Abstract: This disclosure describes techniques and architectures for evaluating conversations. In some instances, conversations with users, virtual assistants, and others may be analyzed to identify potential risks within a language model that is employed by the virtual assistants and other entities. The potential risks may be evaluated by administrators, users, systems, and others to identify potential issues with the language model that need to be addressed. This may allow the language model to be improved and enhance user experience with the virtual assistants and others that employ the language model.

Abstract: A virtual assistant may communicate with a user in a conversational manner based on context. For instances, a virtual assistant may be presented to a user to enable a conversation between the virtual assistant and the user. A response to user input that is received during the conversation may be determined based on contextual values related to the conversation or system that implements the virtual assistant.

Abstract: A fan comprising: (a) an impeller, (b) a motor connected to the impeller so that during operation the motor drives the impeller to move a fluid; (c) an instrumentation assembly that includes one or more components for controlling one or more operations of the fan; (d) an interface in communication with the instrumentation assembly; wherein the interface is configured so that one or more programs, one or more signals, or both can be input into the fan after a final assembly of the fan so that the fan can be configured to perform a desired function at the time of installation into a final product, reconfigured for a different purpose than originally programmed, or both.

Abstract: Techniques and architectures for implementing a team of virtual assistants are described herein. The team may include multiple virtual assistants that are configured with different characteristics, such as different functionality, base language models, levels of training, visual appearances, personalities, and so on. The characteristics of the virtual assistants may be configured by trainers, end-users, and/or a virtual assistant service. The virtual assistants may be presented to end-users in conversation user interfaces to perform different tasks for the users in a conversational manner. The different virtual assistants may adapt to different contexts. The virtual assistants may additionally, or alternatively, interact with each other to carry out tasks for the users, which may be illustrated in conversation user interfaces.

Abstract: Techniques for mapping actions and objects to tasks may include identifying a task to be performed by a virtual assistant for an action and/or object. The task may be identified based on a task map of the virtual assistant. In some examples, the task may be identified based on contextual information of a user, such as a conversation history, content output history, user preferences, and so on. The techniques may also include customizing a task map for a particular context, such as a particular user, industry, platform, device type, and so on. The customization may include assigning an action, object, and/or variable value to a particular task.

Abstract: A fan comprising: (a) an impeller, (b) a motor connected to the impeller so that during operation the motor drives the impeller to move a fluid; (c) an instrumentation assembly that includes one or more components for controlling one or more operations of the fan; (d) an interface in communication with the instrumentation assembly; wherein the interface is configured so that one or more programs, one or more signals, or both can be input into the fan after a final assembly of the fan so that the fan can be configured to perform a desired function at the time of installation into a final product, reconfigured for a different purpose than originally programmed, or both.

Abstract: This disclosure describes techniques and architectures for evaluating conversations. In some instances, conversations with users, virtual assistants, and others may be analyzed to identify potential risks within a language model that is employed by the virtual assistants and other entities. The potential risks may be evaluated by administrators, users, systems, and others to identify potential issues with the language model that need to be addressed. This may allow the language model to be improved and enhance user experience with the virtual assistants and others that employ the language model.

Abstract: Virtual assistants intelligently emulate a representative of a service provider by providing variable responses to user queries received via the virtual assistants. These variable responses may take the context of a user's query into account both when identifying an intent of a user's query and when identifying an appropriate response to the user's query.

Abstract: A conversation user interface enables patients to better understand their healthcare by integrating diagnosis, treatment, medication management, and payment, through a system that uses a virtual assistant to engage in conversation with the patient. The conversation user interface conveys a visual representation of a conversation between the virtual assistant and the patient. An identity of the patient, including preferences and medical records, is maintained throughout all interactions so that each aspect of this integrated system has access to the same information. The conversation user interface presents allows the patient to interact with the virtual assistant using natural language commands to receive information and complete task related to his or her healthcare.

Abstract: Virtual assistants intelligently emulate a representative of a service provider by providing variable responses to user queries received via the virtual assistants. These variable responses may take the context of a user's query into account both when identifying an intent of a user's query and when identifying an appropriate response to the user's query.

Abstract: Techniques and architectures for implementing a team of virtual assistants are described herein. The team may include multiple virtual assistants that are configured with different characteristics, such as different functionality, base language models, levels of training, visual appearances, personalities, and so on. The characteristics of the virtual assistants may be configured by trainers, end-users, and/or a virtual assistant service. The virtual assistants may be presented to end-users in conversation user interfaces to perform different tasks for the users in a conversational manner. The different virtual assistants may adapt to different contexts. The virtual assistants may additionally, or alternatively, interact with each other to carry out tasks for the users, which may be illustrated in conversation user interfaces.

Abstract: Techniques and architectures for implementing a team of virtual assistants are described herein. The team may include multiple virtual assistants that are configured with different characteristics, such as different functionality, base language models, levels of training, visual appearances, personalities, and so on. The characteristics of the virtual assistants may be configured by trainers, end-users, and/or a virtual assistant service. The virtual assistants may be presented to end-users in conversation user interfaces to perform different tasks for the users in a conversational manner. The different virtual assistants may adapt to different contexts. The virtual assistants may additionally, or alternatively, interact with each other to carry out tasks for the users, which may be illustrated in conversation user interfaces.

Abstract: A conversation user interface enables patients to better understand their healthcare by integrating diagnosis, treatment, medication management, and payment, through a system that uses a virtual assistant to engage in conversation with the patient. The conversation user interface conveys a visual representation of a conversation between the virtual assistant and the patient. An identity of the patient, including preferences and medical records, is maintained throughout all interactions so that each aspect of this integrated system has access to the same information. The conversation user interface presents allows the patient to interact with the virtual assistant using natural language commands to receive information and complete task related to his or her healthcare.

Abstract: Techniques and architectures for analyzing conversations between users and virtual assistants to identify instances where the virtual assistants have not satisfied user requests are described. The techniques and architectures may use such analysis to tag conversations regarding unsatisfied user requests, provide information to users regarding conversations with unsatisfied user requests, learn conversation or contextual data for unsatisfied user requests, and/or perform a variety to other processes to improve the virtual assistants.

Abstract: Techniques for interacting with a portion of a content item through a virtual assistant are described herein. The techniques may include identifying a portion of a content item that is relevant to user input and causing an action to be performed related to the portion of the content item. The action may include, for example, displaying the portion of the content item on a smart device in a displayable format that is adapted to a display characteristic of the smart device, performing a task for a user that satisfies the user input, and so on.

Abstract: Techniques for interacting with a portion of a content item through a virtual assistant are described herein. The techniques may include identifying a portion of a content item that is relevant to user input and causing an action to be performed related to the portion of the content item. The action may include, for example, displaying the portion of the content item on a smart device in a displayable format that is adapted to a display characteristic of the smart device, performing a task for a user that satisfies the user input, and so on.

Abstract: User intent may be derived from a previous communication. For example, a text string for user input may be obtained. The text string may include a pronoun. Information from a communication received prior to receipt of the user input may be derived. The information may identify an individual. User intent may be derived from the text string and the information. This may include determining that the pronoun refers to the individual.

Abstract: Various embodiments provide a tool, referred to herein as “Active Lab” that can be used to develop, debug, and maintain knowledge bases. These knowledge bases (KBs) can then engage various applications, technology, and communications protocols for the purpose of task automation, real time alerting, system integration, knowledge acquisition, and various forms of peer influence. In at least some embodiments, a KB is used as a virtual assistant that any real person can interact with using their own natural language. The KB can then respond and react however the user wants: answering questions, activating applications, or responding to actions on a web page.

Abstract: Virtual agents may be implemented on a wearable device. The wearable device may include an input device to receive input and a communication component to send the input to a computing device for processing and to receive a response for the input. The wearable device may also include an output device to output the response via the virtual agent as part of a conversation with a user.

Abstract: Ambiguous input of a user received during an interactive session with a virtual agent may be processed. The virtual agent may be presented via a computing device to facilitate the interactive session with the user. The user may provide the ambiguous input, which is processed to determine a response to the input. The virtual agent may provide the response to the user. The virtual agent may also carry out a goal-based dialogue where a goal to be accomplished is identified. The virtual agent may prompt the user for information related to the goal.