I'm pretty passionate about extremely fast deep learning tools. I like the idea, but as it goes with developers who've been burned before, I'm pretty skeptical

I'm pretty passionate about extremely fast deep learning tools. I like the idea, but as it goes with developers who've been burned before, I'm pretty skeptical and will probably wait and see if this ends up surviving the initial phase of testing and trying things out. I know the xkcd standards comic isn't blindly applicable to everything but still, it's not a bad prior. Peeps who know me know that I really have skin in the game too when it comes to neural network training speed and simplicity, it's something I'm quite passionate about. So something like this, if it actually works like it says it does on the tin and is usable, would be something that would be extremely useful. There's one or two kernels I'd really like to write to bump down speed records even further, and doing so directly in the language feels pretty promising to me. I really like the idea of that. And the promise of mmap-like operations too. We have pointers already in torch, they're just ad-hoc as index values, and still somehow unprotected because you have to reset your entire runtime when CUDA borks out on an out of bounds error (that only triggers the next time you try to access data.... :'( ). It would be nice if this was the real deal. I think time will tell. I hope it is.