Fortran is in a very strange position in the current tech landscape.
There is a race of sorts going on, to simplify and commoditize high performance computing in the post-Moore's era. This means enabling things like easy GPU programming, easy multi-core programming, easy "number crunching" etc. Historically this was the stuff of esoteric HPC (high performance computing) pursued by highly specialized computational scientists etc. (read -> an important but non-economic domain that subsisted largely on government funds).
Yet suddenly the same arcane HPC is effectively also the domain of "AI" and the associated planetary hyperventilation. Now all sorts of modern initiatives and language ecosystems aim to reposition to gainfully intermediate that AI revolution. Python was the scripting language that somewhat unexpectedly enabled all this, but now its warts are under the microscope and people think of various alternatives (julia), supersets (mojo), newcomers like rust etc. But that race is definetely not settled and it might not be so for quite some time. The requirements are highly non-trivial.
As far as taking part in this race, Fortran seems to have missed not one but several boats. Yet the fact remains that it was a language designed for number crunching and evolved as language for HPC, with parallel computing features (since F90) etc. It combines easy to read imperative numerical code with near optimal computational performance.
Its like a former world champion in a sport that was fell out of favor for a long time but is now unexpectedly back in vogue. So the question is whether the champ can get back into shape or make room for new contenders :-)
There is a race of sorts going on, to simplify and commoditize high performance computing in the post-Moore's era. This means enabling things like easy GPU programming, easy multi-core programming, easy "number crunching" etc. Historically this was the stuff of esoteric HPC (high performance computing) pursued by highly specialized computational scientists etc. (read -> an important but non-economic domain that subsisted largely on government funds).
Yet suddenly the same arcane HPC is effectively also the domain of "AI" and the associated planetary hyperventilation. Now all sorts of modern initiatives and language ecosystems aim to reposition to gainfully intermediate that AI revolution. Python was the scripting language that somewhat unexpectedly enabled all this, but now its warts are under the microscope and people think of various alternatives (julia), supersets (mojo), newcomers like rust etc. But that race is definetely not settled and it might not be so for quite some time. The requirements are highly non-trivial.
As far as taking part in this race, Fortran seems to have missed not one but several boats. Yet the fact remains that it was a language designed for number crunching and evolved as language for HPC, with parallel computing features (since F90) etc. It combines easy to read imperative numerical code with near optimal computational performance.
Its like a former world champion in a sport that was fell out of favor for a long time but is now unexpectedly back in vogue. So the question is whether the champ can get back into shape or make room for new contenders :-)