Abstract: A method for training a learning system to identify components of time-based data streams includes processing, by a machine vision component in communication with a learning system, a video file to detect at least one object in the video file. The method includes generating by the machine vision component an output including data relating to the at least one object and the video file. The method includes analyzing, by a learning system, the output. The method includes identifying, by the learning system, an unidentified object in the processed video file.

Abstract: A digital computational learning system and corresponding method plan a series of actions to accomplish tasks. The system learns, automatically, a plurality of actor perceiver predictors (APP) nodes. Each APP node is associated with a context, action, and result. The result is expected to be achieved in response to the action being taken as a function of the context having been satisfied. Each APP node is associated with an action-controller that includes an instance of a planner that includes allied planners. The action-controller is associated with a goal state and employs the allied planners to determine a sequence of actions for reaching the goal state. The allied planners enable the system to plan a series of actions to accomplish complex tasks in a manner that is more robust and resilient relative to current state of the art artificial intelligence based learning systems and methods.

Abstract: A natural language understanding (NLU) system utilizes a knowledge network having interconnected actor perceiver predictor (APP) nodes associated with context, action, and result. For a received utterance, an utterance type is determined, and an input message is generated based on the utterance type. The input message includes word-concept groupings, which include words of the received utterance and concept tags associated with the words. An action type is determined based on the utterance type. The knowledge network is searched to locate a subset of the APP nodes that exceed a threshold connection weight and thereby discriminate the word-concept groupings from other word-concept groupings represented by nodes of the network. Metadata for the word-concept groupings is retrieved from the subset of the APP nodes, and a response to the received utterance is generated by incorporating the metadata into a response template.

Abstract: A computer vision learning system and corresponding computer-implemented method extract meaning from image content. The computer vision learning system comprises at least one image sensor that transforms light sensed from an environment of the computer vision learning system into image data representing a scene of the environment. The computer vision learning system further comprises a digital computational learning system that includes a network of actor perceiver predictor (APP) nodes and a library of visual methods available to the APP nodes for applying to the image data. The digital computational learning system employs the network in combination with the library to determine a response to a query and outputs the response determined. The query is associated with the scene. The computer vision learning system is capable of answering queries not just about what is happening in the scene, but what would happen based on the scene in view of hypothetical conditions and/or actions.

Abstract: Systems and methods of the disclosed subject matter provide a first light source, a second light source, and a controller communicatively coupled to the first light source and the second light source, the controller to control a first operation of the first light source according to an input received by the controller for at first period of time, and to control a second operation of the second light source when the input received by the controller is for a second period of time that is greater than the first period of time.

Abstract: Systems and methods of the disclosed subject matter provide a first light source, a second light source, and a controller communicatively coupled to the first light source and the second light source, the controller to control a first operation of the first light source according to an input received by the controller for at first period of time, and to control a second operation of the second light source when the input received by the controller is for a second period of time that is greater than the first period of time.

Abstract: Systems and methods of the disclosed subject matter provide a first light source, a second light source, and a controller communicatively coupled to the first light source and the second light source, the controller to control a first operation of the first light source according to an input received by the controller for at first period of time, and to control a second operation of the second light source when the input received by the controller is for a second period of time that is greater than the first period of time.

Abstract: Systems and methods of the disclosed subject matter provide a first light source, a second light source, and a controller communicatively coupled to the first light source and the second light source, the controller to control a first operation of the first light source according to an input received by the controller for at first period of time, and to control a second operation of the second light source when the input received by the controller is for a second period of time that is greater than the first period of time.