Abstract: Various methods and processes, apparatuses/systems, and media for systemically and dynamically onboarding and reporting data with no code or low code data warehouse are disclosed. A processor implements a model driven data WaaS and reporting platform; receives data from a plurality of data source systems; provisions the data received from the plurality of source systems; validates the provisioned data; creates a machine learning data model based on the validated data; onboards the data model onto the model driven data WaaS and reporting platform; and generates an adapter pattern on every field type to treat it as a field. The adapter pattern is generated where fields and their types are entered into data WaaS field types so that a user can define the field once and use across all reports thereby enabling no code approach. The processor then dynamically generates a report corresponding to the adapter pattern for publication and consumption.

Abstract: In one example, a method for rotating security credentials includes instantiating an execution environment in which to execute instructions of a script. The method also includes executing the instructions of the script within the execution environment to cause the at least one processor to monitor a passage of time to identify an arrival of a time to coordinate a rotation of a security credential between an executable routine and a secrets management service. The at least one processor is also caused, in response to identifying the arrival of the time, perform operations including: providing a first request to the executable routine to communicate with the secrets management service of the processing device to request rotation of the security credential at the secrets management service, and providing a second request to the executable routine to rotate the security credential at the executable routine.

Abstract: A system for managing a regulated network of network controls to maintain compliance with applicable regulations. The system may comprise instructions that, when executed, cause a processor to: monitor, a network data source, for new regulatory data that pertains to the regulated network; identify new regulatory data that has been obtained from the network data source; determine whether the new regulatory data requires changes to existing network controls from among the network controls; after determining that the new regulatory data requires the changes, implement the changes; determine whether the first set of new regulatory data requires modifying the network controls to include new network controls that pertain to the network; and after determining that the new regulatory data requires the modifying, add the new network controls to the network controls.

Abstract: Systems and methods for cross platform configuration are described herein. The platform may receive selections for software programs or operating system configurations and selections of installation settings. A blueprint file is generated to specify the software programs or operating systems that are selected. In addition, the blueprint file may specify different installation settings and configuration settings. The blueprint file is stored in a repository and may be applied to one or more target devices. When applied, a task schedule is generated, where the task schedule prioritizes installations specified in a blueprint file. In addition, the task schedule specifies various provider identifiers to perform the installation(s).

Abstract: Systems and methods for generating immutable keys for client relationships are disclosed.

Abstract: Systems and methods for source code understanding using spatial representations are disclosed. In one embodiment, a method may include: (1) receiving, by a source code understanding computer program, a source code snippet; (2) converting, by the source code understanding computer program, the source code snippet to a two-dimensional image representation using an encoding technique; (3) mapping, by the source code understanding computer program, the two-dimensional image representation into a three-dimensional image representation; (4) determining, by the source code understanding computer program, a classification for the source code snippet using a deep learning network; and (5) providing, by the source code understanding computer program, the classification for the source code snippet to a downstream system.

Abstract: Systems and methods for protection of data across multiple users and devices are disclosed. According to one embodiment, in privacy server comprising at least one computer processor, a method for protection of data across multiple users and devices may include: (1) receiving, from a first user device, a data sharing permission for the first user device and a data sharing permission for a second user device, the first user device and the second user device associated with the same user; (2) provisioning the data sharing permission for the second user device; and (3) communicating the provisioned data sharing permission to the second user device, wherein the second user device shares data with the first user device according to the provisioned data sharing permission.

Abstract: A method and a system for performing a search in a dataset in a mainframe session are disclosed. The method includes receiving at least one keyword associated with at least one query. The method includes identifying at least one from among at least one step containing the at least one keyword and at least one paragraph containing the at least one keyword based on the at least one query. The method includes tagging at least one identifier to at least one from among the at least one identified step and the at least one identified paragraph. Next, the method includes verifying the at least one tagged identifier. Thereafter, the method includes displaying at least one from among the at least one identified step and the at least one identified paragraph.

Abstract: A method and system for operating an application program interface-based content management system. The method and system each comprises: communicating, by an application that is based on a microservices architecture, with a user interface via content APIs that provide for content creation, content modification, content storage, and content retrieval; storing, by the application, within a relational database, relational data, identification data, and access control data; storing, by the application, within a content store that comprises an object storage database, content as objects in buckets of the object storage database; communicating, by a search engine, with the application via search APIs that provide for a full text-based search of the object storage database; storing, by the search engine, within memory of the search engine, metadata that corresponds to the data; and storing, by the search engine, within the memory, reference data that corresponds to the data.

Abstract: Embodiments use quantum conditional logic in the Quantum Phase Estimation Algorithm (QPEA) to compute eigenvalues prior to inversion. Embodiments estimate the eigenvalues of a unitary, U=eiÂt, generated by a N×N Hermitian matrix Â. The binary representations of the n-bit estimations of eigenvalues of  may be encoded in these states: |?i=|b1b2 . . . bn; ?i is an estimation of the i-th eigenvalue, excluding degeneracy, and .b1b2 . . . bn is its binary representation. To perform the eigenvalue inversion, an n-qubit controlled Ry rotation with angle ?i/2(n?1) conditioned on seeing |b1b2 . . . bn is applied for each possible n-bit binary string b1b2 . . . bn (2n values). The overall unitary is called a “uniformly controlled Ry rotation” in literature.

Abstract: In some aspects, the techniques described herein relate to a method including: providing one or more curation content machine learning models, wherein the one or more curation content machine learning models are configured to classify a textual review into a plurality of classifications, and wherein the plurality of classifications have been assigned respective relative weights; receiving, at a collaboration service, a user review of a travel objective from a user of the collaboration service; providing the review as an input feature dataset to the one or more curation content machine learning models; receiving, as output of the one or more curation content machine learning models, a plurality of classifications of the user review; and aggregating, by the collaboration service, a relative value score based on the assigned relative weight of the plurality of classifications of the user review.

Abstract: Systems and methods for enhanced organizational transparency using a linked activity chain in a ledger are disclosed. In one embodiment, a method may include (1) a back end for an organization comprising at least one computer processor receiving a first communication from a first entity comprising a first customer interaction with the first entity; (2) the back end writing the first communication to a ledger for the organization as a first block in a linked activity chain; (3) the back end receiving a second communication from a second entity comprising a second customer second activity with the second entity; (4) the back end writing the second communication to the ledger for the organization as a second block in the linked activity chain; (5) the back end calculating a summary score for the customer based on the blocks in the linked activity chain.

Abstract: A method and system for generating cluster level explanations for an input data having limited or special values are disclosed. The method includes obtaining an input data set and a clustering stopping criteria, the input data set including multiple features, and each of the features having multiple feature values; performing features decomposition on the input data; performing correlation analysis based on the features decomposition and a correlation threshold value; grouping the features having different feature values into multiple clusters; training a model based on the obtained input data; obtaining a target input data to be tested and a number of cores; grouping the number of cores into multiple clusters; and computing explanations at a cluster level.

Abstract: In one example, a storage medium with program instructions to deploy immutable-image software to retail branch devices is disclosed. The operations include accessing a change request from a user interface to initiate an event on a remote computer system. The event is a deployment of immutable branch-image software to alter or reimage existing software stored or executed on the remote computer system. The operations include validating that the deployment of the immutable branch-image software is required on the remote branch computer system and generating a new partition in a memory of the remote branch computer system. The operations also include retrieving the immutable branch-image software via a secure network socket in response to the event message, installing the immutable branch-image software in the new partition and transferring operation of the remote branch computer system from an original partition of the memory to the new partition.

Abstract: In one example, a storage medium with program instructions to deploy immutable-image software to retail branch devices is disclosed. The operations include accessing a user-interface change request to initiate an event on a remote computer system. The event is a deployment of immutable branch-image software to alter or reimage existing software on the remote computer system. The operations include authenticating an identity of a user interface operator, publishing an event message (preload and build) on a messaging databus. An agent communicating with the remote computer system subscribes to the messaging databus.

Abstract: A method for using a large language model to generate executable code for workflow execution in a manner that integrates user feedback and adjusts the workflow as needed while preserving data privacy is provided. The method includes: receiving first information that relates to a workflow context, second information that relates to at least one application programming interface (API), and third information that relates to a code generation request; using the received information to generate a lecture, and transmitting the lecture to a language model; receiving a user query that relates to performing a task, and transmitting the query to the language model; receiving a workflow that is automatically generated by the language model based on the lecture and the query; and executing the workflow in order to generate an output that is responsive to the query.

Abstract: A method for providing portfolio deviation analytics to facilitate collateral management is disclosed. The method includes retrieving trade data from a source based on a predetermined schedule, the trade data including transaction information and valuations information; retrieving reference data from a reference data hub; parsing the reference data to identify portfolios and corresponding parameters; identifying a deviation amount for each of the portfolios based on the corresponding trade data and the corresponding parameters; determining a resolution action for each of the portfolios based on the corresponding deviation amount; and automatically initiating the resolution action.

Abstract: A method for using encryption and tokenization to protect confidential data that is stored in a public cloud database is provided. The method includes: receiving a first data set; tokenizing the first data set; obtaining a first token for at least one attribute of the first data set; encrypting an original value of the attribute and the first data set; storing each of the original value of the at least one attribute, the encrypted value of the at least one attribute, and the first token in a first memory; storing each of the first token and the encrypted first data set in a second memory; and storing the tokenized first data set in a third memory that is hosted on a public cloud server.

Abstract: Methods and systems for performing a combinatorial optimization task are provided. The method includes: receiving a first set of data items and a second set of data items; dividing the second set of data items into a first subset and a second subset; generating, based on the first subset, a first set of subset sums, and storing the first set of subset sums as a list; generating, based on the second subset, a second set of subset sums, and storing the second set of subset sums as a hash-map in conjunction with a corresponding hash function; and detecting, based on the first set of data items, the list, and the hash-map, at least one match between a subset sum that corresponds to the second set of data items and a subset sum that corresponds to the first set of data items.

Abstract: A method for automatically classifying and tagging natural language data is disclosed. The method includes receiving, via an application programming interface, requests from various sources, each of the requests including raw data in a natural language format; converting the raw data into structured data sets; determining, by using a model, a metadata output for each of the requests based on the corresponding structured data sets; appending the metadata output to the corresponding requests; determining an action for each of the requests based on the corresponding metadata output; and automatically initiating the action.