Not a chance. One thing I found interesting in this article was the graph of successful object identification in images. The author made much of progressing fro

Not a chance. One thing I found interesting in this article was the graph of successful object identification in images. The author made much of progressing from 50% to 88% in the last ten years (I believe this uncited data comes from [0]), but the great majority of that progress happened in the first five years, and the predictable slowdown of improvement is clearly evidenced by the graph. We should also be very clear that 88% success rate given for object detection and identification is against a relatively fixed set of static images[1]. And as far as I can tell from the paper[2], there's no indication of how long it takes to come to a conclusion on any single image, and no description of how much hardware was used to reach this rate of success, which to be honest, I'm surprised is so low. Given all of that, it does not seem reasonable to assume that this 88% success rate has anything to do with how well object detection works in real-time using on-board computing power while the car is in motion. So, don't start planning to throw out your driver's license anytime soon. [0] https://paperswithcode.com/sota/image-classification-on-imagenet https://paperswithcode.com/sota/image-classification-on-imag... [1] https://en.wikipedia.org/wiki/ImageNet https://en.wikipedia.org/wiki/ImageNet [2] https://paperswithcode.com/paper/self-training-with-noisy-student-improves https://paperswithcode.com/paper/self-training-with-noisy-st...