International Business Machines Corporation

Srithar Rajan Thangaraj

Pradeep Raj Jayarathanasamy

Arvind Rangarajan

Vijay Kumar Ananthapur Bache

A method for integrating heterogeneous systems is presented including initiating a conversation between a consumer system having a first artificial intelligence (AI) integrator and a producer system having a second AI integrator, training the first and second AI integrators to enable the conversation between the consumer system and the producer system, upon a data request from a client, enabling the consumer system to receive an application programming interface specification (API Spec) and locate the producer system that provides service in conformance with the API Spec, determining missing data needed to conform to the API Spec to build source code, if the producer system determines that it can support the data request, triggering the producer system to generate a contract, and after consensus is provided, in a deployment phase, generating by the producer system the source code to provide information pertaining to the data request.

Artificial intelligence integrator

A computer-implemented method for sender activated mobile call overloading (SAMCO) is described that includes processors configured for receiving request call data comprising a data request initiated by a sending mobile device intended for a receiving mobile device, receiving active call data corresponding to a telephone call placed by the sending mobile device to the receiving mobile device, wherein the active call data comprises the data request, determining that the receiving mobile device is subscribed to a data request service configured to execute the data request, determining that the sending mobile device is authorized to access the receiving mobile device, and responsive to determining that the sending mobile device is authorized, the method includes processors configured for transmitting the data request to the receiving mobile device.

Sender activated mobile call overloading

A system, method, and computer program product for implementing microservice deployment is provided. The method includes receiving definitions associated with microservices related to implementing hardware and software solutions with respect to hardware and software systems. In response, a definition file and associated code comprising the definitions and associated dependencies associated with the microservices are generated. The microservices are deployed to a container orchestration system cluster on a cloud structure and a service mesh and machine learning module are installed within the container orchestration system cluster. Proxies comprising a proxy for each pair of dependencies are generated and network traffic passing through each proxy is monitored. A malfunction of a hardware or software system is detected and an associated network route passing through an associated proxy is disabled.

Microservice hardware and software deployment

Embodiments of the present invention provide a computer system a computer program product, and a method that comprises converting the retrieved data to a uniform syntax for data assessment; performing a query on a plurality of external data sources for additional information associated with the converted data; analyzing a plurality of indicative markers associated with the retrieved data and the additional information; generating a plurality of machine learning models associated with the converted data based on the analysis of each indicative markers within the plurality of indicative markers; dynamically selecting at least one generated machine learning model within the plurality of generated machine learning models associated with the retrieved data based on an analysis of the plurality of indicative markers associated with the retrieved data and the additional information; and automatically verifying an accuracy value associated with the at least one selected generated machine learning model.

Dynamic updating of digital data

Computer-implemented methods, computer program products, and computer systems for testing a voice assistant device may include one or more processors configured for receiving test data from a database, wherein the test data may include a first set of coding parameters and a first user utterance having an expected device response. Further, the one or more processors may be configured for generating a first modified user utterance by applying the first set of coding parameters to the first user utterance, wherein the first modified user utterance is acoustically different than the first user utterance. The one or more processors may be configured for audibly presenting the first modified user utterance to a voice assistant device, receiving a first device response from the voice assistant device, and determining whether the first voice assistant response is substantially similar to the expected device response.

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Chennai, India

Srithar Rajan Thangaraj