15min of looking through the code and my best guess right now is that it's a reimplementation of higher-level primitives, such as optimizers and layers, found i

15min of looking through the code and my best guess right now is that it's a reimplementation of higher-level primitives, such as optimizers and layers, found in Tensorflow/Pytorch/etc, but based on a variable backend (you can pick jax or TF), together with a collection of models and training loops. I think the idea is that most of the code is simpler and more modular than what you would find in TF, which makes the models easier to read. However, I don't yet understand what the use case is, or how it helps you to "learn" anything.