In the field of autonomous vehicles (AV), engineers, data scientists and enterprise leaders have reached a consensus that the truly autonomous vehicle is not only the primary goal, but also the ultimate goal. This is a concept that inspires enthusiasm, but it is also easy for people to ignore the fact that AV large-scale deployment is not only AI training, but also faces more difficult challenges.
In the development of autonomous vehicles, there are data challenges at every step, such as the training of machine learning models or the fast reading/writing of data that can provide sufficient vehicle response. Engineers must balance the benefits of existing auxiliary AV technologies with the future data challenges of AV.
