JAX in 100 Seconds

  • JAX is an accelerated linear algebra library for fast numerical computing.
  • It is nearly identical to NumPy, but enforces constraints like immutable arrays and pure functions.
  • JAX can automatically compile to low-level code that can run on accelerated hardware like GPUs and TPUs.
  • The 'A' in JAX stands for autograd, which allows automatic differentiation of Python functions.
  • The 'J' stands for just-in-time compilation, transforming functions into a primitive set of operations.
  • JAX supports high performance array computing and automatic differentiation.
  • It can be used to build deep neural networks with libraries like Flax.

via JAX in 100 Seconds

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