Abstract: The invention concerns a query response device comprising: an input adapted to receive user queries; a memory (106) adapted to store one or more routing rules; one or more live agent engines (116) configured to support interactions with one or more live agents; one or more virtual assistant engines (120) configured to support interactions with one or more virtual assistants instantiated by an artificial intelligence module (103); and a routing module (104) coupled to said live agent engines and to said virtual assistant engines, the routing module comprising a processing device configured: to select, based on content of at least a first user message from a first user relating to a first user query and on said one or more routing rules, a first of said live agent engines or a first of said virtual assistant engines; and to route one or more further user messages relating to the first user query to the selected engine.

Abstract: Examples of systems and method for data transition are described. In an example, the present disclosure provides for automating the process of data movement from on premise to cloud, i.e., source Data warehouse (DWH) movement, ETL to cloud base DWH, ETL. The present disclosure provides for objects identification, metadata extraction, automated data type mapping, target data definition script creation, data extraction in bulk using source native optimized utilities, users and access control mapping to the target DWH, binary object movement, end-end audit report, and reconciliation reports.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for service oriented software-defined security framework are disclosed. In one aspect, a system includes a security control device, one or more assets, and a security controller that communicates with the security control device and the one or more assets. The security controller includes a processing engine configured to register the security control device by creating a physical-logical attribute mapping for the security control device, and generating a security service description associated with the security control device. The processing engine is further configured to register the one or more assets by creating a physical-logical attribute mapping for each of the one or more assets, and generating security service requirements for each of the one or more assets. The processing engine is further configured to generate a security service binding based on a request for service.

Abstract: A device may receive first information associated with an asset that is associated with a project. The device may determine a plurality of cost elements associated with the project based on the first information. The device may determine a plurality of sub-elements associated with the project based on the plurality of cost elements and the first information. The device may generate a plurality of hypotheses corresponding to the plurality of sub-elements. The device may receive second information associated with the hypotheses. The device may determine impact factors associated with the plurality of hypotheses based on the second information. The device may generate an estimate based on the impact factors. The device may determine a project execution date, associated with the project, based on the estimate. The device may cause an action to be performed in association with the asset based on the project execution date.

Abstract: A system includes one or more devices to receive a first set of data. The system transmits the first set of data to a first data store for storage. The first data store is of a first data format type. The system transmits the first set of data to a node of a plurality of nodes. The node to perform an action on the first set of data and a second set of data to generate a third set of data. The node to transmit the third set of data to a third data store. The third data store being of a third data format type that is different than the first data format type and the second data format type. The system transmits the third set of data from the third data store to the first data store for reporting.

Abstract: A device may obtain first data regarding a set of events. The device may obtain second data regarding a user. The device may process the first data and the second data to identify one or more events, of the set of events, for participation by the user. The device may receive, via a user interface, a selection of a particular event of the one or more events. The device may receive, via the user interface, a set of prompts relating to participation in the particular event. The device may detect an interaction with the user interface associated with responding to the set of prompts. The device may provide information identifying the user based on the interaction with the user interface associated with responding to the set of prompts.

Abstract: Systems and methods for predictively responding to real-time sensor data from an computer-augmented environment are provided. A system may receive sensor data from the computer-augmented environment. The system may obtain a feature model, a prediction model, and a filter criteria. The system may derive, based on the feature model and the sensor data, a first event. The system may determine the first event is associated with an authorized event identifier in the filter criteria. The system may forecast, based on the authorized event identifier and the prediction model that a second event occurs after the first event. The system may transmit an action message to the computer-augmented environment, the action message indicative of the second event. Updates to the feature model, the prediction model, and/or the filter criteria may occur in batch using machine learning and statistical analytics while the real-time platform predictively responds to the sensor data.

Abstract: In some examples, natural language processing based sign language generation may include ascertaining a speech video that is selected by a user, and determining, based on application of natural language processing to contents of the speech video, a plurality of sentences included in the speech video. For each sentence of the plurality of sentences identified in the speech video, a sign language sentence type, a sign language sentence structure, and a sentiment may be determined. For each sign language sentence structure and based on a corresponding sentiment, a sign video may be determined. Based on the sign video determined for each sentence of the plurality of sentences identified in the speech video, a combined sign video may be generated.

Abstract: Examples of malware detection are provided. In an example, to detect malwares, a first subset of features may be determined from a binary file. The binary file may be analyzed based on machine learning model to determine a category of malware, which is based on a degree of detectability of the category. A first category may have a lower detectability of malware in the binary file and a second category may have a higher detectability than the first. A model may then be created to analyze the first category of malware and an analysis of the binary may be performed. The analysis may be performed using the model. Thereafter, a confidence score may be generated for the binary file. The confidence score may be indicative of certainty of determining whether the binary file is goodware or includes malware. Malware may be detected upon the confidence score exceeding a threshold value.

Abstract: An Artificial Intelligence (AI) based data transformation system receives a process document and automatically generates processor-executable code which enables automatic execution of a process as detailed within the process document. Various structural elements of the process documents are identified and the data from the document is clustered based on common parameters which can include the structural elements or textual data from the process document. The contextual information including conditional and non-conditional statements along with the entities and entity attributes are also obtained. The domain knowledge is superimposed on the contextual information to generate flows that represent procedures which make up the process to be automated. Platform specific code for the automatic execution of the process is automatically generated from the flows.

Abstract: A device may perform a first authentication operation, associated with a contactless media device, using a first key. The first key may permit a security mode of the contactless media device to be modified. The device may cause the contactless media device to set the security mode to a first security mode that causes the contactless media device to secure at least one transmission from the contactless media device. The device may perform a second authentication operation, associated with the contactless media device, using a second key that permits information to be read from or written to the contactless media device. The device may read first secured information from or write second secured information to the contactless media device. The first secured information or the second secured information may be secured based on the security mode of the contactless media device being set to the first security mode.

Abstract: Resource visualization, evaluation, and selection is often a difficult, complex, technically challenging endeavor. This is particularly true when there the resource set is extensive, the resources have widely varying attributes and capabilities, and the resources are also widely disbursed geographically. A multi-dimensional resource evaluation and visualization system implements technical solutions to these technical challenges.

Abstract: A device may receive lifestyle information corresponding to an individual with a medical condition. The device may create a lifestyle timeline, associated with the individual, that includes a plurality of items of lifestyle information, included in the lifestyle information, arranged in a chronological order. The device may generate, based on the lifestyle timeline, a recommendation or a prediction associated with a metric related to the medical condition. The recommendation may be generated based on one or more of the plurality of items of lifestyle information. The prediction may be generated using a prediction model that uses one or more of the plurality of items of lifestyle information as input, and generates the prediction using the prediction model. The device may provide information associated with the recommendation or the prediction to identify a dosage associated with treating or managing the medical condition.

Abstract: In some examples, temporal variation identification of regulatory compliance based robotic agent control may include ascertaining a temporal sequence of compliance specification text, where the temporal sequence may include time points and versions of the compliance specification text at the time points. For each time point of the temporal sequence of the compliance specification text, a compliance specification graph may be generated. Based on an analysis of each of the generated compliance specification graphs, changes in the temporal sequence of the compliance specification text may be determined. Further, an operation associated with a robotic agent may be controlled by the robotic agent and based on the determined changes in the temporal sequence of the compliance specification text.

Abstract: In some examples, image content moderation may include classifying, based on a learning model, an object displayed in an image into a category. Further, image content moderation may include detecting, based on another learning model, the object, refining the detected object based on a label, and determining, based on the another learning model, a category for the refined detected object. Further, image content moderation may include identifying, based on the label, a keyword associated with the object, and determining, based on the identified keyword, a category for the object. Further, image content moderation may include categorizing, based on a set of rules, the object into a category, and moderating image content by categorizing, based on aforementioned analysis the object into a category. Yet further, image content moderation may include tagging, based on fusion-based tagging, the object with a category and a color associated with the object.

Abstract: A system includes circuitry for cryptographic data share controls for distributed ledger technology based data constructs. The system may support placement of compute data on to a distributed ledger technology based data construct. The compute data may have multiple layers of encryption to support permissions and coordination of processing operations for application to the compute data. The multiple layers of encryption may include a homomorphic layer to allow sharing of the compute data for processing by a compute party without divulging the content of the compute data with the compute party. While in the homomorphically encrypted form, the homomorphic compute data supports the application of processing operations while maintaining the secrecy of the underlying data.

Abstract: Systems and methods for entitlement tracking and control with blockchain technology are provided. A server node may receive usage information indicating usage of a licensed component by a remote device. The server node may generate a datablock that includes the usage information and append the datablock to a blockchain. The server node may acquire, from the blockchain, a license smart contract. The license smart contract may include control logic to control access to the license component. The server node may control access to the license component by the remote device based on the usage information and the control logic.

Abstract: A device may receive video of a facility from an image capture system. The video may show an individual within the facility, an object within the facility, or an activity being performed within the facility. The device may process the video using a technique to identify the individual within the facility, the object within the facility, or the activity being performed within the facility. The device may track the individual, the object, or the activity through the facility to facilitate an analysis of the individual, the object, or the activity. The device may perform the analysis of the individual, the object, or the activity using information related to tracking the individual, the object, or the activity. The device may perform an action related to the individual, the object, or the activity based on a result of the analysis. The action may positively impact operations of the facility.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for user interface generation for transacting goods are disclosed. In one aspect, a method includes receiving order data, user data, and other data. The method further includes determining, for a particular user, an order confidence score that corresponds to a likelihood that the particular user ordered a particular good from a particular vendor on a particular day. The method further includes receiving vendor-type mapping data. The method further includes determining a good-type confidence score that corresponds to the likelihood that the particular good or the particular vendor is associated with a particular type of good. The method further includes determining a composite confidence score. The method further includes storing the composite confidence score, data identifying the particular user, data identifying the particular type of good, and data identifying the particular date.

Abstract: An artificial intelligence system for managing a consumer relationship is provided. The artificial intelligence system includes: one or more client entities; a storage device configured to store data related to actions and characteristics of the one or more client entities, the actions and characteristics relating to payment of accounts receivable; one or more machine learning server devices configured to generate and update a machine learning model based on previous actions and characteristics of said one or more client entities; and predict future actions of the one or more client entities with respect to the payment of accounts receivable, based on the machine learning model.