Roboflow: Popular autonomous vehicle data set contains critical flaws
A machine learning model’s performance is only as good as the quality of the data set on which it’s trained, and in the domain of self-driving vehicles, it’s critical this performance isn’t adversely impacted by errors. A troubling report from computer vision startup Roboflow alleges that exactly this scenario occurred — according to founder Brad Dwyer, crucial bits of data were omitted from a corpus used to train self-driving car models.