This isn't surprising to me at all, since these systems are only "developed independently" in a very narrow sense. Each company may have it's own implementation (Tensorflow vs. Torch, etc) but they are implementations of nearly identical underlying models, namely deep convolutional neural networks. We shouldn't be surprised that they all agree since they are all the same under the hood, probably even down to the level of choice of hyperparameters (stride length, filter size, etc) since there is plenty of research on what kind of deep net works best on particular applications.