Capsule Networks Are Shaking up AI – Here's How to Use Them

You should be able to see that with this definition our neural net shouldn't be as easily fooled by our misshapen Kardashian. This new architecture also achieves significantly better accuracy on the following data set. This data set was carefully designed to be a pure shape recognition task that shows the ability to recognize the objects even from different points of view. It beat out the state-of-the-art CNN, reducing the number of errors by 45%. Further more, in their most recent paper, they found that Capsules show far more resistance to white box adversarial attack than a baseline convolutional neural network. I have pieced together a repo that is an implementation of Hinton's paper (many thanks to naturomics). In order to use the Capsule Network model you first need to train it. The following guide will get you a model trained on the MNIST data set. For those of you who don't know, MNIST is a data set of handwritten digits and is a good baseline for testing out machine learning algorithms.