Perhaps it could be this: if my value comes from running some crazy interesting high level
Math derived machine learning model on data and I’m highly paid the opportunity cost to invest the time and effort to both become good at and write C++ is higher than if I can do the same thing in a few lines of python and just throw some more compute at the problem since that’s a fixed cost.
Compute is most definitely a marginal cost rather than a fixed cost....
And when you start talking about buying 10s of millions in additional hardware to support the project you're trying to launch you start thinking pretty hard about whether you can speed things up.
And for practitioners most of this is not crazy high level math, it's first year linear algebra and multivariable calculus at most, and generally just lego blocks, intuition and data work.
> Perhaps it could be this: if my value comes from running some crazy interesting high-level Math-derived ML model on data, and I’m highly paid, then the opportunity cost of becoming good at C++ is higher than if I can do the same thing in a few lines of python and just throw some more compute at the problem, since that’s a fixed cost.
Add some hyphens and commas and shed a bit of cruft, and it's fine IMO. (I hope you don't mind my speculative editing.)
I appreciate the feedback. Defending wordy stream-of-consciousness writing style is not a hill I want to die on.
I did realize that if I have to throw a million cores at something vs. 1000 perhaps it would make sense to spend the effort or buy the time from an expert in C++ so as to save on the compute cost. But then, what if those million cores are only needed for a a day or an hour? Then python or some other rapid prototyping language would make a bit more sense imo.
