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December 12, 2023 - January 10, 2024
But an algorithm is just a finite sequence of steps used to solve a problem,
Optimal stopping tells us when to look and when to leap. The explore/exploit tradeoff tells us how to find the balance between trying new things and enjoying our favorites. Sorting theory tells us how (and whether) to arrange our offices. Caching theory tells us how to fill our closets. Scheduling theory tells us how to fill our time.
Instead, tackling real-world tasks requires being comfortable with chance, trading off time with accuracy, and using approximations.
Seizing a day and seizing a lifetime are two entirely different endeavors. We have the expression “Eat, drink, and be merry, for tomorrow we die,” but perhaps we should also have its inverse: “Start learning a new language or an instrument, and make small talk with a stranger, because life is long, and who knows what joy could blossom over many years’ time.”
When balancing favorite experiences and new ones, nothing matters as much as the interval over which we plan to enjoy them.
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.
In the memorable words of management theorist Chester Barnard, “To try and fail is at least to learn; to fail to try is to suffer the inestimable loss of what might have been.”
The success of Upper Confidence Bound algorithms offers a formal justification for the benefit of the doubt. Following the advice of these algorithms, you should be excited to meet new people and try new things—to assume the best about them, in the absence of evidence to the contrary. In the long run, optimism is the best prevention for regret.
To live in a restless world requires a certain restlessness in oneself. So long as things continue to change, you must never fully cease exploring.
Cooking for two is typically no harder than cooking for one, and it’s certainly easier than cooking for one person twice. But sorting, say, a shelf of a hundred books will take you longer than sorting two bookshelves of fifty apiece: you have twice as many things to organize, and there are twice as many places each of them could go. The more you take on, the worse it gets. This is the first and most fundamental insight of sorting theory. Scale hurts.
A research scientist at IBM and professor at UC Santa Cruz, Whittaker, for almost two decades, has been studying how people manage personal information. (He wrote a paper on “email overload” in 1996, before many people even had email.) In 2011, Whittaker led a study of the searching and sorting habits of email users, resulting in a paper titled “Am I Wasting My Time Organizing Email?” Spoiler alert: the conclusion was an emphatic Yes.
“Things which matter most must never be at the mercy of things which matter least,” Goethe allegedly proclaimed; but while that has the ring of wisdom about it, sometimes it’s just not true. Sometimes that which matters most cannot be done until that which matters least is finished, so there’s no choice but to treat that unimportant thing as being every bit as important as whatever it’s blocking.
in 1754, Horace Walpole coined the term “serendipity,” based on the fairy tale adventures of The Three Princes of Serendip (Serendip being the archaic name of Sri Lanka),
the mathematician John Nash proved in 1951 that every two-player game has at least one equilibrium. This major discovery would earn Nash the Nobel Prize in Economics in 1994 (and lead to the book and film A Beautiful Mind, about Nash’s life). Such an equilibrium is now often spoken of as the “Nash equilibrium”—the “Nash”
The road to hell is paved with intractable recursions, bad equilibria, and information cascades. Seek out games where honesty is the dominant strategy. Then just be yourself.
trade off the costs of error against the costs of delay, and take chances. These aren’t the concessions we make when we can’t be rational. They’re what being rational means.
