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

Re:Why we’re writing machine learning infrastructure in Go, ... by whateveracct on Friday January 17, 2020 @05:36PM (#22080286)

Go necessitates so much handrolling. Loops, concurrency patterns, resource management. You can't abstract over much, so you end up doing these things by hand constantly. Therefore you rely on brainpower, ad hoc linters (if one exists), and tests to not blow things up.

Go has its benefits and reasons to use it (especially the network effects around it). But when it comes to the three things I mention, Go is truly pathetic compared to a language like Haskell. It's amazing how much effort is wasted on those activities. I can see why a corporation would not care, but as an engineer I can do better with my time and effort for my personally-owned endeavors.

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Re:Why we’re writing machine learning infrastructure in Go, ... by cle on Friday January 17, 2020 @08:01PM (#22081381)

As an individual, many of Go's benefits aren't as useful. It's optimized for team settings, emphasizing consistency, readability, explictness, and low cognitive overhead, which are all major weaknesses of Haskell, and major reasons it's not widely used in industry.

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Re:Why we’re writing machine learning infrastructure in Go, ... by whateveracct on Friday January 17, 2020 @08:54PM (#22081630)

For many applications, Go has higher cognitive overhead than Haskell. Modulo learning Haskell of course, but still.

Go is made to treat people as Resources. Full stop. That explains everything about it's benefits.

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