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 for orchestrating an operation is disclosed. The system includes an case orchestration engine to identify a discrepancy in the operation, and to generate a plurality of hypotheses for resolving the discrepancy. The case orchestration engine further collects evidence pertaining to the discrepancy in the operation, evaluates each of the plurality of hypotheses based on a dialogue-driven feedback received from a user, and selects one of the plurality of hypotheses for resolving the discrepancy based on the evidence and an expected outcome of the operation. The case orchestration engine provides reasons for the discrepancy along with remedial measures for resolving the discrepancy based on the selected hypothesis, and then generates a plan for performing the operation to achieve the expected outcome based on the remedial measures.

Abstract: Systems and methods for orchestrating a process are disclosed. In an implementation, a system is configured to extract process information associated with the process. Based on the process information, the system is configured to determine a current model of performing the process based on the process information. The system is further configured to retrieve regulatory information associated with the process, wherein the regulatory information is indicative of at least one of a predefined policy, a predefined rule, and a predefined regulation associated with the process. Further, the system is configured to update the current model based on at least one of the process information and the regulatory information for obtaining a predefined outcome of the process.

Abstract: A system for reconciliation comprises a determination engine to determine whether data is structured or unstructured, a data structuring engine to structure the data, and a rule extraction engine to determine relations between pairs of values of a first set and a second set of data. The system further comprises a matching engine to generate a confidence score for each pair of the values, a categorization engine to classify the pairs of values into matched pairs and unmatched pairs, a validation engine to validate matching and classification of the pairs based on a user feedback, and a learning engine to store details pertaining to the validation of the matching and the classification over a period of time. The learning engine forwards the details to the rule extraction engine and the categorization engine to determine the relations between subsequent pairs of values and classify the pairs based on the stored details.

Abstract: A method and system are provided. The system includes a network configurator for configuring a network as a backplane of the system to optimize throughput rate and minimize latency across a plurality of subsystems that are cloud-based and that form the system. The system further includes a composable system building block configurator for refactoring the plurality of subsystems to use the network to communicate as a single system. The system also includes a system resource multidimensional model generator for generating a multidimensional optimization model that models the composable system building blocks as resources having adjustable parameters in a multidimensional parameter space.

Abstract: Systems, methods and articles of manufacture are disclosed for building and executing analytics solutions. Such a solution may provide a comprehensive analytics solution (e.g., a risk assessment, fraud detection solution, dynamic operational risk evaluations, regulatory compliance assessments, etc.). The analytics solution may perform an analytics task using operational data distributed across a variety of independently created and governed data repositories in different departments of an organization. A framework is disclosed which allows a user (e.g., a risk analyst) to compose analytical tools that can access data from a variety of sources (both internal and external to an enterprise) and perform a variety of analytic functions.

Abstract: There is a computer program product and computer system that includes program instructions programmed to identify, in a software-defined environment, a security container describing a workload and a set of resources required by the workload, the security container including self-describing sub-containers having associated metadata describing content of a respectively corresponding sub-container; determine, for the workload, a set of resource-divisible portions of the workload including a compute-resource portion; generate a plurality of sub-containers within the security container, a sub-container within the plurality of sub-containers being a self-describing sub-container having associated metadata describing the content of the sub-container representing only one resource-divisible portion, the sub-container being an operating system sub-container; and responsive to identifying a security event while processing the workload, adjust a security mechanism associated with the security container.

Abstract: There is a computer program product and computer system that includes program instructions programmed to establish a security container describing a workload and a set of resources in a software-defined environment, the security container including a set of sub-containers that are self-describing sub-containers having associated metadata describing content of a respectively corresponding sub-container, each sub-container of the set of sub-containers respectively corresponds to a resource-divisible portion of the workload, the set of resources being required by the workload, wherein a sub-container of the set of sub-containers is an operating system sub-container; monitor the workload and the set of resources for security events; and responsive to identifying a security event, adjust isolation mechanisms provided by the plurality of sub-containers at various layers of a stack. The set of sub-containers represents an end-to-end run time environment for processing the workload using the set of resources.

Abstract: A method and system are provided. The system includes a network configurator for configuring a network as a backplane of the system to optimize throughput rate and minimize latency across a plurality of subsystems that are cloud-based and that form the system. The plurality of subsystems includes hardware and software subsystems. The system further includes a composable system building block configurator for refactoring, based on a disaggregated system principle, the plurality of subsystems to use the network to communicate as a single system. The system also includes a system resource multidimensional model generator for generating a multidimensional optimization model that models the composable system building blocks as resources having adjustable parameters in a multidimensional parameter space.

Abstract: Examples of job allocation are described hereon. In an example, a job for allocation may be received. The job may be analyzed to obtain information pertaining to the job. The information may comprise at least one of a domain of the job and a priority level of the job. Further, performance of resources may be determined to provide resource information. The resource information may be determined using a supervised learning model comprising a job vector for each job type and a resource vector corresponding to each resource. The resource information may include a list of resources with at least one of a corresponding probability of each resource completing the job and a performance score of each resource. Based on the job information and the resource information, the resource may be recommended for the job using an expertise-estimation modeling technique and the job may be assigned to the recommended resource, accordingly.

Abstract: A curator captures input data corresponding to service tasks from an external source. Further, a browser extension collects intermediate service delivery data for the service tasks from the external source. Subsequently, a learner stores the input data and the intermediate service delivery data as training data. Then, a receiver receives a service request from a client. The service request is indicative of a service task to be performed and information associated with the service task. Further, an advisor processes the service request to generate an intermediate service response. Thereafter, the advisor determines a confidence level associated with the intermediate service response and ascertains whether the confidence level associated with service response is below pre-determined threshold level. If the confidence level is below a pre-determined threshold level, the advisor automatically generates a final service response corresponding to service request based on training data.

Abstract: There is a method and system that includes establishing a security container that describes a workload and a set of resources that corresponds to the workload in a software-defined environment, determining a set of security criteria for the security container, monitoring the workload and the set of resources for security events based, at least in part, upon the set of security criteria, and responsive to identifying a security event, adjusting one or more security mechanisms. The steps of monitoring and adjusting are operated within the software-defined environment.

Abstract: A method and system are provided. The system includes a network configurator for configuring a network as a backplane of the system to optimize throughput rate and minimize latency across a plurality of subsystems that are cloud-based and that form the system. The plurality of subsystems includes hardware and software subsystems. The system further includes a composable system building block configurator for refactoring, based on a disaggregated system principle, the plurality of subsystems to use the network to communicate as a single system. The system also includes a system resource multidimensional model generator for generating a multidimensional optimization model that models the composable system building blocks as resources having adjustable parameters in a multidimensional parameter space.

Abstract: A method and device for provisioning bare-metal servers to tenants of a cloud provider is provided. The cloud provider operating a datacenter receives a profile of a tenant. The cloud provider identifies a set of physical resources subscribed by the tenant based on the tenant's profile and identifies a bare-metal server in the datacenter having sufficient physical resources to provide the subscribed physical resources. The cloud center reports to the tenant a set of physical resources in the BM server that corresponds to the subscribed set of physical resources. The cloud center receives a request from the tenant to provision a tenant bare metal machine in the datacenter. The cloud center enables at least one of the reported physical resources in the bare-metal server for the tenant, based on the request, and disables remaining reported physical resources in the bare-metal.

Abstract: There is a method and system for capability-based resource allocation in a software-defined environment that performs the following steps (not necessarily in the following order): (i) determining a set of capability characteristics for a plurality of workload resources within a software-defined environment; (ii) determining a set of workload components for a specified workload; and (iii) identifying a set of workload resources from the plurality of workload resources to allocate to the specified workload based, at least in part, on the set of capability characteristics corresponding to each workload within the set of workload resources. A workload component of the set of workload components has a unique set of workload characteristics.

Abstract: A method and system for outcome-based adjustment of a software-defined environment (SDE) that includes establishing a link between a business outcome and a first resource configuration from software defined environment, establishing a monitoring mechanism for continuously measuring a current state of the SDE, using a behavior model of the SDE to anticipate, or forecast, a triggering event, and responsive to the forecast of a triggering event, using the behavior model to determine a second resource configuration to achieve the business outcome. The link includes at least one of a utility of services for the business outcome, a cost of a set of resources consumed by the first resource configuration, and a risk of the set of resources becoming unavailable.

Abstract: Outcome-based adjustment of a software-defined environment (SDE) includes determining a business operation and a corresponding set of tasks to be performed in a software defined environment (SDE), establishing a first resource configuration to perform the corresponding set of tasks to achieve a business outcome target, determining a first resource cost for performing the corresponding set of tasks, assigning a priority level to tasks within the corresponding set of tasks, determining a set of performance indicators corresponding to a task having a first priority level, monitoring the SDE to identify a triggering event, responsive to identifying the triggering event, establishing a second resource configuration based, at least in part, on a performance level of a performance indicator in the set of performance indicators, the second resource configuration addressing the triggering event, and determining a second resource cost for performing the corresponding set of tasks according to the second resource config

Abstract: A method and system for outcome-based adjustment of a software-defined environment (SDE) that includes establishing a link between a business outcome and a first resource configuration from software defined environment, establishing a monitoring mechanism for continuously measuring a current state of the SDE, using a behavior model of the SDE to anticipate, or forecast, a triggering event, and responsive to the forecast of a triggering event, using the behavior model to determine a second resource configuration to achieve the business outcome. The link includes at least one of a utility of services for the business outcome, a cost of a set of resources consumed by the first resource configuration, and a risk of the set of resources becoming unavailable.

Abstract: There is a method and system that includes establishing a security container that describes a workload and a set of resources that corresponds to the workload in a software-defined environment, determining a set of security criteria for the security container, monitoring the workload and the set of resources for security events based, at least in part, upon the set of security criteria, and responsive to identifying a security event, adjusting one or more security mechanisms. The steps of monitoring and adjusting are operated within the software-defined environment.

Abstract: There is a method and system that includes establishing a security container that describes a workload and a set of resources that corresponds to the workload in a software-defined environment, determining a set of security criteria for the security container, monitoring the workload and the set of resources for security events based, at least in part, upon the set of security criteria, and responsive to identifying a security event, adjusting one or more security mechanisms. The steps of monitoring and adjusting are operated within the software-defined environment.