JAX

High-performance numerical computing and machine learning

JAX is a library for high-performance numerical computing that combines NumPy-like APIs with automatic differentiation and hardware acceleration. It uses XLA to compile and run programs on GPUs and TPUs. JAX supports vectorization, just-in-time compilation, and differentiable programming, making it especially powerful for research in deep learning, optimization, and scientific simulation where performance and flexibility are critical.