Abstract: Various embodiments discussed herein enable client applications to be heavily integrated with a voice assistant in order to both perform commands associated with voice utterances of users via voice assistant functionality and also seamlessly cause client applications to automatically perform native functions as part of executing the voice utterance. For example, some embodiments can automatically and intelligently cause a switch to a page the user needs and automatically and intelligently cause a population of particular fields of the page the user needs based on a user view context and the voice utterance.

Abstract: Various embodiments discussed herein enable client applications to be heavily integrated with a voice assistant in order to perform commands associated with voice utterances of users via voice assistant functionality and also seamlessly cause client applications to automatically perform native functions as part of executing the voice utterance. Such heavy integration also allows particular embodiments to support multi-modal input from a user for a single conversational interaction. In this way, client application user interface interactions, such as clicks, touch gestures, or text inputs are executed alternative or in addition to the voice utterances.

Abstract: Various embodiments discussed herein enable client applications to be heavily integrated with a voice assistant in order to both perform commands associated with voice utterances of users via voice assistant functionality and also seamlessly cause client applications to automatically perform native functions as part of executing the voice utterance. For example, some embodiments can automatically and intelligently cause a switch to a page the user needs and automatically and intelligently cause a population of particular fields of the page the user needs based on a user view context and the voice utterance.

Abstract: Various embodiments discussed herein enable client applications to be heavily integrated with a voice assistant in order to both perform commands associated with voice utterances of users via voice assistant functionality and also seamlessly cause client applications to automatically perform native functions as part of executing the voice utterance. For example, some embodiments can automatically and intelligently cause a switch to a page the user needs and automatically and intelligently cause a population of particular fields of the page the user needs based on a user view context and the voice utterance.

Abstract: Embodiments are directed to probabilistic neural programs, a framework for program induction that permits flexible specification of the computational model and inference algorithm, while simultaneously enabling the use of deep neural networks. The approach implemented by one or more embodiments builds on computation graph frameworks for specifying neural networks by adding an operator for weighted nondeterministic choice that is used to specify the computational model. Thus, a program sketch describes both the decisions to be made and the architecture of the neural network used to score these decisions. The computation graph interacts with nondeterminism: the scores produced by the neural network determine the weights of nondeterministic choices, while the choices determine the network's architecture.