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If anyone doubted the extent to which Brainchip is responsible for the power efficiency of the EQXX the following taken from this new website should remove any doubt:
BrainChip Automotive brings Essential AI to the next generation of smarter cars.
In-cabin experience is improved with on-chip learning for keyword spotting, “hey car,” face recognition, driver authentication, gesture recognition, and the unique ability to combine sensory modalities, creating a roadmap for the in-cabin experience of the future. Advanced Driver Assistance Systems (ADAS) focus on the automobile industry, as embedded sensors provide surrounding data that radically improve safety and pave the way for fully autonomous vehicles.
However, the amount of sensor data processed “in-car” can require significant compute and associated valuable power. BrainChip’s solution has hardware at the sensor to analyze the data in real-time and forward “inference data” to the car’s central processor. This architecture improves performance and radically reduces system-level power consumption.
System health monitoring is another critical use case that leverages BrainChip’s Akida processor IP. Any piece of machinery produces vibrations or sound representing a healthy state, which changes over time as the equipment ages or is damaged. While the human ear may not be able to distinguish minor changes in sound that indicate an impending problem, the Akida Edge AI processor can provide early diagnostics through real-time analysis of sensor data on issues such as reducing human-related errors and labor costs, preventing machinery deterioration in real-time. This offers invaluable progress towards complete safety and reducing maintenance costs.
BrainChip Automotive brings Essential AI to the next generation of smarter cars.
In-cabin experience is improved with on-chip learning for keyword spotting, “hey car,” face recognition, driver authentication, gesture recognition, and the unique ability to combine sensory modalities, creating a roadmap for the in-cabin experience of the future. Advanced Driver Assistance Systems (ADAS) focus on the automobile industry, as embedded sensors provide surrounding data that radically improve safety and pave the way for fully autonomous vehicles.
However, the amount of sensor data processed “in-car” can require significant compute and associated valuable power. BrainChip’s solution has hardware at the sensor to analyze the data in real-time and forward “inference data” to the car’s central processor. This architecture improves performance and radically reduces system-level power consumption.
System health monitoring is another critical use case that leverages BrainChip’s Akida processor IP. Any piece of machinery produces vibrations or sound representing a healthy state, which changes over time as the equipment ages or is damaged. While the human ear may not be able to distinguish minor changes in sound that indicate an impending problem, the Akida Edge AI processor can provide early diagnostics through real-time analysis of sensor data on issues such as reducing human-related errors and labor costs, preventing machinery deterioration in real-time. This offers invaluable progress towards complete safety and reducing maintenance costs.
