Why we’re writing machine learning infrastructure in Go, not Python

Re:Why we’re writing machine learning infrastructure in Go, ... by dewey on Saturday January 18, 2020 @07:16AM (#22084004)

There's probably a very big difference between "industry standard" and working with a new language at a startup where a lot of things are written from scratch in a short amount of time. 50 lines of code on average for a year won't get you very far if you work on greenfield project.

The industry standard is probably very heavily biased by big corporate code bases where refactoring / architecture takes a lot more time than implementing the actual changes afterwards. Doesn't seem like a very useful calculation you are trying to do there to proof the previous poster wrong.

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Re:Why we’re writing machine learning infrastructure in Go, ... by RandyRanderson on Saturday January 18, 2020 @04:28PM (#22087366)

"There's probably a very big difference between" - that is precisely my point.

I have a lot of time playing ms flight sim and so obviously I know how to design airplanes is his argument.

Writing "greenfield" applications that no one (comparatively) is using is relatively easy. Creating systems that have four+ 9's availability, integrate with various disparate APIs, don't lose data, and,and etc is where, IMO, the learning is.

Once one has this experience, watching this micro services "movement" is, in my mind, related to global warming - like watching someone jump out of a plane with no parachute, smiling.

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