As a data nerd not doing deep learning but who follows the space, I'd say the article jives with what I've seen and heard: pytorch is cool, but predominantly fo

As a data nerd not doing deep learning but who follows the space, I'd say the article jives with what I've seen and heard: pytorch is cool, but predominantly for research and prototyping. Both academic and non-academic colleagues use it to test ideas a bit more quickly before taking the time to write it in tensorflow for larger-scale training. I suspect as the distributed stuff new to 0.2 catches on, the more academic ones might be able to stick with pytorch for the full/distributed training runs; curious to see.