Abstract: Methods, systems, devices, and computer-readable media for generating authentication policy recommendations and insights using generative AI are described. An authentication policy recommendation system associated with an identity management system may receive a request from a client organization for an authentication policy configuration recommendation for an application associated with the client organization. One or more recommended authentication policy rules may be generated for the application using a machine learning model (such as a large-learning model). The model may output the authentication policy rules in a machine-readable format. Based on an analysis of applying information about the client organization to the model-generated recommended authentication policy rule to generate a context-specific recommended authentication policy rule, an impact of implementing the context-specific recommended authentication policy rule may be determined and output.

Abstract: A computer-implemented method to generate robotic instructions is disclosed. The method may include receiving video data demonstrating one or more tasks and text data related to the one or more tasks. Further, the method may include encoding the video data and the text data, wherein the encoding is generated using at least one cross-attentional transformer. The method also includes receiving image data providing environmental data for at least one robotic task. Furthermore, the method may include encoding vision data corresponding to the image data. Consequently, the method may include generating robotic instructions based upon the video data, the text data and the vision data that was encoded.

Abstract: A computer-implemented system and method for managing and executing activities for uninterrupted processing. At least one process definition representing a plurality of activities to be executed by computing devices located outside of at least one firewall associated with a data communications network is accessed. Respective ones of the plurality of activities are identified and, for each: input representing details associated with the respective one of the plurality of activities is accessed and at least one computing device is determined to execute steps associated with the respective one of the plurality of activities. Information associated with the respective one of the plurality of activities is transmitted to the computing device(s). A response representing output from the executed steps associated with the respective one of the plurality of activities is received and stored.

Abstract: A computer-implemented method or system is provided for generating programming code automatically for performing database operations. At least one computing device accesses at least one input file. The at least one input file is processed by the at least one computing device to identify at least one operation to be performed on an object associated with a database, wherein the processing further includes generating a database schema. Further, the at least one computing device is configured to generate a plurality of data files representing the at least one operation, and to sort information in the at least one data file. Further, the at least one computing device is configured to determine, as a function of the sorting, an order of steps associated with the at least one operation. Programming code is automatically generated for performing the at least one database operation in accordance with the determined order of steps.

Abstract: An authentication system for financial transactions is disclosed. For non-disabled consumers, the authentication system sends authentication messages that have been formatted using a standard format that is easy for non-disabled consumers to interpret but which is more difficult for disabled consumers to accurately interpret. The authentication system assists disabled consumers by sending authentication messages to disabled consumers in a non-standard format that is easier to interpret than standard authentication messages.

Abstract: A device may receive a three-dimensional (3D) computer-aided design (CAD) model, and may generate an assembly graph with nodes that represent components and edges that represent contact between the components. The device may generate component graphs for the components, and may generate an assembly descriptor based on the assembly graph and the component graphs. The device may process the assembly descriptor, with a graph convolution network model, to generate node embeddings, and may apply pooling to the node embeddings to generate graph embeddings. The device may calculate a cross attention between the components to generate component interrelations, and may utilize the graph embeddings and the component interrelations to predict links between the components. The device may predict poses and joint axes for the components, and may generate assembly instructions based on the graph embeddings, the component interrelations, the links, the poses, and the joint axes.

Abstract: In some implementations, a robot host may receive a video associated with assembly using a plurality of sub-objects. The robot host may determine spatio-temporal features based on the video and may identify a plurality of actions represented in the video based on the spatio-temporal features. The robot host may map the plurality of actions to the plurality of sub-objects to generate an assembly plan and may combine output from a point cloud model and output from a color embedding model to generate a plurality of sets of coordinates corresponding to the plurality of sub-objects. The robot host may perform object segmentation to estimate a plurality of grip points and a plurality of widths corresponding to the plurality of sub-objects. Accordingly, the robot host may generate instructions, for robotic machines, based on the assembly plan, the plurality of sets of coordinates, the plurality of grip points, and the plurality of widths.

Abstract: Methods, systems, devices, and computer-readable media for generating authentication policy recommendations and insights using generative AI are described. An authentication policy recommendation system associated with an identity management system may receive a request from a client organization for an authentication policy configuration recommendation for an application associated with the client organization. One or more recommended authentication policy rules may be generated for the application using a machine learning model (such as a large-learning model). The model may output the authentication policy rules in a machine-readable format. Based on an analysis of applying information about the client organization to the model-generated recommended authentication policy rule to generate a context-specific recommended authentication policy rule, an impact of implementing the context-specific recommended authentication policy rule may be determined and output.

Abstract: A method of accessing data from a data storage device includes transmitting a request including a first part to the data storage device, based on availability of memory in host device. The first part includes data access information and one or more parameters for accessing data from data storage device. The method further includes receiving a first notification from the data storage device, indicating a transfer of the data to a storage buffer associated with the data storage device. The method further includes accessing the data from the data storage device by transmitting second part of request to the data storage device. The second part includes buffer information associated with a host buffer of host device. The data is transferred by the data storage device from the storage buffer to the host buffer of host device using buffer information.

Abstract: A method, computer program product, and computing system for obtaining, by a computing device, encounter information of a patient encounter, wherein the encounter information may include audio encounter information obtained from at least a first encounter participant. The audio encounter information obtained from at least the first encounter participant may be processed. A user interface may be generated displaying a plurality of layers associated with the audio encounter information obtained from at least the first encounter participant. A user input may be received from a peripheral device to navigate through each of the plurality of layers associated with the audio encounter information displayed on the user interface.

Abstract: A device may receive a three-dimensional (3D) computer-aided design (CAD) model, and may generate an assembly graph with nodes that represent components and edges that represent contact between the components. The device may generate component graphs for the components, and may generate an assembly descriptor based on the assembly graph and the component graphs. The device may process the assembly descriptor, with a graph convolution network model, to generate node embeddings, and may apply pooling to the node embeddings to generate graph embeddings. The device may calculate a cross attention between the components to generate component interrelations, and may utilize the graph embeddings and the component interrelations to predict links between the components. The device may predict poses and joint axes for the components, and may generate assembly instructions based on the graph embeddings, the component interrelations, the links, the poses, and the joint axes.

Abstract: A method of accessing data from a data storage device includes transmitting a request including a first part to the data storage device, based on availability of memory in host device. The first part includes data access information and one or more parameters for accessing data from data storage device. The method further includes receiving a first notification from the data storage device, indicating a transfer of the data to a storage buffer associated with the data storage device. The method further includes accessing the data from the data storage device by transmitting second part of request to the data storage device. The second part includes buffer information associated with a host buffer of host device. The data is transferred by the data storage device from the storage buffer to the host buffer of host device using buffer information.

Abstract: Implementations are directed to processing a content object model through a ML model to provide a set of base content feature representations, processing a style object model through the ML model to provide a set of base style feature representations, executing iterations including: generating, by the ML model, a set of stylized feature representations for an initial stylized object model, the initial stylized object model having one or more adjusted parameters relative to a previous iteration, determining a total loss based on the set of stylized feature representations, the set of base content feature representations, and the sets of base style feature representations, and determining that the total loss is non-optimized, and in response, initiating a next iteration, executing an iteration including determining that the total loss is optimized, and in response providing the initial stylized object model as output of the iterative process.

Abstract: In some examples, artificial intelligence-based intelligent programming assistance may include ascertaining, for a software program that is to be completed, code for the program, and identifying, based on an analysis of error message-based contextual information associated with the ascertained code, an error in the ascertained code. A resolution to the identified error may be generated, and the code may be modified to resolve the identified error, Based on an analysis of problem description-based contextual information associated with the ascertained code, a next token associated with the ascertained code may be generated, and used to generate further code for the program. A performance of a user may be analyzed with respect to generation of the code for the program to generate feedback for the user. A query associated with the program may be ascertained from the user, and classified by utilizing an ontology to generate a response to the query.

Abstract: A method performed by a storage device for reducing latency of read operations performed on the storage device, includes: transmitting Host Memory Buffer (HMB) destination information to a host device. The HMB destination information relates to a read destination space reserved within a HMB of the host device. The method also includes receiving a read request from the host device for performing at least one data read operation on a memory of the storage device. The read request specifies data to be read from the memory of the storage device. The method further includes: performing the at least one data read operation on the memory for reading the data specified in the read request and transmitting the data read from the memory to the read destination space reserved within the HMB of the host device.

Abstract: Systems and methods that support functionality for performing disassembly sequence planning are disclosed. The systems and methods may obtain 3D model data for a product to be disassembled and may convert the 3D model to one or more graph-based representations. An encoder is provided to generate a set of embeddings based on the one or more graph-based representations. A decoder is provided to generate disassembly data based on the set of embeddings. In an aspect, the disassembly data may indicate an order in which each component is to be removed during disassembly of the product and a direction in which each component should be removed.

Abstract: A method for adapting text message communications in electronic financial transactions to accommodate users with color vision deficiency. During a registration process, a primary account number, a selection of an enrollment in a color vision deficiency accommodation service, a selection of a preferred critical text color, and an electronic device identifier are received from a user. During a subsequent electronic card present transaction process, the primary account number and the electronic device identifier are received from the user via a payment gateway webpage. During an adaptation process, a text of a message containing a critical text element communicated to the user regarding the transaction is adapted by presenting the critical text element in the preferred critical text color previously selected by the user. The message may be adapted within a template, or the message may be dynamically adapted by searching the message and identifying the critical text element.

Abstract: A method for adapting text message communications in electronic financial transactions to accommodate users with color vision deficiency. During a registration process, a primary account number, a selection of an enrollment in a color vision deficiency accommodation service, a selection of a preferred critical text color, and an electronic device identifier are received from a user. During a subsequent electronic card present transaction process, the primary account number and the electronic device identifier are received from the user via a payment gateway webpage. During an adaptation process, a text of a message containing a critical text element communicated to the user regarding the transaction is adapted by presenting the critical text element in the preferred critical text color previously selected by the user. The message may be adapted within a template, or the message may be dynamically adapted by searching the message and identifying the critical text element.

Abstract: Implementations are directed to processing a content object model through a ML model to provide a set of base content feature representations, processing a style object model through the ML model to provide sets of base style feature representations, executing iterations including: generating, by the ML model, sets of stylized feature representations for an initial stylized object model, the initial stylized object model having one or more adjusted parameters relative to a previous iteration, determining a total loss based on the sets of stylized feature representations, the set of base content feature representations, and the sets of base style feature representations, and determining that the total loss is non-optimized, and in response, initiating a next iteration, executing an iteration of the iterative process, the iteration including determining that the total loss is optimized, and in response providing the initial stylized object model as output of the iterative process.

Abstract: In some implementations, a robot host may receive a video associated with assembly using a plurality of sub-objects. The robot host may determine spatio-temporal features based on the video and may identify a plurality of actions represented in the video based on the spatio-temporal features. The robot host may map the plurality of actions to the plurality of sub-objects to generate an assembly plan and may combine output from a point cloud model and output from a color embedding model to generate a plurality of sets of coordinates corresponding to the plurality of sub-objects. The robot host may perform object segmentation to estimate a plurality of grip points and a plurality of widths corresponding to the plurality of sub-objects. Accordingly, the robot host may generate instructions, for robotic machines, based on the assembly plan, the plurality of sets of coordinates, the plurality of grip points, and the plurality of widths.