If you are a professional writer – i.e., if someone else is getting paid to worry about how your words are formatted and printed – Emacs outshines all other editing software in approximately the same way that the noonday sun does the stars. It is not just bigger and brighter; it simply makes everything else vanish.
— In the Beginning…
— Neal Stephenson
2013.02.01 Friday ACHK
2013.01.28 Monday ACHK
The web.py slogan is: “Think about the ideal way to write a web app. Write the code to make it happen.”
This is literally how I developed web.py. I wrote a web application in Python just imagining how I wanted the API to be.
— The web.py Philosophy
— Aaron Swartz
2013.01.25 Friday ACHK
I’m not a very good speaker. I say “um” a lot. Sometimes I have to pause when I lose my train of thought. I wish I were a better speaker. But I don’t wish I were a better speaker like I wish I were a better writer. What I really want is to have good ideas, and that’s a much bigger part of being a good writer than being a good speaker.
Having good ideas is most of writing well. If you know what you’re talking about, you can say it in the plainest words and you’ll be perceived as having a good style. With speaking it’s the opposite: having good ideas is an alarmingly small component of being a good speaker.
I first noticed this at a conference several years ago. There was another speaker who was much better than me. He had all of us roaring with laughter. I seemed awkward and halting by comparison. Afterward I put my talk online like I usually do. As I was doing it I tried to imagine what a transcript of the other guy’s talk would be like, and it was only then I realized he hadn’t said very much.
— Writing and Speaking
— March 2012
— Paul Graham
2013.01.25 Friday ACHK
2010.01.03 Sunday ACHK
Being productive
= having a lot of products, a lot of results
— Me@2012.03.19
2013.01.24 Thursday (c) All rights reserved by ACHK
lisper 4 days ago | link
I was never in academia, but I was a researcher (at NASA) so I played the publishing game. And if you look at my record, I was relatively good at it. Not only was my publications list fairly long, but my work was also pretty widely referenced. But since my career no longer depends on it, I am now free to say that I credit my success almost entirely to gaming the system. This is not to say that I didn’t do good work (I think I did), but there was virtually no correlation between what I thought was quality work and what I actually got rewarded for. The vast majority of my publications were minor tweaks on previous work that were specifically engineered to get past the program committees of key conferences. My best work (by my own quality metric) either went unnoticed, or could not get accepted for publication at all. When it got to the point where I was faced with a very stark choice between continuing to produce bullshit and get rewarded for it, or to do what I thought was good work and eventually get fired, I quit.
Evbn 4 days ago | link
Industry isn’t so different. My salary is determined by 2 days of interviews and negotiations, and only slightly perturbed by my performance over the next several years.
— Hacker News
2013.01.11 Friday ACHK
zatara 59 days ago | link
I am almost afraid to ask you this, but here it goes.
On the last few weeks/months before starting Viaweb, did you consider yourself a failure for being almost 30, well-educated but out of the formal career track, “poor” and unmarried? If so, was that the fuel behind your many amazing achievements later on?
—–
pg 59 days ago | link
No, not really. I’d written the two Lisp books, and people liked those. Not a lot of people, but they were people whose opinions I cared about. Actually Viaweb felt like more of a compromise than the way I’d been living before, because it was something I was doing mostly for money.
—–
sayemm 58 days ago | link
So, you finally had your first taste of startup success at age 34. And you started Y Combinator at 41.
Think your story, along with many others in the Valley (e.g. Jim Clark), goes to show that this is a long-term game, and it only gets better with age and experience.
— Hacker News
2013.01.11 Friday ACHK
這段改編自 2010 年 4 月 3 日的對話。
《SICM》（Structure and Interpretation of Classical Mechanics）中的編程語言，除了 Scheme 的本體外，還會用到作者特製的力學程式庫 Scmutils。而這個程式庫（library）卻只有 Linux 的版本，不能安裝在 Windows 之中。那導致我要特意在我的 Windows 中，先裝一個 virtual machine（虛擬機器），從而在那個虛擬機器之上，再安裝一個 Linux 作業系統。
閱讀《SICM》，除了間接令我，發現「時間」的定義外，還令我第一次接觸「virtual machine」這個概念。兩者各自都是，我個人智力發展的一個里程碑。
— Me@2012.12.25
2012.12.25 Tuesday (c) All rights reserved by ACHK
SICM, 3 | SICP, 2
這段改編自 2010 年 4 月 3 日的對話。
當年，我初看《SICM》（Structure and Interpretation of Classical Mechanics）時，我不太懂做那些練習題目，因為那時，我是只是初學，而尚未能掌握，內裡的編程語言 Scheme programming language。
為了熟習 Scheme，我先行閱讀了《SICM》的姊妹作，《SICP》（Structure and Interpretation of Computer Programs）的頭幾課。
《SICP》跟《SICM》，同樣是超級名著。但是它不易理解。幸好，它官方網站提供了，一些 1986 年的講課錄影。當年（2006），尚未流行使用 YouTube，所以我要花很多時間，下載那些錄影。我還記得，每節課的錄影檔案，有 600MB 那麼大。
雖然那麼費神，但卻換來意外的收穫。《SICP》令我瞭解「時間」的定義。
 |
| This image is taken from 《SICP》 and 《SICP》 itself is licensed under a Creative Commons Attribution-Noncommercial 3.0 Unported License. |
最令我意想不到的是，那竟然是來自一本電腦書，而不是物理書。
— Me@2012.12.23
2012.12.23 Sunday (c) All rights reserved by ACHK
To get a feeling of dying, play the video game Dear Esther till the end.
— Me@2012.12.16
When you finish a video game, you go back to the real world;
when your real world is over, you go back to your realer world.
— Me@2012.12.21
There is another theory, that in a car crash, Esther was put in a coma, and the voice is her husband talking to her, in hopes that she can hear him. She wanders along beaches and through caves that are filled with sometimes strange things, things that are bits and fragments of what she is hearing and what her mind is putting together. At the end when Esther jumps, it is possible her heart rate increased, showing up on the hospital monitor, which would explain the voice at the end saying “Come back,” and the darkness at the end would probably be her dying in the coma.
— Wikipedia on Dear Esther
— 21:01, 29 May 2012
2012.12.22 Saturday (c) All rights reserved by ACHK
這段改編自 2010 年 4 月 3 日的對話。
《SICM》（Structure and Interpretation of Classical Mechanics）總共花了我兩年的時間。我大概由 2006 年，閱讀至 2008 年。除了閱讀課文外，我還把內裡的幾乎所有練習，無論是數學題，還是程式題，都一一擊破。要花那麼長的時間才能完成，主要是因為上班的工務繁忙。每日可以花在自修的時間，通常也不會超過半小時。
雖然時間成本奇高，但是，我仍然覺得是值得的。一來，它是一本名著，質素非常高。二來，它竟然把我人生的兩大興趣，重疊在一起。
— Me@2012.12.21
2012.12.21 Friday (c) All rights reserved by ACHK
SICM, 1.3
這段改編自 2010 年 4 月 3 日的對話。
即使有時會剛巧得到正確的結果，但是由於胡亂推導，大家也不知道，那個正確結果的真正由來。所以，每一代的學生，都不可能明白那一個部分。
要戒除「暗地裡轉換意思」的陋習，並不困難。如果透過編寫程式，來解決力學問題，你就要先把那個力學問題，翻譯制訂成電腦程式的版本。那樣，在過程中，你自然會百分百釐清了，所有符號的意義，因為，在同一個程式中，同一個符號，電腦只會容許，有唯一的一個意思。電腦不會讓你（，在沒有事先特別聲明的情況下），任意放大、縮小 或 更改，那一個符號的意思。電腦不會錯失，你任何的「概念扭曲」或者「概念滑轉」，所以不會有絲毫的容忍。
由於要你「寫程式學力學」，《SICM》（Structure and Interpretation of Classical Mechanics）會教你一種編程語言 Scheme programming language。這種語言的好處是，你學了一句後，就可以立刻應用那一句，而不像一般的程式語言，應用前，要先行學習一大堆語法。
（安：那本書真的用 programming（電腦編程），來講解 mechanics（力學）？）
無錯。正如一般的教科書，課文以外，《SICM》還有例題和練習題。而例子和練習之中，有超過一半是程式題目。其餘的則是文字題目和數學題目。
但是，《SICM》的正題始終是力學，而不是寫程式。正如，力學需要用數學。但是數學在這本書內，只是工具，不是主菜。
— Me@2012.12.18
2012.12.19 Wednesday (c) All rights reserved by ACHK
SICM, 1.2 | 程式員頭腦 14
這段改編自 2010 年 4 月 3 日的對話。
“In almost all textbooks, even the best, this principle is presented so that it is impossible to understand.” (K. Jacobi, Lectures on Dynamics, 1842-1843). I have not chosen to break with tradition.
— V. I. Arnold, Mathematical Methods of Classical Mechanics, footnote, p. 246
— Structure and Interpretation of Classical Mechanics
這本書的主要好處是，它會要求你，透過編寫簡短的電腦程式，來解決力學問題。反過來說，你亦可以透過解決力學問題，來練習 programming（電腦編程）。
這本書的主旨是，在經典力學，人們做公式推導的過程中，有時會把一些數字符號的意思，不自覺地改了一點，導致推導失效。例如，運算步驟的第二行和第五行，都會出現的函數 f 這個符號。但是，第二行的 f ，是代表 f(x,y)。而第五行的 f ，卻是指 f(x(t),y(t))。
即使有時會剛巧得到正確的結果，但是由於胡亂推導，大家也不知道，那個正確結果的真正由來。所以，每一代的學生，都不可能明白那一個部分。
如果透過編寫程式，來解決力學問題，你就可以避免了「暗地裡轉換意思」的陋習，因為在同一個程式中，同一個符號，電腦只會容許，有唯一的一個意思。電腦不會錯失，你任何的「概念扭曲」或者「概念滑轉」，所以不會有絲毫的容忍。
— Me@2012.12.17
2012.12.17 Monday (c) All rights reserved by ACHK
意念可樂 3
A good scientist is a person with original ideas. A good engineer is a person who makes a design that works with as few original ideas as possible. There are no prima donnas in engineering.
— Disturbing the Universe
— Freeman Dyson
handrake 2 days ago | link | parent
I think MS was pretty much the same way until very recent. Maybe companies really start making money when they stop being innovative.
— Amazon Has the Most Generous Shareholders in the World
— Hacker News
The difference between design and research seems to be a question of new versus good. Design doesn’t have to be new, but it has to be good. Research doesn’t have to be good, but it has to be new.
I think these two paths converge at the top: the best design surpasses its predecessors by using new ideas, and the best research solves problems that are not only new, but actually worth solving. So ultimately we’re aiming for the same destination, just approaching it from different directions.
— Paul Graham
2012.12.17 Monday ACHK
這段改編自 2010 年 4 月 3 日的對話。
（安：我怎樣把 mechanics（力學）學得好一點？）
哪一門力學？經典力學，還是量子力學？
（安：經典力學。）
你想應用在哪些地方？
（安：暫時純粹為了求知和娛樂。）
那我介紹一本名著給你。它叫做《SICM》（Structure and Interpretation of Classical Mechanics）。它免費發布於 MIT（麻省理工學院）的網站。
這本書的主要好處是，它會要求你，透過編寫簡短的電腦程式，來解決力學問題。反過來說，你亦可以透過解決力學問題，來練習 programming（電腦編程）。
— Me@2012.12.15
2012.12.15 Saturday (c) All rights reserved by ACHK
Recursion 7.2
Act as if = recursion
Recurse your life:
For recursion, all you need to do are just acting as if it exists and adding a terminating condition.
— Me@2011.12.14
2012.11.02 Friday (c) All rights reserved by ACHK
a good programmer’s mind = a reliable mind
— Me@2011.12.14
2012.10.29 Monday (c) All rights reserved by ACHK
wpietri 6 days ago | link
Yes. You can get to the top by competing with others; [but] you stay on top by competing with yourself.
— Hacker News
2012.10.24 Wednesday ACHK
snippyhollow 192 days ago | link
A neuron “could” store a generalized memory (the amount of information it stores is gigantic, w/o pendantically considered the DNA). However, it’s more complex than that (there are many types of memories and many means of retrieval). Basically, memories are sets of synaptic connections, and a neuron has many synapses (average ~7,000 synaptic connections/neuron to multiply by our 10^11 neurons/brain).
As you said, it may be a “key”, but it should be seen more like the memory _is_ a complete list of hashes. Not {“key”: memory} but {“key1”: {“key2”: {“key3”: {…} } }, {…}, {…}, …} and the set of {key1..keyN} is the memory. So if you removed whichever keyI in the middle, you lose the information.
(That’s not really true because there is high redundancy, but there are keys/synapses/nodes less redundant than others. The fact is, they don’t fire on only “one” neuron, they fire at a very precise region but the light still goes through a population of neurons.)
— MIT discovers the location of memories: Individual neurons
— Hacker News
2012.10.02 Tuesday ACHK
Physics Town 
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