Optimization algorithms and the life lessons they taught me

Optimization is about maximizing or minimizing something. The math behind how you do that has taught me some important life lessons, including: (Gradient descent) Incremental progress with regular course corrections will eventually get you where you want to go. (Soft constraints) Giving yourself some wiggle room can help you avoid black and white thinking. (Local minima) Sometimes things have to get worse before they get better. (Multi-objective optimization) Managing the tradeoffs between multiple conflicting goals can help you reach both goals better. (Overfitting) Optimizing too hard can actually make you worse off, and so it’s important to know when to quit. 

Links: 

Joggling: https://www.designreview.byu.edu/collections/being-the-best-in-the-world-is-easy 

Exchanging money for time: https://www.lesswrong.com/posts/cvDtmPNCyrkpg4d4F/units-of-exchange

https://www.clearerthinking.org/tools/value-of-your-time-calculator 

Russian internet trolls: https://en.wikipedia.org/wiki/Russian_web_brigades