PyTorch Levels Up Its Serving Game with TorchServe

With TorchServe, Facebook and AWS continue to narrow the gap between machine learning research and production. PyTorch's 1.5 release brings the initial version of TorchServe as well as experimental support of TorchElastic with Kubernetes for large-scale model training. With TorchServe, Facebook and AWS continue to narrow the gap between Machine Learning research and production. In recent years, PyTorch has largely overtaken Tensorflow as the machine learning model training framework that is preferred for research-leaning data scientists. There are a few reasons for this, but mainly that Pytorch is built for Python as its first-class language of use, whereas Tensorflow's architecture stays much closer to its C/C core.