Abstract: Various embodiments are described for searching and retrieving documents based on a natural language input. A computer-implemented natural language processor electronically receives a natural language input phrase from an interface device. The natural language processor attributes a concept to the phrase with the natural language processor. The natural language processor searches a database for a set of documents to identify one or more documents associated with the attributed concept to be included in a response to the natural language input phrase. The natural language processor maintains the concepts during an interactive session with the natural language processor. The natural language processor resolves ambiguous input patterns in the natural language input phrase with the natural language processor. The natural language processor includes a processor, a memory and/or storage component, and an input/output device.

Abstract: A powered air purifying respirator and method of operating the same. The powered air purifying respirator comprises a fluid moving device. The fluid moving device comprises an outlet, an airflow sensor retaining member located proximate to the outlet, and an airflow sensor engaged with the airflow sensor retaining member.

Abstract: Various embodiments are described for searching and retrieving documents based on a natural language input. A computer-implemented natural language processor electronically receives a natural language input phrase from an interface device. The natural language processor attributes a concept to the phrase with the natural language processor. The natural language processor searches a database for a set of documents to identify one or more documents associated with the attributed concept to be included in a response to the natural language input phrase. The natural language processor maintains the concepts during an interactive session with the natural language processor. The natural language processor resolves ambiguous input patterns in the natural language input phrase with the natural language processor. The natural language processor includes a processor, a memory and/or storage component, and an input/output device.

Abstract: Various embodiments are described for searching and retrieving documents based on a natural language input. A computer-implemented natural language processor electronically receives a natural language input phrase from an interface device. The natural language processor attributes a concept to the phrase with the natural language processor. The natural language processor searches a database for a set of documents to identify one or more documents associated with the attributed concept to be included in a response to the natural language input phrase. The natural language processor maintains the concepts during an interactive session with the natural language processor. The natural language processor resolves ambiguous input patterns in the natural language input phrase with the natural language processor. The natural language processor includes a processor, a memory and/or storage component, and an input/output device.

Abstract: Various embodiments are described for searching and retrieving documents based on a natural language input. A computer-implemented natural language processor electronically receives a natural language input phrase from an interface device. The natural language processor attributes a concept to the phrase with the natural language processor. The natural language processor searches a database for a set of documents to identify one or more documents associated with the attributed concept to be included in a response to the natural language input phrase. The natural language processor maintains the concepts during an interactive session with the natural language processor. The natural language processor resolves ambiguous input patterns in the natural language input phrase with the natural language processor. The natural language processor includes a processor, a memory and/or storage component, and an input/output device.

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: 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 natural language that simulates a human. The virtual assistant may be associated with a human-configured knowledge base that simulates human responses. In some instances, a parent response may be provided by the virtual assistant and, thereafter, a child response that is associated with the parent response may be provided.

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: 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: 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: 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: 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.

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: Various embodiments are described for searching and retrieving documents based on a natural language input. A computer-implemented natural language processor electronically receives a natural language input phrase from an interface device. The natural language processor attributes a concept to the phrase with the natural language processor. The natural language processor searches a database for a set of documents to identify one or more documents associated with the attributed concept to be included in a response to the natural language input phrase. The natural language processor maintains the concepts during an interactive session with the natural language processor. The natural language processor resolves ambiguous input patterns in the natural language input phrase with the natural language processor. The natural language processor includes a processor, a memory and/or storage component, and an input/output device.

Abstract: A virtual assistant may communicate with a user in a natural language that simulates a human. The virtual assistant may be associated with a human-configured knowledge base that simulates human responses. In some instances, a parent response may be provided by the virtual assistant and, thereafter, a child response that is associated with the parent response may be provided.