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JAX is a Python library similar to NumPy for scientific computing and linear algebra, but designed to run on accelerators like Cuda-based GPUs and Google's TPUs. 

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Google JAX on GitHub https://github.com/google/jax
Tensorflow in 100 Seconds https://youtu.be/i8NETqtGHms
Cuda in 100 Seconds https://youtu.be/pPStdjuYzSI
GPU vs TPU https://youtu.be/r5NQecwZs1A


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- JAX basics tutorial
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- Tensorflow vs JAX
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Fireship is a YouTube channel created by Jeff Delaney that offers quick tutorials and explanations on web development, programming, and tech trends. Known for the “100 Seconds of Code” and “The Code Report” series, the channel breaks down complex topics in a short, engaging format, covering everything from JavaScript frameworks to emerging technologies.

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Jax is an accelerated linear algebra library that allows for high-performance array computing and automatic differentiation. It enforces constraints like immutable arrays and pure functions. Jax can run on accelerated hardware like GPUs and TPUs.

JAX in 100 Seconds