Comment by Qem
2 years ago
Python 3.11.6 (main, Oct 3 2023, 00:00:00) [GCC 13.2.1 20230728 (Red Hat 13.2.1-1)] on linux
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>>> population_base = [100_000_000, 1_000_000_000, 8_000_000_000]
>>> for population in population_base:
... print('15s/day for',population, 'people equals:', round((15*population)/3600), 'man-hours/day')
...
...
15s/day for 100000000 people equals: 416667 man-hours/day
15s/day for 1000000000 people equals: 4166667 man-hours/day
15s/day for 8000000000 people equals: 33333333 man-hours/day
Now compare that to the total productivity loss (using whatever marginal efficiency deflator you think is reasonable).
If you're trying to get shorter workdays, go for that.
If you're trying to get more open source labor, go for that.
Arguing that the best way to target the second is via the first seems tenuous at best.
I guess that means I'm not the only person to use a repl for calculations. Neat!
(Though this has evolved a bit for me, in order of tidiness/laziness : repl -> jupyter -> GPT+ data analysis)