Autonomous vehicles: AI must accelerate - Electronic Products & Technology

Large numbers of sensors, massive amounts of data, ever-increasing computing power, real-time operation and security concerns required for autonomous vehicles are driving the core of computation from the cloud to the edge of the network. Autonomous vehicles are constantly sensing and sending data on road conditions, location and the surrounding vehicles. Self-driving cars generate roughly 1 GB of data per second – it is impractical to send even a fraction of the terabytes of data for analysis to a centralized server because of the processing bandwidth and latency. Due to the high volume of data transfer, latency issues and security, the current cloud computing service architecture hinders the vision of providing real-time artificial intelligence processing for driverless cars. Thus, deep learning, as the main representative of artificial intelligence, can be integrated into edge computing frameworks.