Only if you did it at a company like Google where it's being talked about and you've got that large a user base. Inside most of corporate America internal infrastructure / modernization efforts get little recognition.

I wrote an entire (Torch-like - pre PyTorch) C++-based NN framework myself, just as a hobbyist effort. Ran on CPU as well as GPU (CUDA). For sure it didn't compete with TensorFlow in terms of features, but was complete enough to build and train things like ResNet. A lot of work to be sure, but hardly legendary.

> Only if you did it at a company like Google where it's being talked about and you've got that large a user base

Google has lots of folks who had access to the similar level of resources and no one but Jeff and Sanjay made it. Large scale engineering is not just about writing some fancy infra code, but a very rigorous project to convince thousands of people to onboard which typically requires them to rewrite significant fraction of their production code, typically referred as "replacing wheels on a running train". You gotta need lots of evidence, credits and visions to make them move.

> "replacing wheels on a running train"

Yeah - just finished migrating a system of 100+ Linux processes all inter-communicating via CORBA to use RabbitMQ instead. Production system with 24x7 uptime and migration spread over more than a year with ongoing functional releases at the same time. I prefer to call it changing the wheels on a moving car.

No doubt it's worse at Google, but these type of infrastructure projects are going on everywhere, and nobody is getting medals.