While true, another is that “crop harvesting efficiency” and medicine are both more a biology/chemistry problem which may not interest the same people so it’s unclear they’d even attract the same thing.
It’s also missing that advancements in one field, particularly computer science, computation, and AI creates significant infrastructure that can be applied to those tasks in never before seen ways.
And finally, physical problems evolve much more slowly and is more capital intensive and requires a lot more convincing of other people. Digital problems by comparison are more “shut up I’m right, here’s the code that does X”. It’s easier to validate, easier feedback resulting in quicker mastery, etc. Not saying it’s completely bulletproof in that way, but more true than in physical sciences these days. So just throwing more people at the problem may not necessarily yield results without correct funding which historically was provided by the government (hence the huge boom in the 60s) but as the low hanging fruit were picked and government became more dysfunctional, this slowed to a crawl.
For example, personally I probably could have ended up working on fusion research if I had more economic security growing up and it felt like the nuclear industry was booming instead of constantly underdeveloped (both fission and fusion). But instead I’ve worked with computers because I felt like it was a boom segment of the economy (and it has largely been while I’ve worked) and the problems felt interesting (I’ve worked on embedded OSes, mobile OSes, ML, large distributed systems, databases, and now AI) and like there’s always interesting products to build to help improve the world.