Abstract: A method comprises determining whether a decision can be determined for the request based on a current information available; when the decision can be determined, utilizing a first model to determine a set of questions corresponding to the request, the first model previously trained using training data comprising a set of questions associated with a set of requests; utilizing a second model to determine one or more predicted answers for the set of questions, the second model ingesting the set of questions determined by the first model and at least one attribute associated with the request to generate the one or more predicted answers; and utilizing a third model to determine the decision for the request.

Abstract: The present disclosure is directed toward systems and methods that efficiently and effectively generate and utilize collections of content items. For example, systems and methods described herein generate a collection content item including one or more content item references. In one or more embodiments, the collection content item can include content item references for content items located internally or externally, with granular levels of permissions settings and version controls. Additionally, in response to a detected selection of a content item reference, systems and methods described herein generate a rendering of the associated content item that can be viewed regardless of any third party software installed on the viewing client computing device.

Abstract: The present disclosure is directed toward systems and methods that efficiently and effectively generate and utilize collections of content items. For example, systems and methods described herein generate a collection content item including one or more content item references. In one or more embodiments, the collection content item can include content item references for content items located internally or externally, with granular levels of permissions settings and version controls. Additionally, in response to a detected selection of a content item reference, systems and methods described herein generate a rendering of the associated content item that can be viewed regardless of any third party software installed on the viewing client computing device.

Abstract: Sensor information is received. Based at least in part on at least one state detected using the sensor information, an expected value for automatically performing an action associated with a device controlled by a device controller system is evaluated as compared to an expected value for potentially performing, subject to a user interactive qualification, the action associated with the device controlled by the device controller. It is determined that the expected value of automatically performing the action is insufficient to trigger automatically performing the action without being subject to the user interactive qualification. A confirmatory indication is identified. Based at least in part on the confirmatory indication, an instruction is sent to the device to perform the action.

Abstract: The present disclosure is directed toward systems and methods that efficiently and effectively generate and utilize collections of content items. For example, systems and methods described herein generate a collection content item including one or more content item references. In one or more embodiments, the collection content item can include content item references for content items located internally or externally, with granular levels of permissions settings and version controls. Additionally, in response to a detected selection of a content item reference, systems and methods described herein generate a rendering of the associated content item that can be viewed regardless of any third party software installed on the viewing client computing device.

Abstract: Sensor information is received. Based at least in part on at least one state detected using the sensor information, an expected value for automatically performing an action associated with a device controlled by a device controller system is evaluated as compared to an expected value for potentially performing, subject to a user interactive qualification, the action associated with the device controlled by the device controller. It is determined that the expected value of automatically performing the action is insufficient to trigger automatically performing the action without being subject to the user interactive qualification. A confirmatory indication is identified. Based at least in part on the confirmatory indication, an instruction is sent to the device to perform the action.

Abstract: Sensor information is received. Based at least in part on at least one state detected using the sensor information, an expected value for automatically performing an action associated with a device controlled by a device controller system is evaluated as compared to an expected value for potentially performing, subject to a user interactive qualification, the action associated with the device controlled by the device controller. It is determined that the expected value of automatically performing the action is insufficient to trigger automatically performing the action without being subject to the user interactive qualification. A confirmatory indication is identified. Based at least in part on the confirmatory indication, an instruction is sent to the device to perform the action.

Abstract: A network connected controllable device is automatically controlled. A plurality of inputs that indicate states of a network connected device environment associated with a property of the network connected controllable device to be automatically controlled is received. A plurality of output candidates is evaluated according to an optimization function. The optimization function depends on the plurality of inputs and one or more parameters and the output candidates are associated with candidate settings of the property of the network connected controllable device to be automatically controlled. An output that optimizes the optimization function is selected among the plurality of output candidates.

Abstract: Network connected devices are controlled. A command is received. A graph model is applied to identify a subset of nodes related to the command. The graph model includes a plurality of nodes that each correspond to a device and the graph model includes a plurality of edges that specify relationships between the plurality of nodes. The subset of nodes is activated in response to the command.

Abstract: Network connected devices are controlled. A command is received. A graph model is applied to identify a subset of nodes related to the command. The graph model includes a plurality of nodes that each correspond to a device and the graph model includes a plurality of edges that specify relationships between the plurality of nodes. The subset of nodes is activated in response to the command.

Abstract: Network connected devices are controlled. A command is received. A graph model is applied to identify a subset of nodes related to the command. The graph model includes a plurality of nodes that each correspond to a device and the graph model includes a plurality of edges that specify relationships between the plurality of nodes. The subset of nodes is activated in response to the command.

Abstract: Network connected devices are controlled. A command is received. A graph model is applied to identify a subset of nodes related to the command. The graph model includes a plurality of nodes that each correspond to a device and the graph model includes a plurality of edges that specify relationships between the plurality of nodes. The subset of nodes is activated in response to the command.