Learn JAX in 2023: Part 2 - grad, jit, vmap, and pmap

In this tutorial, you will learn the power tools of JAX, grad, jit, vmap, and pmap. To learn how to use JAX's power tools, just keep reading. Welcome to our comprehensive guide on advanced JAX techniques! In the previous tutorial, we were introduced to JAX, and its predecessors autograd and xla. We also briefly looked into numerical computing with JAX. In this post, we'll be diving into some of the most powerful and useful features of the JAX library, including grad, jit, vmap, and pmap. These functions allow you to easily and efficiently compute gradients of functions, optimize your code for faster execution, and apply functions to arrays of data in parallel. By the end of this post, you'll have a solid understanding of how to use these tools to improve the performance and functionality of your numerical computation and machine learning tasks. We'll also cover the topic of randomness in JAX, including how to generate and control random numbers for use in your computations.