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With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and...

...Please uninstall older versions of this software before installing a new version. Your configuration won't be deleted if you have already a version greater than 1.3.1 installed on your machine. Minimum System Requirements: - Operating System: Windows Vista, Windows 7/8/10 - CPU: Intel Pentium 4, AMD Athlon 64 or newer.. - RAM: 500 MB - Video-Memory: 256 MB - Free Disk Space: 5 MB - .NET-Framework (Version >= 2.0) Recommended Requirements: - Operating System: Windows 7 or 10 - CPU: Multicore-Processor e.g. Intel Core 2 Duo or AMD Athlon II (>=2,0Ghz) - RAM: >1.500 MB - Video-Memory: 256 MB - Free Disk Space: 100 MB - .NET-Framework (Version >= 2.0 until 1.4.7 / 4.0 for >1.5.0) Note to users of versions lesser than 1.5.7: You’ll need administrator privileges to install the software. -- Developed in Germany by Nils Schmidt - nilsschmidt1337