Models by mlxa

meet_annually = 20 to 300
interest_ratio = 0.02 to 0.5
boyfriend_rate = meet_annually * interest_ratio / 15 * (1 / 365)
t_days = exponential(boyfriend_rate)

// How many dollars can be saved, if the problem is totally solved
problem_size = lognormal(log(100), log(10)) + // journalists
lognormal(log(1000), log(10)) + // news agencies
lognormal(log(10), log(10)) // individuals

// Chance that we manage to implement a deeper and higher-quality search
better_tech = bernoulli(0.1)
// Number of months till the feature is copied
monopoly_time = lognormal(log(6), log(4))

me_danger = bernoulli(0.3)
me = min(me_danger * (1 to 4) + (1 - me_danger) * (15 to 75), 90)
ai_danger = bernoulli(0.5)
ai = ai_danger * (4 to 27) + (1 - ai_danger) * 100
nuke_danger = bernoulli(0.04)
nuke = nuke_danger * uniform(0, 60) + (1 - nuke_danger) * 100
climate_danger = bernoulli(0.2)
climate = climate_danger * (10 to 40) + (1 - climate_danger) * 100
total = min(min(min(min(me, ai), nuke), climate), 60)

/*
Describe your code here
*/

a = normal(2, 5)