About the Author
Brian Christian is the author of The Most Human Human, a Wall Street Journal bestseller, New York Times editors’ choice, and a New Yorker favorite book of the year. His writing has appeared in The New Yorker, The Atlantic, Wired, The Wall Street Journal, The Guardian, and The Paris Review, as well as in scientific journals such as Cognitive Science, and has been translated into eleven languages. He lives in San Francisco.
Tom Griffiths is a professor of psychology and cognitive science at UC Berkeley, where he directs the Computational Cognitive Science Lab. He has published more than 150 scientific papers on topics ranging from cognitive psychology to cultural evolution, and has received awards from the National Science Foundation, the Sloan Foundation, the American Psychological Association, and the Psychonomic Society, among others. He lives in Berkeley.
A fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind
All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us.
In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.
##很久以前就知道這本書瞭,不過看著"算法"兩字實在沒興趣。直到某天翻Google Talks, 發現作者的講座很受歡迎,看瞭看纔發現確實很有意思 放在國內的語境下,這本書叫"心智模型",或model thinker可能好一點 介紹裏寫 "A fascinating exploration of how insights from computer ...
評分##《指導生活的算法》 生活中的很多復雜決策,看上去沒有規律可循,實際上是可以用算法來解決的。e.g.找對象用到的37%法則 很多時候我們會沉迷在細節裏,看不清大方嚮,其實是犯瞭數學上的過度擬閤錯誤。 時間問題本質上是個數學問題,用數學傢的辦法管理時間,纔能活得更有效率。
評分##Have you updated your OS today yet? #wethebots
評分##持續21天的《算法之美》同讀打卡結束:現貼齣本書的摘抄和感悟,希望對其他讀者有所幫助。 2018.10.08《算法之美》第一章 1. 今日關鍵詞:給定量。幾乎不會隨著時代的變遷而發生改變的事情,在代數學上,被稱為給定量。例如符閤自然規律,很難被改變的現象。 2. 無信息博弈。我...
評分##37% | 關鍵在於時間,假設你還打算住很久,那就應該去積極探索新事物,冒點險是值得的 | 避免過度擬閤 1限定思考時間。比如一天小時之內必須完成報告。2限定內容長度。比如 “電梯談話” 。3在白闆上討論商業計劃,要使用粗的馬剋筆,筆畫越粗,對你的思維越有利,越能逼著你去考慮大局
評分 評分從運動聯盟排對陣錶的角度看幾種排序算法的角度倒是新穎。從第六章貝葉斯之後開始起飛瞭。從 overfitting 飛躍到瞭進化中的滯後,第七章 randomness 提到的 Monte Carlo 原來是被正經在研究原子彈的時候發明齣來的,我當初還覺得自己用它省去瞭一些數學證明是作弊,turns out s...
評分##37%規則:以買房為例,目標一年內,前 37% 的時間隻看不買,在預算內瞭解一下市場上哪些房子你喜歡,哪些不喜歡,記住這個階段內你看到過的最滿意的那個,等到過瞭 37% 這個時間點,一旦遇到比前一階段那個最好的房子好,或者類似的房子,就毫不猶豫地買下來。數學傢的時間管理思維:1. 最近截止日期優先 2. 如果最近截止日期優先法還是做不完,優先放棄佔用時間最長的任務 3. 如果牽涉到別人的等待時間,則完成時間短的任務優先 4. 小事與要事的衡量公式,任務密度 = 重要程度 / 完成時間,然後按照任務的密度由高到低的順序去做。
評分##37% | 關鍵在於時間,假設你還打算住很久,那就應該去積極探索新事物,冒點險是值得的 | 避免過度擬閤 1限定思考時間。比如一天小時之內必須完成報告。2限定內容長度。比如 “電梯談話” 。3在白闆上討論商業計劃,要使用粗的馬剋筆,筆畫越粗,對你的思維越有利,越能逼著你去考慮大局
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