Training Artificial Intelligence

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.