface, the response. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A method and system(s) for processing queries to sparsely populated datasets. The method includes (i) receiving a query from a client system, (ii) determining, based at least in part on the query, a plurality of partitions of a hypercube that are expected to comprise information used in generating a response for the query, (iii) communicating a set of requests to a data source storing the hypercube, the set of requests comprising one or more requests corresponding to the plurality of partitions of the hypercube, (iv) obtaining, from the data source, a set of results to the set of requests, the set of results comprising data stored in the plurality of partitions of the hypercube, (v) determining a plurality of virtual objects for the set of results, (vi) combining the plurality of virtual objects into a response to the query, and (vii) providing the response to the query.

Abstract: The example embodiments relate to matching response data to request data. in an embodiment, a method includes retrieving a request and a plurality of responses; generating packed candidates based on the request and the plurality of responses, a given packed candidate in the packed candidates including the request and a subset of the plurality of responses; generating feature vectors corresponding to the packed candidates, a given feature vector in the feature vectors including at least one aggregated feature computed based on the request and one or more corresponding responses in a respective packed candidate; inputting the feature vectors into a machine learning (ML) model, the ML model configured to output predictions corresponding to the feature vectors; selecting a feature vector from the feature vectors based on the predictions; and storing responses associated with the optimal feature vector and the request in a data storage device.

Abstract: In some implementations, the techniques described herein relate to a method including: receiving, at an API gateway, an API request from an API client; extracting, by the API gateway, a client identity associated with the API request; checking, by the API gateway, API Level Objectives (ALOs) associated with the client identity, the ALOs defining acceptable usage limits for the client identity; determining, by the API gateway, that the API request falls outside the acceptable usage limits defined by the ALOs; and applying, by the API gateway, an API Level Agreement (ALA) action, the ALA action specifying an action to be taken when an ALO is breached.

Abstract: A system, method, and device for managing dependencies between a hypercube base version and a set of scenario versions for the hypercube are provided. The method includes (i) obtaining a request for a version of a hypercube, and (ii) in response to obtaining the request: (a) obtaining a base version of the hypercube, (b) obtaining an override data structure that indicates a set of scenario values that override corresponding base version values, and (c) providing the version of the hypercube based at least in part on the base version and the override data structure.

Abstract: A system, method, and device for storing a scenario version as a base version for a hypercube are provided. The method includes (i) obtaining a request to store a scenario version of a hypercube as a base version; (ii) obtaining a set of transactions corresponding to hypercube updates for the scenario version, and (iii) writing the set of transactions to the base version.

Abstract: A system, method, and device for managing updates to a hypercube is provided. The method includes (i) obtaining a hypercube comprising a plurality of locations, wherein a particular location has an anchor object that stores version information for the particular location, and the particular location comprises a first formula that is evaluated to return a value for the particular location, (ii) in response to receiving the request for the value, determining that the particular location comprises the first formula, (iii) in response to determining that the particular location comprises the first formula, evaluating the first formula to obtain a result, and (iv) storing the result for the particular location in association with the version information for the particular location.

Abstract: A system includes an interface and a processor. The interface is configured to receive a predicted output signal. The processor is configured to: a) determine whether the predicted output signal satisfies a constraint set; and b) in response to the predicted output signal not satisfying the constraint set, determine a transformed output signal that satisfies the constraint set by: 1) determining a set of transformed predicted output signals that satisfy the constraint set, wherein a transformed predicted output signal of the set of transformed predicted output signals that satisfy the constraint set comprises the predicted output signal modified by one or more value modifications; 2) selecting a transformed predicted output signal of the set of transformed predicted output signals that satisfy the constraint set; and 3) providing the transformed predicted output signal of the set of transformed predicted output signals that satisfy the constraint set.

Abstract: A system, method, and device for managing updates to a hypercube is provided. The method includes (i) obtaining a hypercube comprising a plurality of locations, wherein a particular location has an associated anchor object that stores version information for the particular location, (ii) receiving a request to store an updated value for the particular location, and (iii) storing the updated value for the particular location of hypercube, the updated value being stored with associated version information stored in the anchor object for the particular location.

Abstract: A system, method, and device for evaluating a query is provided. The method includes (i) receiving the query to be evaluated against a data structure, (ii) determining input data corresponding to a subset of the data structure that is to be used in evaluating the query, (iii) determining a solve order for evaluating the query against the input data, (iv) partitioning the input data into a plurality of sub-grids based at least in part on the solve order, (v) processing the plurality of sub-grids to compute corresponding parts of the query, and (vi) evaluating the query based at least in part on the processing of the plurality of sub-grids to obtain a query result.

Abstract: An incident manager application (IM) for responding to data security incidents in enterprise networks is disclosed. An IM tracks the incidents in an enterprise network by storing incident objects and incident artifact (IA) metadata created for the incidents, where the incident objects and IAs include information concerning the incidents. Incident response team (IRT) personnel of the enterprise networks can define action conditions within the IM that are associated with the incident objects. When the information within the incident objects and/or IAs meets the defined action conditions, the IM includes the objects that cause the action conditions to be satisfied in messages. Devices such as user account databases and configuration servers within the enterprise network can then download the messages and execute actions that reference the objects extracted from the downloaded messages to implement a response to the incidents.

Abstract: A system, method, and device for evaluating a query is provided. The method includes (i) receiving a query that is indicative of one or more properties of result data, (ii) determining, based at least in part on the query, one or more partitions of a hypercube that are expected to comprise information used in generating result data for a response for the query; (iii) generating a data structure comprising a set of data of the one or more partitions, wherein the data structure is indicative of relationships among data in the set of data; (iv) evaluating the query with respect to the plurality of account groups; and (v) using the data structure to determine the result data based at least in part on an evaluation of the query with respect to the plurality of account groups.

Abstract: The present application discloses a method, system, and computer system for enforcing security with respect to a database. The system includes a database configured to receive a query, wherein the query is modified to comprise one or more security predicates; determine data to return in response to the query by examining the one or more security predicates with respect to security for a field; and return the determined data in response to the query.