Abstract: In one embodiment, a device represents spatial characteristics over time of an object in video data as one or more timeseries. The device detects an event based on a rate of change of behavioral regimes associated with different portions of the one or more timeseries. The device selects contextual data for the event that comprises spatial timeseries information for different types of objects or different activities. The device provides an alert for the event to a user interface regarding the event that includes the contextual data.

Abstract: In one embodiment, a student agent identifies a topic of interest. The student agent issues a set of one or more questions to a teacher agent regarding the topic of interest. The student agent receives, from the teacher agent, answer data in response to the set of one or more questions. The student agent uses the answer data to generate a neuro-symbolic metamodel that comprises a semantic reasoner and a sub-symbolic layer.

Abstract: In one embodiment, a device represents spatial characteristics over time of an object in video data as one or more timeseries. The device detects an event based on a rate of change of behavioral regimes associated with different portions of the one or more timeseries. The device selects contextual data for the event that comprises spatial timeseries information for different types of objects or different activities. The device provides an alert for the event to a user interface regarding the event that includes the contextual data.

Abstract: In one embodiment, a device obtains data regarding generation of an artificial intelligence model. The device analyzes the data using a neuro-symbolic metamodel, to match the data to one or more concepts of a knowledge graph of the neuro-symbolic metamodel. The device makes one or more inferences about the artificial intelligence model, by applying a semantic reasoning engine to the one or more concepts of the knowledge graph. The device causes, based on the one or more inferences, generation of a replacement artificial intelligence model for the artificial intelligence model.

Abstract: In one embodiment, a device converts video data into a set of tracklets, each tracklet representing a different object depicted in the video data. The device identifies a particular object depicted in the video data as being an attractor or repulsor with respect to one or more other objects depicted in the video data, based on an analysis of their respective tracklets. The device makes, using a semantic reasoning engine, an inference about the video data, based in part on the particular object being identified as an attractor or repulsor. The device provides data based on the inference for display.

Abstract: In one embodiment, a device provides information for display regarding an artificial intelligence metamodel that includes at least a symbolic layer and a sub-symbolic layer. The device receives an indication of a target node in a network to which the artificial intelligence metamodel is to be deployed. The device generates a modified version of the artificial intelligence metamodel based on resources available at the target node. The device deploys the modified version of the artificial intelligence metamodel for execution by the target node.

Abstract: In one embodiment, a device identifies, using a semantic reasoning engine, activities in a location, based on sensor data obtained from a plurality of sensors deployed to the location. The device associates the activities with areas of the location in which they occurred. The device makes, using the semantic reasoning engine, an inference about a particular activity, based in part on where that activity occurred. The device raises, based on the inference, an alert regarding the particular activity.

Abstract: In one embodiment, a device receives sensor data from a plurality of sensors. The device detects, using a semantic reasoning engine, a disruption to a first shipment based on the sensor data. The device infers, using the semantic reasoning engine, that one or more other shipments are related to the first shipment. The device initiates a mitigation action for the disruption that is performed with respect to the one or more other shipments.

Abstract: In one embodiment, a device makes an inference about an event indicated by sensor data from a plurality of sources by applying a semantic reasoning engine to the sensor data. The device receives a selected semantic compression level from a user interface. The device selects a subset of the sensor data based on the inference and on the selected semantic compression level. The device exports the subset of the sensor data and the inference made by the semantic reasoning engine about the event.