Abstract: A device may receive, from an augmented reality device, speech data identifying augmented reality interactions with an augmented reality robot. The device may receive, from a camera, video data identifying movements of a real robot based on the augmented reality interactions with the augmented reality robot. The device may process the speech data to obtain first action data identifying first actions that the real robot is to perform. The device may process the video data to obtain second action data identifying second actions that the real robot is to perform. The device may process the first action data and the second action data to generate pseudocode. The device may transform the pseudocode into code. The device may cause the real robot to execute the code, wherein executing the code causes the real robot to perform the first actions and the second actions.

Abstract: A device may communicate with a first server to obtain first information regarding a particular entity. The device may communicate with a second server to obtain second information regarding a plurality of entities. The device may process the first information and the second information to generate one or more recommendations for the particular entity. The one or more recommendations including a recommendation may relate to the particular entity altering an attribute of the particular entity to match an attribute of one or more of the plurality of entities. The attribute may be associated with a threshold level of performance for the one or more of the plurality of entities. The device may generate a user interface including the one or more recommendations. The device may communicate with a client device to cause the user interface to be provided for display.

Abstract: A method for validating information includes accessing validation rules from a validation rule store and transferring a plurality of received data files and the validation rules to a validation storage space. The method also includes selecting each of the one or more data files defined in the validation configuration file. Each data file includes a plurality of records, each record having values associated with a plurality of attributes. For each data file, the method includes applying the plurality of validation rules to determine valid and invalid content within the data file; and generating a report that specifies the invalid content of each data file.

Abstract: The global proliferation of high speed communication networks has created unprecedented opportunities for geographically distributed resource interaction. A data structure synthesizer provides crowd source project management features, crowd source resource sentiment analysis features, and crowd source resource configuration features.

Abstract: The network simulation platform may determine a plurality of potential links to connect a plurality of target nodes to an existing fiberoptic infrastructure. The network simulation platform may determine a set of potential links, of the plurality of potential links, based on one or more criteria. The network simulation platform may determine, based on the set of potential links, an initial fiberoptic network simulation that includes one or more links. The network simulation platform may determine, for each link of the one or more links, a respective weighted highway score associated with the link and may determine, based on the initial fiberoptic network simulation and the respective weighted highway scores associated with the one or more links of the initial fiberoptic network simulation, a final fiberoptic network simulation. The network simulation platform may cause, based on the final fiberoptic network simulation, one or more actions to be performed.

Abstract: A device may provide a user interface with which to provide an action plan. The device may detect one or more interactions with the user interface associated with identifying one or more portions of the action plan. The action plan may include information regarding a treatment plan for a patient. The device may parse the action plan to identify a set of prompts and/or a set of actions that are to be performed based on a set of triggers. The set of prompts may be related to a clinically validated questionnaire for a particular condition. The device may detect a particular trigger, of the set of triggers, after parsing the action plan. The device may provide, for display via the user interface, a particular prompt, of the set of prompts, or transmit data to perform a particular action, of the set of actions, based on detecting the particular trigger.

Abstract: A multi-layer cluster node optimization (CNO) stack may generate a token containing cluster node optimization prescriptions for detaching nodes from a storage cluster. A prescriptive engine layer of the CNO stack may select target computing resource nodes from a selected cluster based on the utilization tracking data, the optimization metric thresholds, and the CNO interval; utilize a prediction engine to predict respective storage utilizations over a next operation cycle for the nodes of the selected cluster; generate an aggregated storage utilization prediction for the selected cluster based on the predicted storage utilizations; determine a network traffic coefficient for the selected cluster based on the network traffic data; perform a cluster determination whether to execute a cluster node optimization for the selected cluster based on the aggregated storage utilization prediction and the network traffic coefficient; and generate a CNO token based on the cluster determination.

Abstract: Methods, systems, and apparatus for authenticating and authorizing users using quantum key distribution through segmented quantum computing environments. In one aspect, a method includes receiving a first and second plaintext data input from a first party and from a second party, respectively; applying a quantum computation translation operation to the first and second plaintext data inputs to generate a corresponding first sequence of quantum computations and a second sequence of quantum computations; implementing the first and second sequence of quantum computations in a first and second segmented quantum computing environment, respectively, to obtain a first and second sequence of measurement results; generating a first and second encryption key using the first and second sequence of measurement results, respectively, and an encrypted authorization token using the second encryption key; and sending the first encryption key to the first party, and the encrypted authorization token to the second party.

Abstract: Embodiments of the present disclosure provide systems and methods for providing functionality that enables automated generation of advisory and guidance data for designing, managing, and executing UAS flight operations. According to the present disclosure, a location analytics engine may perform analysis and provide requirements based on location, and a technology analytics engine may be provided to determine which UAS platform, sensors, and other technology (e.g., other equipment such as parachutes, etc.) that may be required to perform the desired UAS operations. In embodiments, a mission operational relationships engine may correlate various data associated with the industry, mission type, regulatory environment, location, etc., in order to identify relationship between the various data and determine requirements. An operational advisory engine may leverage the other engines in order to generate the advisory and guidance data.

Abstract: Identification of malicious network domains through use of links analysis of graph representation of network activity, such as a bipartite graphs. An example method includes setting an initial reputation score for each of a plurality of host computers and each of a plurality of domains accessed by the plurality of host computers; until a predefined condition is satisfied, iteratively rescoring the reputation scores for each of the plurality of host computers based upon the reputation scores of the plurality of domains; and rescoring the reputation scores for each of the plurality of domains based upon the reputation scores of the plurality of host computers; and determining, based upon the rescored reputation scores for each of the plurality of host computers and the rescored reputation scores for each of the plurality of domains, whether one or more domains amongst the plurality of domains are exhibiting malicious behavior.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for engineering a data analytics platform using machine learning are disclosed. In one aspect, a method includes the actions of receiving data indicating characteristics of data for analysis, analysis techniques to apply to the data, and requirements of users accessing the analyzed data. The actions further include accessing provider information that indicates computing capabilities of a respective data analysis provider, analysis techniques provided by the respective data analysis provider, and real-time data analysis loads of the respective data analysis provider. The actions further include applying the characteristics of the data, the analysis techniques, the requirements of the users, and the provider information, the analysis techniques, and the real-time data analysis loads to a model.

Abstract: An example chatbot generation platform may receive a request to generate a chatbot; determine a chatbot template for the chatbot based on the request; obtain custom chatbot information according to the chatbot template; generate a chatbot corpus for the chatbot using the custom chatbot information and the chatbot template; generate a set of question and answer (QnA) pairs based on the chatbot corpus; configure a language analysis model for the chatbot; build the chatbot according to the set of QnA pairs and the language analysis model; and deploy the chatbot to a chatbot host platform for operation. The chatbot may be built to engage in an interaction with a user via the chatbot host platform, use the language analysis model to select one or more QnA pairs from the set of QnA pairs during the interaction, and train the language analysis model based on the interaction.

Abstract: A security monitoring platform may use an unsupervised machine learning technique to cluster historical data related to user access rights associated with multiple cloud applications based on various features that relate to user permissions and attributes within the multiple cloud applications. The security monitoring platform may use a supervised machine learning technique to train an access rights data model based on the clustered historical data and perform one or more actions that relate to current access rights assigned to at least one user within one or more of the multiple cloud applications based on a score representing a probability that an access level assigned to the at least one user within the one or more of the multiple cloud applications is correct. The security monitoring platform may apply a reinforcement learning technique to update the access rights data model based on feedback related to the one or more actions.

Abstract: Implementations are directed to receiving communication data from a device, the communication data including data input by a user of the device, determining a context based on an extended finite state machine that defines contexts and transitions between contexts, transmitting a service request to at least one cloud-hosted service, the service request being provided at least partially based on masking sensitive information included in the communication data, receiving a service response from the at least one cloud-hosted service, the service response including one or more of an intent, and an entity, determining at least one action that is to be performed by at least one back-end source system based on the service response, providing a response at least partially based on an action results received from the at least one back-end source system, and transmitting the result data to the device.

Abstract: A device may receive input data identifying user stories, test case documents, event logs, and application logs associated with an application, and may perform natural language processing on the user stories and the test case documents, identified in the input data, to generate a first state diagram associated with the application. The device may process the event logs identified in the input data, with a heuristic miner model, to generate a second state diagram associated with the application, and may process the application logs identified in the input data, with a clustering model, to generate a volumetric analysis associated with the application. The device may perform post processing of the first state diagram, the second state diagram, and the volumetric analysis, to remove duplicate data and unmeaningful data and to generate modified outputs, and may perform actions based on the modified outputs.

Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning to predict future handover success rates of cells of a wireless network and to determine updated network parameter values that may be used to improve the future handover success rates. Clustering algorithms may be applied to handover success rates associated with the cells to group the cells into different clusters. Machine learning (ML) models may be trained based on historical handover data associated with cells of the clusters to predict future handover success rates based on current handover success rates. The output of the ML models may be used to determine one or more updated network parameter values to be implemented by the wireless network to improve future handover success rates at one or more cells.

Abstract: This document describes systems, methods, devices, and other techniques for performing content moderation. In some implementations, a computing device receives input data in relation to an electronic document. The computing device generates, based on the received input data, data representing one or more features of the electronic document and analyzes the generated data representing one or more features of the electronic document to determine one or more reliability scores indicating respective measures of reliability of the electronic document. The reliability scores include one or more of (i) a content reliability score, (ii), an author reliability score, and (iii) a domain reliability score. The computing device indicates, based on one or more of the reliability scores, whether the electronic document is reliable or not.

Abstract: A device may receive contextual data, computational data, experiential data, and industry data associated with software code, and may receive detected vulnerabilities data identified by a scanning model based on the software code and software code metadata of the computational data. The device may process the contextual data, the computational data, and the experiential data, with a contextual identification model, to determine a set of rules and a set of actions, and may enrich, via an enrichment model, the industry data with the experiential data to generate enriched industry data. The device may process the software code metadata, the detected vulnerabilities data, and the enriched industry data, with a correlation model, to generate analysis data, and may process the analysis data and the set of rules, with a security model, to confirm security issues associated with the software code. The device may perform one of the set of actions based on the security issues.

Abstract: A cloud control and management circuitry may provide both static rule based and intelligent dynamic backups of a cloud computing environment. The cloud control and management circuitry may monitor the operating status of the cloud computing environment, perform additional analytics on the monitored status, and provide an intelligent policy that is responsive to various levels of the computing entities of the cloud computing environment, and causes automatic backup to prevent unrecoverable and potentially unexpected failures. The cloud control and management circuitry further provide a uniform interface for automatically and intelligently controlling and predicting backup of the computing environment based on disparate cloud computing platforms.

Abstract: A hierarchical document classification system is disclosed. The system includes a text-based document classifier model for classifying an input electronic document into one of a set of predefined document categories. The system further includes an image-based metadata identification model for classifying electronic documents of a particular document category into a set of metadata categories. The system further includes a fuzzy text matcher for supplementing classification accuracy of the image-based metadata identification model to obtain a metadata category for the input electronic document.