Data is received characterizing a request for agent computation of sensor data. The request includes a required confidence and required latency for completion of the agent computation. Agents to query are determined based on the required confidence. Data is transmitted to query the determined agents to provide analysis of the sensor data. Related apparatus, systems, techniques, and articles are also described.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: receiving sensor data; classifying the sensor data into one of two or more classes by at least a machine computation component including a predictive model trained on data labeled by at least an agent computation component, the agent computation component including a platform to query an agent; and providing the classification. 2. The method of claim 1, further comprising: requesting processing by the agent computation component and receiving a result and a confidence measure of the result from the agent computation component, the confidence measure of the result exceeding a predefined threshold; and providing, to the machine computation component, the sensor data as an input and the result from the agent computation component as supervisory data to train a predictive model of the machine computation component. 3. The method of claim 2, wherein the agent computation component processes the sensor data by at least: receiving data characterizing a request for agent computation of the sensor data, the request including a required confidence and required latency for completion of the agent computation; determining agents to query based on at least one of: the required confidence, a measure of agent quality, a measure of expected agent latency, and proximity to average completion time for a current task; and transmitting data to query the determined agents to provide analysis of the sensor data. 4. The method of claim 1, wherein the machine computation component includes a deep learning artificial intelligence classifier, a deep neural network, and/or a convolutional neural network. 5. The method of claim 4, wherein the machine computation component detects objects and classifies objects in the sensor data, the sensor data including an image. 6. The method of claim 1, wherein at least one of the receiving, classifying, and providing is performed by at least one data processor forming part of at least one computing system. 7. The method of claim 1, wherein the sensor data is of a security system asset that is an imaging device, a video camera, a still camera, a radar imaging device, a microphone, a chemical sensor, an acoustic sensor, a radiation sensor, a thermal sensor, a pressure sensor, a force sensor, or a proximity sensor. 8. The method of claim 1, wherein the sensor data includes an image including a single image, a series of images, or a video; and the computational task includes: detecting a pattern in the image; detecting a presence of an object within the image; detecting a presence of a person within the image; detecting intrusion of the object or person within a region of the image; detecting suspicious behavior of the person within the image; detecting an activity of the person within the image; detecting an object carried by the person, detecting a trajectory of the object or the person in the image; a status of the object or person in the image; identifying whether a person who is detected is on a watch list; determining whether a person or object has loitered for a certain amount of time; detecting interaction among person or objects; tracking a person or object; determining status of a scene or environment; determining the sentiment of one or more people; counting the number of objects or people; determining whether a person appears to be lost; determining whether an event is normal or abnormal; and/or determining whether text matches that in a database. 9. A method comprising: receiving sensor data; requesting processing by an agent computation component and receiving a result and a confidence measure of the result from the agent computation component, the confidence measure of the result exceeding a predefined threshold; and providing, to a machine computation component, the sensor data as an input and the result from the agent computation component as supervisory data to train a predictive model of the machine computation component. 10. The method of claim 9, wherein the agent computation component processes the sensor data by at least: receiving data characterizing a request for agent computation of the sensor data, the request including a required confidence and required latency for completion of the agent computation; determining agents to query based on at least one of: the required confidence, a measure of agent quality, a measure of expected agent latency, and proximity to average completion time for a current task; and transmitting data to query the determined agents to provide analysis of the sensor data. 11. The method of claim 9, wherein the machine computation component includes a deep learning artificial intelligence classifier, a deep neural network, and/or a convolutional neural network. 12. The method of claim 11, wherein the machine computation component detects objects and classifies objects in the sensor data, the sensor data including an image. 13. The method of claim 9, wherein at least one of the receiving, requesting, and providing is performed by at least one data processor forming part of at least one computing system. 14. A non-transitory computer program product which, when executed by at least one data processor forming part of at least one computer, result in operations comprising: receiving sensor data; classifying the sensor data into one of two or more classes by at least a machine computation component including a predictive model trained on data labeled by at least an agent computation component, the agent computation component including a platform to query an agent; and providing the classification. 15. The computer program product of claim 14, further comprising: requesting processing by the agent computation component and receiving a result and a confidence measure of the result from the agent computation component, the confidence measure of the result exceeding a predefined threshold; and providing, to the machine computation component, the sensor data as an input and the result from the agent computation component as supervisory data to train a predictive model of the machine computation component. 16. The computer program product of claim 14, wherein the machine computation component includes a deep learning artificial intelligence classifier, a deep neural network, and/or a convolutional neural network. 17. The computer program product of claim 16, wherein the machine computation component detects objects and classifies objects in the sensor data, the sensor data including an image. 18. A system comprising: a media processor that receives sensor data; and means for classifying the sensor data into one of two or more classes by at least a machine computation component including a predictive model trained on data labeled by at least an agent computation component, the agent computation component including a platform to query an agent. 19. The system of claim 18, further comprising: means for requesting processing by the agent computation component and receiving a result and a confidence measure of the result from the agent computation component, the confidence measure of the result exceeding a predefined threshold; and means for providing, to the machine computation component, the sensor data as an input and the result from the agent computation component as supervisory data to train a predictive model of the machine computation component. 20. The system of claim 18, wherein the machine computation component includes a deep learning artificial intelligence classifier, a deep neural network, and/or a convolutional neural network. 21. The system of claim 18, wherein the machine computation component detects objects and classifies objects in the sensor data, the sensor data including an image.