Abstract: An example non-transitory machine-readable medium includes instructions to capture a first image of a scene that includes light emitted by a display device, change a brightness of the display device, capture a second image of the scene while the brightness of the display device is changed, train a machine-learning model with the first image and the second image to provide a filter to reduce glare, and apply the machine-learning model to a third image captured of the scene to reduce glare in the third image, which is different from the first and second images.

Abstract: In an example implementation according to aspects of the present disclosure, a system may include a controller and non-volatile memory. The controller may query and receive a configuration from a system. The controller may query a se of system state analytics from the system. The controller may receive an indication of an anomalous state of the system. The controller may tag and create a record based on the tag and the set of analytics. The controller may input the record into an artificial neural network and receive a source of the anomalous state. The controller may then correct the source of the anomalous state.

Abstract: A microcomputer architecture and method allows for high processing speeds. A microprocessor constitutes the central processing unit. The microprocessor comprises an on-chip cache memory and is capable of reading data in a burst mode. The central processing unit and the system memory communicate by way of a high speed host bus. The system memory is comprised of multiple buses and is capable of delivering data to the microprocessor in a burst mode at high speeds. A memory controller addresses data locations within the system memory upon receipt of a first host address from the microprocessor. Accordingly, the microprocessor can access data in the system memory at an extremely fast rate when operating in a burst mode. High speed processing is accomplished without the need for an external cache.