l'empathie mécanique @dpwiz@qoto.org

@acegikmo your "t"s are on the bottom and "b"s on the left

s/b/l/g
s/t/b/g

@amiloradovsky she's not interested in your degree, it's what you can do with it

@amiloradovsky "stop waiving your degree around and get to work!"

@amiloradovsky degree is offensive word, basically a "dick"

@amiloradovsky but also, main: "stay away from me you fucking main"

@amiloradovsky jack is a racial slur too.

“Those jacks took our jobs and corrupted our country.”

Il faut imaginer Sisyphe gagnant

@xerz @acegikmo looks like vanilla type classes to me...

@poppyhaze Air, a schedule 2 substance

@carnage4life CNet: Let's generate and post some random crap!
Also CNet: oh no, our ratings have tanked, maybe we should delete some old content

@reidrac@social.sdf.org Please go on. Let the game become its best version.

(Unless this block you from having something even better!)

@amiloradovsky i think using lognormal makes sense given it represents the long tail of "ways this can go wrong" while yielding to central limit nicely.

I just thought that ELI5 of it can be something like "estimating order of magnitude". Something like "weeks" is anywhere from 7 days to a month.

@amiloradovsky those "hours" numbers, are lower/upper bound? Mean/median? Anyway, there's a missing variance information. And usually that's what screws your deadlines. Sufficiently high average numbers aren't actionable.

@amiloradovsky a cli version would be nice indeed

@amiloradovsky squiggle is just a bunch of js, should work offline.

You don't need to have a statistics insight, just combine those intervals and get the risk profile: given X amount of resources I will fuck that up in Y% of cases.

@xameer lazy eval is basically GC for execution.

If you like your memory and cars on manual, you'll hate it there.

@amiloradovsky It is easy enough to run guesstimates:

https://www.squiggle-language.com/playground#code=eNptkdtqwzAQRH9lMBRaGtILbSmFPPU3DGEdbWwRWRukdYwp%2FfeulPTy0EdbO2dmdj8ax3uagr6L4%2BatubtD2%2BjAUMoH%2BAymvKzQTQqvmGUKDh3jxGnBQMlBBT3XRz5xxJ6ycmqbNhrpRxFFDXhgBM4ZOlDEEwaZUsa1xLDg%2BQqUGDJp8JzyTZVTdP8gRrHBinj9RlBPPq5QSQ%2BQPR7va%2F6M4A91WGtIsdhdkDka%2F5hYddnmyWgbS2M9XtHGatw2sw%2FhbEdwtEASdJZSi7ad122tvjGFyR5efmQjLbac2VQhMbkFzpcK6%2FP%2B9qXEqlTa1UoX%2Fjz4wOvCNle37aeyo40VMfbT%2FYVdTjKylVY%2FcnnZyXgMrOZWopqrS74coFtwouQp7vh8gzWv8X3QbNM61M%2FZO86KRLG3QRWlYKZ%2Ft3KLP11v8RvuEinKjCBygG23EI%2BcdhzVymQ7Rf2VfD9oG5vPL9Af05U%3D

But, as they say in docs, you gonna need a bit of training to get overconfidence under control.
The good news here, is the `x to y` model is less underconfidence-sensitive so you can set "protect thy ass" upper ranges and still get an realistic, actionable estimate.

@amiloradovsky lognormal from percentile intervals for the rescue!

https://www.squiggle-language.com/docs/Guides/DistributionCreation#to

@fortune Privacy is the beginning of anarchy.

@joris state machines are hard