New Patent Reveals Tesla Aiming For Quicker Autonomous Driving Improvements

The Neural Net of electric vehicle maker Tesla continues to improve regularly, and it seems that the company would like to make sure that it evolves at a faster rate. A new Tesla patent reveals that the company would like to enable a more efficient autonomous driving systems on Tesla vehicles. It would be made possible through a new data pipeline focused on more optimized data processing.

The recently spotted Tesla patent titled “Data Pipeline and Deep Learning System for Autonomous Driving” was published just a couple of days ago. The concept is that Tesla would revolutionize and improve beyond deep learning systems used for autonomous vehicles. These systems have used captured sensor data in the past to retrieve data.

Tesla acknowledges that there is a need for new sensors, particularly when the data becomes more complex. The patent states that “a need for a customized data pipeline that can maximize the signal information from the captured sensor data and provide a higher level of signal information to the deep learning network for deep learning analysis.”

The technology described in this new patent would capture an image using any of the cameras or sensors on the electric vehicle. In this case, it would be a highly dynamic image sensor, camera, or radar, or ultrasonic sensor. Through a ‘high pass’ or ‘low pass,’ the image would be broken down, and a set of processors would decipher what the image means.

In a different process, the series of data retrieved from images would be compared to the compiled information from other Tesla vehicle owners on a global scale. The newly filed patent aims to create a safe driving experience and enhance the solid performance of the autonomous driving software of the company and do so in a more efficient process. Through this, the electric vehicle maker would be able to maintain as much resolution as feasible from the images obtained by its electric vehicles’ sensors and cameras.

Through this, Tesla Neural Network would learn more efficiently from the data packets that it is getting. It would allow the company’s Neural network to function with improved images in a more efficient manner, which paves the way to faster autonomous driving enhancements.