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Comments (8)

• heisenzombie
  Jax is super fun to use outside of ml!Recently I had fun reimplementing an old (but still usable!) code for accelerator optics. It involved transfer matrices for a 6D phase space to second order. Most of the FORTRAN77 source code was just pages and pages of hand-differentiated 6x6x6 matrices (with quite non-trivial elements) and the plumbing to painstakingly propagate those jacobians around for fitting... all replaced with a single, magic, call to jax.grad(). Felt like cheating!I'm also super interested in its application to modelling, e.g. projects like https://github.com/deepmodeling/jax-fem -- particularly for chaining different sorts of simulations and analysis together and getting gradients through the lot. Also quite magic!
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  corndoge
  Moving my thumb across the image causes the ball and cube graphic to disappear to black and then scrolls the page. Firefox on iOS
• VHRanger
  Pytorch is such a maddening mess of half implemented research features in a state of Heisen-deprecation, Jax becomes more appealing to me by the day.
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  vatsachak
  Yeah GPU compilers will be used for way more things than AI because parallel = good
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  dvt
  > the thing JAX was truly meant for: a graphics rendererI mean, just like ray-tracing, SDF (ray-marching) is neat, but basically everything useful is expensive or hard to do (collisions, meshes, texturing etc.). I mean mathy stuff is easier (rotations, unions/intersections, function composition, etc.) but 3D is usually used in either modeling software or video games, which care more about the former than they do the latter.