The detailed examples made this exceptionally interesting.
A minor nitpick: it is more accurate to draw the efficient frontier with axis-aligned line segments. To see why, consider points P=(1,1), Q=(3,2), R=(4,4). These points are all on the efficient frontier, because no point dominates any other in both cost and quality. But the straight line from P to R passes to the upper-left of Q, making it look as if Q is not on the efficient frontier. The solution is to draw the efficient frontier as (1,1)-(3,1)-(3,2)-(4,2)-(4,4). (It's a bit uglier though!)
If the "75%" stat is coming from Wikipedia, that's for SOV and SVO combined: https://en.wikipedia.org/wiki/Subject%E2%80%93object%E2%80%93verb#Incidence .
This seems reasonable, but I wonder whether "long-term complications" might be a bit underrated. It seems like there are a lot of viruses that have long-term effects or other non-obvious consequences. (I should add that I'm not a biologist, so this is not an informed opinion.)
The example I'm most familiar with is chicken pox causing shingles, decades later from the initial sickness. In that case, shingles is (I think) typically more severe than the original sickness, and is quite common: 1 out of 3 people develop it in their lifetime, according to the CDC.... (read more)
Thanks for your reply!
A few points where clarification would help, if you don't mind (feel free to skip some):
I find myself returning to this because the idea of a "common cortical algorithm" is intriguing.
It seems to me that if there is a "common cortical algorithm" then there is also a "common cortical problem" that it solves. I suspect it would be useful to understand what this problem is.
(As an example of why isolating the algorithm and problem could be quite different, consider linear programming. To solve a linear programming problem, you can choose a simplex algorithm or an interior-point method, and these are fundamentally different approaches that are bot... (read more)