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July 21, 2022 - April 23, 2023
in the face of slim pickings, lower your standards.
Exploration in itself has value, since trying new things increases our chances of finding the best. So taking the future into account, rather than focusing just on the present, drives us toward novelty.
“To try and fail is at least to learn; to fail to try is to suffer the inestimable loss of what might have been.”
But just as there’s a cost to not having a secretary, there’s a cost to committing too soon to a particular airline: the world might change.
Being sensitive to how much time you have left is exactly what the computer science of the explore/exploit dilemma suggests.
Minimizing the sum of completion times leads to a very simple optimal algorithm called Shortest Processing Time: always do the quickest task you can.
Live by the metric, die by the metric.
“Things which matter most must never be at the mercy of things which matter least,”
“Feel like you can’t proceed until you have a bulletproof plan in place? Replace ‘plan’ with ‘guess’ and take it easy.”
Count the number of times it has happened in the past plus one, then divide by the number of opportunities plus two.
“It really is true that the company will build whatever the CEO decides to measure.”
Giving yourself more time to decide about something does not necessarily mean that you’ll make a better decision.
an algorithm should be considered “efficient” if it runs in what’s called “polynomial time”—that is, O(n2), O(n3), or in fact n to the power of any number at all. A problem, in turn, is considered “tractable” if we know how to solve it using an efficient algorithm. A problem we don’t know how to solve in polynomial time, on the other hand, is considered “intractable.”
One of the simplest forms of relaxation in computer science is known as Constraint Relaxation. In this technique, researchers remove some of the problem’s constraints and set about solving the problem they wish they had.
if we’re willing to accept solutions that are close enough, then even some of the hairiest problems around can be tamed with the right techniques.
when we’re trying to get things done—the more likely we are to end up in a situation where finding the perfect solution takes unreasonably long.
