> There are so many places where computation is far from free and size matters (embedded, HPC for example).
Even in more typical use cases, it matters: for example performance or memory use can mean the difference between a small or large EC2 instance which has very real cost implications. Or it affects battery life of my phone app. Or between my application feeling fluid or laggy.
All of there’s things have real implications for users.
I very much care when I need a top of the line computer to run some shitty application that should be able to run on 20 year old hardware.
Yet I also understand programmer ergonomics and recently implemented an interpreter for a domain specific language in an already not the fastest language because productivity mattered more to me and correct easy to write domain code mattered more to me. But the point is that it was a conscious decision made after weighing the costs and benefits, not just because I think compute and memory are free. They’re not, this has a real cost for me being able to run it, in terms of servers, but with the benefit that I can replace complex buggy code that took me months to write, with simple easy to understand code that I could write in a few hours (and a thoroughly unit tested parser and interpreter that took a week to write)