Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.

Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.

Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.

Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.

Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.

Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.

Abstract: Circuits for full duplex bi-directional differential communication via a single conductor pair. A transceiver for full duplex differential communication over a single conductor pair includes a differential driver, a polarity neutral receiver, and receiver output circuitry. The differential driver is to drive the conductor pair. The polarity neutral receiver is to detect signals present on the conductor pair. The receiver output circuitry is configured to determine a logic value to be output by the transceiver as received via the conductor pair based on an output of the polarity neutral receiver and a logic value driven onto the conductor pair by the differential driver.

Abstract: Circuits for full duplex bi-directional differential communication via a single conductor pair. A transceiver for full duplex differential communication over a single conductor pair includes a differential driver, a polarity neutral receiver, and receiver output circuitry. The differential driver is to drive the conductor pair. The polarity neutral receiver is to detect signals present on the conductor pair. The receiver output circuitry is configured to determine a logic value to be output by the transceiver as received via the conductor pair based on an output of the polarity neutral receiver and a logic value driven onto the conductor pair by the differential driver.