Tesla hat ein neues Patent beanftragt, dass die Daten aus seinen Kundenfahrzeugen nutzt, um ein neuronales Netz zum Autonomen Fahren zu trainieren.
“Deep learning systems used for applications such as autonomous driving are developed by training a machine learning model. Typically, the performance of the deep learning system is limited at least in part by the quality of the training set used to train the model. In many instances, significant resources are invested in collecting, curating, and annotating the training data. The effort required to create the training set can be significant and is often tedious. Moreover, it is often difficult to collect data for particular use cases that a machine learning model needs improvement on.” Tesla’s approach to developing a self-driving system is widely different than most other companies. Whereas most other companies utilize relatively small fleets of test vehicles to collect data and test their systems, Tesla uses its fleet of hundreds of thousands of customer cars equipped with an array of sensors to collect road and driving data as well as test its self-driving system in “shadow mode”.