读书笔记-《The Art of Doing Science and Engineering》
作者理查德・W・汉明（Richard W. Hamming，1915–1998），是美国数学家、计算机科学家，曾参与曼哈顿计划、任职贝尔实验室，1968 年获图灵奖。
创立汉明码、汉明距离、汉明窗，奠定纠错编码与数字信号处理基础。
《The Art of Doing Science and Engineering》 这本书，源于他在美国海军研究生院开设的同名课程，1996 年出版，是《你和你的研究》完整拓展版。
全书不讲纯粹技术公式，核心传授科研做事的思维格局：区分普通研究者与顶尖学者的关键是思考方式；教人挑选有价值的问题、跨学科学习、持续自我迭代、把握机遇、长远预判行业发展；结合他在曼哈顿计划、贝尔实验室的亲身经历，搭配编码、信号处理案例讲解治学方法，适合理工科从业者提升科研格局。
姜丹讲，其实是一本《纳瓦尔宝典》式的书，以下是书中的一些摘要：
思考、学习与观察的方法
- Education is what, when, and why to do things, Training is how to do it.
教育是教你做什么、何时做以及为什么做；训练是教你怎么做。 - Moral: when you know something cannot be done, also remember the essential reason why, so later, when the circumstances have changed, you will not say, ‘It can’t be done’.
教训：当你知道某件事做不到时，也要记住根本原因，这样以后当情况发生变化时，你就不会再说’这做不到’。 - The Buddha told his disciples, ‘Believe nothing, no matter where you read it, or who said it, no matter if I have said it, unless it agrees with your own reason and your own common sense’.
佛告弟子：‘无论你在哪里读到，无论谁说的，即使是我亲口所说，只要不合你的理性和常识，就不要相信。’ - You get what you measure.
你测量什么，就得到什么。 - The instrument you use clearly affects what you see.
你使用的工具显然影响你看到的东西。 - Intelligence has a normal distribution in the population! Of course it has, it was made to be that way!
智力在人群中呈正态分布！当然如此，它本来就是被设计成那样的！
学习与准备的意义
It is claimed by many the half-life of the technical knowledge you just learned in school is about 15 years—in 15 years half of it will be obsolete (either we have gone in other directions or have replaced it with new material).
许多人声称，你在学校刚学的技术知识的半衰期大约是15年——15年后其中一半将过时（要么我们转向了其他方向，要么用新材料取代了它）。
Your anticipation means you are far, far better prepared to absorb the new things when they arise than if you sit passively by and merely follow progress.
你的前瞻性意味着，当新事物出现时，你比那些被动地坐着只是跟随进展的人准备得充分得多得多。It pays to know more than just what is needed at the moment!
掌握超出当前需要的知识总是有回报的！You establish in yourself the style of doing great things, and then when opportunity comes you almost automatically respond with greatness in your actions. You have trained yourself to think and act in the proper ways.
你要在自己身上建立做大事的风格，这样当机会来临时，你几乎会自动以伟大的行动做出回应。你已经训练自己以正确的方式思考和行动。Learning a new subject is something you will have to do many times in your career if you are to be a leader and not be left behind as a follower by newer developments.
如果你想成为领导者而非因新发展而落后的追随者，在职业生涯中你将不得不多次学习新学科。
创新
You must get the essentials of the job in mind and then design the mechanization to do that job rather than trying to mechanize the current version.
你必须先把握工作的本质，然后设计机械化方案来完成这项工作，而不是试图把现有流程原样机械化。It is first necessary to prove beyond any doubt the new thing, device, method, or whatever it is, can cope with heroic tasks before it can get into the system to do the more routine, and in the long run, more useful tasks.
任何新事物、新设备、新方法，都必须先毫无疑义地证明自己能胜任艰巨的任务，然后才有资格进入系统，去做那些更常规但长远来看更有用的工作。The purpose of computing is insight, not numbers.
计算的目的是获得洞见，而非数字。Computers manipulate symbols, not information; we are simply unable to say, let alone write a program for what we mean by the word ‘information’."
计算机操纵的是符号，而非信息；我们根本无法说清楚’信息’这个词的含义，更不用说为此编写程序了。Typically a single order of magnitude change (a factor of 10) produces fundamentally new effects, and computers are many, many times faster than hand computations. Those who claimed there was no essential difference never made any significant contributions to the development of computers.
通常，一个数量级的变化（10倍）就会产生全新的效应，而计算机比手工计算快了无数倍。那些声称没有本质区别的人从未对计算机的发展做出任何重大贡献。If you do not work on important problems then it is obvious you have little chance of doing important things.
如果你不研究重要的问题，那显然你几乎没有机会做出重要的事情。Great people can tolerate ambiguity, they can both believe and disbelieve at the same time.
伟大的人能够容忍模糊性，他们能同时既相信又不相信。
人性
- Once a boss says ‘no!’ it is very hard to get a different decision, so don’t let them say ‘No!’ to a proposal.
一旦老板说了’不！‘，就很难让他改变决定，所以别让他们对提案说’不！’。 - The human animal is not reliable, as I keep insisting, so low redundancy means lots of undetected errors, while high redundancy tends to catch the errors.
人类是不可靠的，正如我一直强调的，低冗余意味着大量未被发现的错误，而高冗余则倾向于捕捉到这些错误。