I don't get it. How is it different from "Wide & Deep Learning for Recommender Systems (2016)" by Google?
The whole project, up til now, contains less than 2,500 lines of Python, and 271 lines of Markdown as doc, 159 lines of Shell script, and a Kaggle benchmark on Criteo CTR which dated back to 2014. The project seems to be published by FB Research, while I do not see much "research" value in this project or the companion blog.
Unlike TPU that is only made available through Google Cloud Platform, Ascend 910 will be available on market in 2019 Q2, in form of PCIe line cards and OEM servers.