1) Performance can be a genuine requirement of the product, i.e. if it's not fast enough, it doesn't ship. You can't ship faster and cheaper by sacrificing the thing you need to ship (well, you can, but then you're shipping a different product, not meeting the same requirements sooner; it's no different than cutting a feature).
2) Many processes can't be horizontally scaled in an efficient way, period. Not because the programmer is ignorant of some cool algorithm, but because the problem is fundamentally expensive to parallelize. Maybe you end up getting something like a 20% boost by having twice as many nodes, even after applying all the cool algorithms. And you don't necessarily get that scalability in your code base for free, either.
3) "Speed" in the mobile and embedded spaces is often as much about energy efficiency and thermal management as getting done sooner.
4) The metrics for deciding that Python is faster to develop in only measure small problems. People tend to shy away from Python for bigger projects, and the reasons for this are pretty hotly debated.
1) Performance can be a genuine requirement of the product, i.e. if it's not fast enough, it doesn't ship. You can't ship faster and cheaper by sacrificing the thing you need to ship (well, you can, but then you're shipping a different product, not meeting the same requirements sooner; it's no different than cutting a feature).
2) Many processes can't be horizontally scaled in an efficient way, period. Not because the programmer is ignorant of some cool algorithm, but because the problem is fundamentally expensive to parallelize. Maybe you end up getting something like a 20% boost by having twice as many nodes, even after applying all the cool algorithms. And you don't necessarily get that scalability in your code base for free, either.
3) "Speed" in the mobile and embedded spaces is often as much about energy efficiency and thermal management as getting done sooner.
4) The metrics for deciding that Python is faster to develop in only measure small problems. People tend to shy away from Python for bigger projects, and the reasons for this are pretty hotly debated.