International Business Machines Corporation

Anvita Vyas

Vijay Ekambaram

Sarbajit Kumar Rakshit

Namit Kabra

Hemant Kumar Sivaswamy

Tarun Tater

Saranga Dhar Tripathy

A system and method are disclosed that utilizes an artificial intelligence based virtual proxy node. The virtual proxy node includes an intent resolution model and communicates between a smart audio device and at least one secondary device, wherein the at least one secondary device is configured to be controlled by a smart audio device or smart hub. The virtual proxy node tracks interactions between the smart audio device and the at least one secondary device to derive historical and context data from the tracking interactions. The virtual proxy node uses the historical and context data to predict which secondary device will be successful in responding to the user input command and broadcasts the input command to the virtual proxy node associated with one of the at least one secondary device. The virtual proxy node includes an intent resolution model trained by historical and context data.

AI-based virtual proxy nodes for intent resolution in smart audio devices

An approach is disclosed that receives a code segment from a source code file. The received code segment is inputted to a trained knowledge manager from which one or more comparable code segments are received. Each of the comparable code segments are identified as having similar functionality as the selected code segment and each of the comparable code segments has a set of metadata. The metadata is used to select one of the comparable code segments and this selected code segment is used to replace the original code segment in the source code file.

Identify, suggest, and auto-implement best practices for requirement specific software development

A computer-implemented method comprises determining a desired resolution quality of a media file; determining available resources of a computing device; selecting one of a plurality of Generative Adversarial Network (GAN) plugins based on the determined available resources of the computing device; and estimating a second resolution quality of the media file corresponding to the selected GAN plugin. The second resolution quality is less than the desired resolution quality. The method further comprises communicating with a server to receive the media file at the estimated second resolution quality; converting the received media file from the second resolution quality to the desired resolution quality by using the selected GAN plugin; and outputting the converted media file with the desired resolution quality.

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Deori, India

Anvita Vyas