Abstract: Techniques are disclosed for using a computation engine executing a machine learning system to generate, according to constraints, renderings of a building or building information modeling (BIM) data for the building, wherein the constraints include at least one of an architectural style or a building constraint. In one example, an input device is configured to receive an input indicating one or more surfaces for the building and one or more constraints. A machine learning system executed by a computation engine is configured to apply a model, trained using images of buildings labeled with corresponding constraints for the buildings, to the one or more surfaces for the building to generate at least one of a rendering of the one or more surfaces for the building according to the constraints or BIM data for the building according to the constraints. Further, the machine learning system is configured to output the rendering or the BIM data.

Abstract: Techniques are disclosed for a self-reflection layer of an autonomous system that improves trust and collaboration with a user by identifying actions of the autonomous system that may be unexpected to the user. In one example, an autonomous system determines actions for one or more tasks. A self-reflection unit generates a model of a behavior of the autonomous system. The self-reflection identifies, based on the model, one or more actions of the actions for the tasks that may be unexpected to the user. The self-reflection unit determines, based on the model, a context and a rationale for the actions. An explanation unit outputs, for display, an explanation for the actions comprising the context and the rationale for the actions to improve trust and collaboration with the user of the autonomous system.

Abstract: Techniques are disclosed for using a computation engine executing a machine learning system to generate, according to constraints, renderings of a building or building information modeling (BIM) data for the building, wherein the constraints include at least one of an architectural style or a building constraint. In one example, an input device is configured to receive an input indicating one or more surfaces for the building and one or more constraints. A machine learning system executed by a computation engine is configured to apply a model, trained using images of buildings labeled with corresponding constraints for the buildings, to the one or more surfaces for the building to generate at least one of a rendering of the one or more surfaces for the building according to the constraints or BIM data for the building according to the constraints. Further, the machine learning system is configured to output the rendering or the BIM data.

Abstract: The present invention relates to a method and apparatus for assisting with automated task management. In one embodiment, an apparatus for assisting a user in the execution of a task, where the task includes one or more workflows required to accomplish a goal defined by the user, includes a task learner for creating new workflows from user demonstrations, a workflow tracker for identifying and tracking the progress of a current workflow executing on a machine used by the user, a task assistance processor coupled to the workflow tracker, for generating a suggestion based on the progress of the current workflow, and a task executor coupled to the task assistance processor, for manipulating an application on the machine used by the user to carry out the suggestion.

Abstract: A device, method and system for monitoring, predicting, and accelerating interactions with a computing device includes determining a current interaction context at a computing device based on interactions occurring at the computing device, predicting a number of potential subsequent interactions, speculatively executing at least some of the potential subsequent interactions, and presenting interactive representations of the speculatively-executed interactions at the computing device.

Abstract: The present invention relates to a method and apparatus for assisting with automated task management. In one embodiment, an apparatus for assisting a user in the execution of a task, where the task includes one or more workflows required to accomplish a goal defined by the user, includes a task learner for creating new workflows from user demonstrations, a workflow tracker for identifying and tracking the progress of a current workflow executing on a machine used by the user, a task assistance processor coupled to the workflow tracker, for generating a suggestion based on the progress of the current workflow, and a task executor coupled to the task assistance processor, for manipulating an application on the machine used by the user to carry out the suggestion.

Abstract: A LCD display comprises an LCD panel coupled to a backlight system. The backlight system comprises a direct view backlight comprising a first plurality of LEDs configured to emit white illumination that, at least in part, provides the required luminosity for the LCD panel. The backlight system further comprises an edge view backlight comprising a second plurality of LEDs configured to emit colored illumination that, at least in part, provides the required chromaticity for the LCD panel.