Abstract: The present disclosure relates to systems, methods, and computer-readable media for managing a cooling system to based on dynamic power and temperature conditions of computing hardware (e.g., a system on a chip (SOC), respective hardware blocks on the SOC). For example, systems described herein involve tracking real-time power and temperature conditions of computing hardware and determining a dynamic cooling level to actuate in maintaining a desired temperature of the computing hardware. This is done in a way that preserves long-term durability of the cooling system while maintaining the ability of the cooling system to respond to a potential spike in power consumption by the computing hardware.

Abstract: A computing device is provided, including one or more processing devices, one or more temperature sensors, a fan, and a fan tachometer. The one or more processing devices may be configured to execute an application program. While executing the application program, the one or more processing devices may be further configured to collect performance data including temperature data received from the one or more temperature sensors and fan speed data received from the fan tachometer. The one or more processing devices may be further configured to generate a fan control signal at least in part by applying a machine learning model to the performance data. The one or more processing devices may be further configured to control the fan according to the fan control signal.

Abstract: A computing device is provided, including one or more processing devices, one or more temperature sensors, a fan, and a fan tachometer. The one or more processing devices may be configured to execute an application program. While executing the application program, the one or more processing devices may be further configured to collect performance data including temperature data received from the one or more temperature sensors and fan speed data received from the fan tachometer. The one or more processing devices may be further configured to generate a fan control signal at least in part by applying a machine learning model to the performance data. The one or more processing devices may be further configured to control the fan according to the fan control signal.

Abstract: The present disclosure relates to a computer-implemented method, devices and systems for determining a location associated with a gemstone. That method includes training a data model to detect a characteristic associated with a feature of interest pertaining to a gemstones surface. The training including the steps of providing a plurality of training images of gemstones, each training image associated with a label for a feature of interest pertaining to a given region of a gemstone type and an output indicating the specific gemstone type for the label.

Abstract: A computing device is provided, including one or more processing devices, one or more temperature sensors, a fan, and a fan tachometer. The one or more processing devices may be configured to execute an application program. While executing the application program, the one or more processing devices may be further configured to collect performance data including temperature data received from the one or more temperature sensors and fan speed data received from the fan tachometer. The one or more processing devices may be further configured to generate a fan control signal at least in part by applying a machine learning model to the performance data. The one or more processing devices may be further configured to control the fan according to the fan control signal.