> I have nothing against supporting GPUs (although I think their use is overrated and most people would do fine with CPUs), but Python really needs a general purpose, high performance autodiff.

As someone who works with machine learning models day-to-day (yes, some deep NNs, but also other stuff) - GPUs really seem unbeatable to me for anything gradient-optimization-of-matrices (i.e. like 80% of what I do) related. Even inference in a relatively simple image classification net takes an order of magnitude longer on CPU than GPU on the smallest dataset I'm working with.

Was this a comment about specific models that have a reputation as being more difficult to optimize on the GPU (like tree-based models - although Microsoft is working in this space)? Or am I genuinely missing some optimization techniques that might let me make more use of our CPU compute?