Abstract: An electrical heating system for a vehicle. The system includes: a transparent metallic layer configured to be mounted to a transparent material, conduct electrical current, and increase in temperature to heat the transparent material in response to electrical current running across the transparent metallic layer; a power supply; a heating, ventilation, and air conditioning (HVAC) system configured to heat and cool a passenger cabin of the vehicle; and a control module. The control module is configured to: apply voltage from the power supply to the transparent metallic layer to heat the transparent material; and apply voltage from the power supply to a component of the HVAC system to heat the component of the HVAC system.

Abstract: Embodiments described herein are generally directed to improvements relating to power, latency, bandwidth and/or performance issues relating to GPU processing/caching. According to one embodiment, a system includes a producer intellectual property (IP) (e.g., a media IP), a compute core (e.g., a GPU or an AI-specific core of the GPU), a streaming buffer logically interposed between the producer IP and the compute core. The producer IP is operable to consume data from memory and output results to the streaming buffer. The compute core is operable to perform AI inference processing based on data consumed from the streaming buffer and output AI inference processing results to the memory.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of audio files. Each audio file in the set of audio files includes audio from an audio call. The program further truncates each audio file in the set of audio files to a defined call length. For each audio call in the set of audio calls, the program also receives a transcript of the audio call based on the audio file of the audio call. For each audio call in the set of audio calls, the program further uses the transcript of the audio call as input to a machine learning model for the machine learning model to predict a category from a plurality of categories that is associated with the audio call.