Abstract: A computer architecture may comprise a processor, a memory, and a differential memory subsystem (DMS). A learning engine is stored on the memory and configured to present data to an expert user, to receive user sensory input measuring reactions related to the presented data, and to create an attention map based thereon. The attention map is indicative of portions of the presented data on which the expert user focused. The learning engine is configured to annotate the attention map with the natural language input labels and to train a neural network based on the user sensory input. The learning engine is configured to create a model based on the trained neural network, to provide an application program for an output target; and to instruct the output target via the application program to detect and remedy anomalous activity. The DMS is physically separate and configured for experimental data processing functions.

Abstract: A computer architecture may comprise a processor, a memory, and a differential memory subsystem (DMS). A learning engine is stored on the memory and configured to present data to an expert user, to receive user sensory input measuring reactions related to the presented data, and to create an attention map based thereon. The attention map is indicative of portions of the presented data on which the expert user focused. The learning engine is configured to annotate the attention map with the natural language input labels and to train a neural network based on the user sensory input. The learning engine is configured to create a model based on the trained neural network, to provide an application program for an output target; and to instruct the output target via the application program to detect and remedy anomalous activity. The DMS is physically separate and configured for experimental data processing functions.

Abstract: A user media device may include a microphone array and a communication interface. The microphone array may include an omnidirectional microphone and a directional microphone. The microphone array may be selectively switchable. The communication interface may communicatively couple the user media device with a computer and may transmit audio captured by the microphone array to the computer for transfer to a remote service. The remote service may generate text of the processed audio via natural language processing. The remote service may further perform semantic reasoning of the processed audio via a semantic reasoning engine. The remote service may also generate content based at least in part on the semantic reasoning performed on the processed audio. The curated content may include a report having results of the semantic reasoning organized to demonstrate the results in a meaningful way with respect to the processed audio.

Abstract: A user media device may include a microphone array and a communication interface. The microphone array may include an omnidirectional microphone and a directional microphone. The microphone array may be selectively switchable. The communication interface may communicatively couple the user media device with a computer and may transmit audio captured by the microphone array to the computer for transfer to a remote service. The remote service may generate text of the processed audio via natural language processing. The remote service may further perform semantic reasoning of the processed audio via a semantic reasoning engine. The remote service may also generate content based at least in part on the semantic reasoning performed on the processed audio. The curated content may include a report having results of the semantic reasoning organized to demonstrate the results in a meaningful way with respect to the processed audio.

Abstract: A user media device may include a microphone array and a communication interface. The microphone array may include an omnidirectional microphone and a directional microphone. The microphone array may be selectively switchable. The communication interface may communicatively couple the user media device with a computer and may transmit audio captured by the microphone array to the computer for transfer to a remote service. The remote service may generate text of the processed audio via natural language processing. The remote service may further perform semantic reasoning of the processed audio via a semantic reasoning engine. The remote service may also generate content based at least in part on the semantic reasoning performed on the processed audio. The curated content may include a report having results of the semantic reasoning organized to demonstrate the results in a meaningful way with respect to the processed audio.

Abstract: A kettlebell includes sensors to collect movement data during use, a controller to track movement data, a kinetic charging circuit to charge a kettlebell battery, a network interface over which to transmit movement data to a networked device, and a user interface to display a representation of electricity generated by the kettlebell movement. The sensors include an accelerometer or a gyroscope. The controller may execute instructions to store the movement data, sample or aggregate the data, transmit the sampled or aggregated data to the networked device, determine the amount of electricity generated by kettlebell movement, or calculate a measure of exercise intensity based on the generated electricity. The networked device may generate and provide data representing the effectiveness of a user's fitness program to a cloud-based server or exchange the data with another networked device. The server may provide the data to a fitness professional or another user.