Abstract: Implementations described herein are directed to enabling collaborative ranking of interpretations of spoken utterances based on data that is available to an automated assistant and third-party agent(s), respectively. The automated assistant can determine first-party interpretation(s) of a spoken utterance provided by a user, and can cause the third-party agent(s) to determine third-party interpretation(s) of the spoken utterance provided by the user. In some implementations, the automated assistant can select a given interpretation, from the first-party interpretation(s) and the third-party interpretation(s), of the spoken utterance, and can cause a given third-party agent to satisfy the spoken utterance based on the given interpretation.

Abstract: Implementations described herein utilize an independent server for facilitating secure exchange of data between multiple disparate parties. The independent server receives client data, via an automated assistant application executing at least in part at a client device, that is to be transmitted to a given third-party application. The independent server processes the client data, using a first encoder-decoder model, to generate opaque client data, and transmits the opaque client data to the given third-party application and without transmitting any of the client data. Further, the independent server receives response data, via the given third-party application, that is generated based on the opaque client data and that is to be transmitted back to the client device. The independent server processes the response data, using a second encoder-decoder model, to generate opaque response data, and transmits the opaque response data to the client device and without transmitting any of the response data.

Abstract: Implementations described herein are directed to enabling collaborative ranking of interpretations of spoken utterances based on data that is available to an automated assistant and third-party agent(s), respectively. The automated assistant can determine first-party interpretation(s) of a spoken utterance provided by a user, and can cause the third-party agent(s) to determine third-party interpretation(s) of the spoken utterance provided by the user. In some implementations, the automated assistant can select a given interpretation, from the first-party interpretation(s) and the third-party interpretation(s), of the spoken utterance, and can cause a given third-party agent to satisfy the spoken utterance based on the given interpretation.

Abstract: The present invention relates to systems and methods for automated channel addition. A content management system receives a request for channel assessment from the channel. The request may include a JSON file. The system then scores the channel by at the number of users, topics of conversations, sentiment of the topics, and level of engagement for the users. The channel is then cataloged for access by a client (advertiser). Next the system receives approval of the channel from the client. Next the system selects content for the channel. Content selection may be in response to a channel request for particular content, in response to a client request for the particular channel, or through sentiment based matching. After content selection it may be published to the channel. This publishing uses the JSON file to modify the content to be compatible with the channel application programming interface.