Sunday, August 26, 2012

The Disciplined Pursuit of Less

by Greg McKeown  |  10:00 AM August 8, 2012

Why don't successful people and organizations automatically become very successful? One important explanation is due to what I call "the clarity paradox," which can be summed up in four predictable phases:
Phase 1: When we really have clarity of purpose, it leads to success.
Phase 2: When we have success, it leads to more options and opportunities.
Phase 3: When we have increased options and opportunities, it leads to diffused efforts.
Phase 4: Diffused efforts undermine the very clarity that led to our success in the first place.
Curiously, and overstating the point in order to make it, success is a catalyst for failure.
We can see this in companies that were once darlings of Wall Street, but later collapsed. In his book How the Mighty Fall, Jim Collins explored this phenomenon and found that one of the key reasons for these failures was that companies fell into "the undisciplined pursuit of more." It is true for companies and it is true for careers.
Here's a more personal example: For years, Enric Sala was a professor at the prestigious Scripps Institution of Oceanography in La Jolla, California. But he couldn't kick the feeling that the career path he was on was just a close counterfeit for the path he should really be on. So, he left academia and went to work for National Geographic. With that success came new and intriguing opportunities in Washington D.C. that again left him feeling he was close to the right career path, but not quite there yet. His success had distracted him. After a couple of years, he changed gears again in order to be what he really wanted: an explorer-in-residence with National Geographic, spending a significant portion of his time diving in the most remote locations, using his strengths in science and communications to influence policy on a global scale. (Watch Enric Sala speak about his important work at TED). The price of his dream job was saying no to the many good, parallel paths he encountered.

What can we do to avoid the clarity paradox and continue our upward momentum? Here are three suggestions:
First, use more extreme criteria. Think of what happens to our closets when we use the broad criteria: "Is there a chance that I will wear this someday in the future?" The closet becomes cluttered with clothes we rarely wear. If we ask, "Do I absolutely love this?" then we will be able to eliminate the clutter and have space for something better. We can do the same with our career choices.
By applying tougher criteria we can tap into our brain's sophisticated search engine. If we search for "a good opportunity," then we will find scores of pages for us to think about and work through. Instead, we can conduct an advanced search and ask three questions: "What am I deeply passionate about?" and "What taps my talent?" and "What meets a significant need in the world?" Naturally there won't be as many pages to view, but that is the point of the exercise. We aren't looking for a plethora of good things to do. We are looking for our absolute highest point of contribution.

HPOC_DR.jpg

Enric is one of those relatively rare examples of someone who is doing work that he loves, that taps his talent, and that serves an important need in the world. His main objective is to help create the equivalent of National Parks to protect the last pristine places in the ocean — a significant contribution.
Second, ask "What is essential?" and eliminate the rest. Everything changes when we give ourselves permission to eliminate the nonessentials. At once, we have the key to unlock the next level of our lives. Get started by:
  • Conducting a life audit. All human systems tilt towards messiness. In the same way that our desks get cluttered without us ever trying to make them cluttered, so our lives get cluttered as well-intended ideas from the past pile up. Most of these efforts didn't come with an expiration date. Once adopted, they live on in perpetuity. Figure out which ideas from the past are important and pursue those. Throw out the rest.
  • Eliminating an old activity before you add a new one. This simple rule ensures that you don't add an activity that is less valuable than something you are already doing.
Third, beware of the endowment effect. Also known as the divestiture aversion, the endowment effect refers to our tendency to value an item more once we own it. One particularly interesting study was conducted by Kahneman, Knetsch and Thaler (published here) where consumption objects (e.g. coffee mugs) were randomly given to half the subjects in an experiment, while the other half were given pens of equal value. According to traditional economic theory (the Coase Theorem), about half of the people with mugs and half of the people with pens will trade. But they found that significantly fewer than this actually traded. The mere fact of ownership made them less willing to part with their own objects. As a simple illustration in your own life, think of how a book on your shelf that you haven't used in years seems to increase in value the moment you think about giving it away.

Tom Stafford describes a cure for this that we can apply to career clarity: Instead of asking, "How much do I value this item?" we should ask "If I did not own this item, how much would I pay to obtain it?" And the same goes for career opportunities. We shouldn't ask, "How much do I value this opportunity?" but "If I did not have this opportunity, how much would I be willing to sacrifice in order to obtain it?"

If success is a catalyst for failure because it leads to the "undisciplined pursuit of more," then one simple antidote is the disciplined pursuit of less. Not just haphazardly saying no, but purposefully, deliberately, and strategically eliminating the nonessentials. Not just once a year as part of a planning meeting, but constantly reducing, focusing and simplifying. Not just getting rid of the obvious time wasters, but being willing to cut out really terrific opportunities as well. Few appear to have the courage to live this principle, which may be why it differentiates successful people and organizations from the very successful ones.

Thursday, August 9, 2012

Notes for Graduate Students (From a Chinese PI)

Notes for Graduate Students
(Revised by September 12, 2002)

Performance
l  Progress
l  Efficiency
l  Quality
l  Quantity
l  Originality and novelty
l  Independence

Communication

l  Coordinate with colleagues for the usage of equipments, space and reagents, etc.
l  Active interactions with advisor and colleagues
l  Presentation in lab meetings: treat your every presentation as a publication
l  Be in lab meetings on time and active involvement in the discussion
l  Response to advice appropriately
l  No one is a monster in this lab.

Working as a professional scientist

l  Do you have your working model?
l  Include appropriate controls in EVERY experiment
l  Independently think and design of experiments
l  Knowledge on your field
l  Read at least two original research papers per week
l  If you disagree with your advisor, speak out!
There is absolutely NO experiment that does not have a conclusion
There is absolutely NO project that does not have a conclusion
A tough project does not mean a gradually disappearing or forgettable project
l  Take care about your plants; take actions before they die or flower in tissue culture media
l  Use equipments and reagents in a professional way

Notes

l  Record everything you have done, including negative results; photography is essential
l  Data analysis and conclusions
l  Discussion, comments and plans for future experiments
l  Record your data, even if you do not like them
l  Notes of seminars and paper readings

Working as a dedicated scientist
l  As a scientist, you must dedicate everything to this business
l  Working time: 8-hour is unpractical. There is NO way for a scientist or a Ph.D student to work only 8 hours a day!
l  Go to your mother’s house for afternoon naps and never come back!
l  Vacation: 5 weeks per year (Chinese New Year, the May Day and the National Day breaks are included)
l  Start your morning work not later than 8:30 am and afternoon work no later than 1 pm
l  Surf over the Internet for non-scientific purposes should be less than 30 min a day
l  Reading newspapers should be limited less than 30 min a day
l  Novels or other non-scientific journals/magazines are not permitted in the lab and office
l  If you are absent from the lab more than one hour, get permission first.
l  Everyone has personal business, but the lab business always has priority unless in emergency
l  In this business, an “average” student who works seven days a week is definitely more productive than a “genius” who works five days a week
l  If you are able to make any major progresses by working 8 hours a day and 5 days a week, every fortunate in this world must be on your side!

Your Efforts

l  What is your career plan?
l  How much efforts you have made?
l  It is the shared responsibilities of your advisor and yourself to move a project forward
l  You should have great concentrations on your project
l  There is no easy way to get your Ph.D. degree unless hard working
l  You should know how to use major database (e.g., NCBI and TARI) but rather than an expert on SINA, SOHU or any other non-scientific websites
l  If you cannot pass the English Test, you are partially disqualified as a Ph.D. candidate in this lab.
l  The US definition for graduate students: those who can survive and colonize on the minimal medium with vender machines as the sole carbon source in the absence of dental insurance!
l  You are working neither for your parents, your parents’ neighbors, nor your friends to solely earn a “glorious” name (Ph.D. degree) per se. You are working for your own career!
l  Working-hard before 30-year-old is the best way to prevent suffers after turning 30
l  We are NOT writers or any other non-research professionals
l  A real scientist needs a logic rather than romantic way to think!

 

Use your brains: think and work smartly

l  A good graduate student is not a robot
l  A good graduate student always knows what he/she is doing and what he/she has done
l  A good graduate student always scientifically goes beyond what he/she has been “advised”
l  A good graduate student must independently think about the project and read the data as well as catch hints derived from the data

l  You should learn and eventually know how to interpret your data
l  You should learn and eventually know how to write a paper or a progress report in a professional and logic way
l  You should be capable of tackling technical troubles by smartly using references and by discussing with coworkers
l  If you use your brain, you should be able to avoid unnecessary, stupid mistakes or to avoid making the same mistakes more than once. Many of such mistakes cannot be rescued by money (e.g., the loss of mutant seeds)
l  Mistakes resulted from brain- or thinking-less actions are not tolerated
l  Making mistakes with similar natures more than once is not tolerated


Your qualifications for a Ph.D. degree will be judged based on these criteria, which are the keys to differentiate you from a technician.

[FYI: The lab's link]

Monday, July 16, 2012

Epilogue The Ph.D. Grind

Epilogue

The Ph.D. Grind

If you are not going to become a professor, then why even bother pursuing a Ph.D.? This frequently-asked question is important because most Ph.D. graduates aren't able to get the same jobs as their university mentors and role models—tenure-track professors. There simply aren't enough available faculty positions, so most Ph.D. students are directly training for a job that they will never get. (Imagine how disconcerting it would be if medical or law school graduates couldn't get jobs as doctors or lawyers, respectively.)
So why would anyone spend six or more years doing a Ph.D. when they aren't going to become professors? Everyone has different motivations, but one possible answer is that a Ph.D. program provides a safe environment for certain types of people to push themselves far beyond their mental limits and then emerge stronger as a result. For example, my six years of Ph.D. training have made me wiser, savvier, grittier, and more steely, focused, creative, eloquent, perceptive, and professionally effective than I was as a fresh college graduate. (Two obvious caveats: Not every Ph.D. student received these benefits—many grew jaded and burned-out from their struggles. Also, lots of people cultivate these positive traits without going through a Ph.D. program.)
Here is an imperfect analogy: Why would anyone spend years training to excel in a sport such as the Ironman Triathlon—a grueling race consisting of a 2.4-mile swim, 112-mile bike ride, and a 26.2-mile run—when they aren't going to become professional athletes? In short, this experience pushes people far beyond their physical limits and enables them to emerge stronger as a result. In some ways, doing a Ph.D. is the intellectual equivalent of intense athletic training.
Here are twenty of the most memorable lessons that I've learned throughout my Ph.D. years. My purpose in sharing is not to provide unsolicited advice to students, since everyone's Ph.D. experience differs greatly; nor is it to encourage people to pursue a Ph.D., since these lessons can come from many sources. Rather, this section merely serves as a summary of what I gained from working towards my Ph.D.
  1. Results trump intentions: Nobody questions someone's intentions if they produce good results. I didn't have so-called pure intellectual motivations during grad school: I started a Ph.D. because I wasn't satisfied with engineering jobs, pressured myself to invent my own projects out of fear of not graduating on time, and helped out on HCI projects with Scott, Joel, and Jeff to hedge my bets. But I succeeded because I produced results: five prototype tools and a dozen published papers. Throughout this process, I developed strong passions for and pride in my own work. In contrast, I know students with the most idealistic of intentions—dreamy and passionate hopes of revolutionizing their field—who produce few results and then end up disillusioned.
  2. Outputs trump inputs: The only way to earn a Ph.D. is by successfully producing research outputs (e.g., published papers), not merely by consuming inputs from taking classes or reading other people's papers. Of course, it's absolutely necessary to consume before one can produce, but it's all too easy to over-consume. I fell into this trap at the end of my first year when I read hundreds of research papers in a vacuum—a consumption binge—without being able to synthesize anything useful from my undirected readings. In contrast, related work literature searches for my dissertation projects were much more effective because my reading was tightly directed towards clear goals: identifying competitors and adapting good ideas into my own projects.
  3. Find relevant information: My Ph.D. training has taught me how to effectively find the most relevant information for what I need to accomplish at each moment. Unlike traditional classroom learning, when I'm working on research, there are no textbooks, no lecture notes, and no instructors to provide definitive answers. Sometimes what I need for my work is in a research paper, sometimes it's within an ancient piece of computer code, sometimes it's on an obscure website, and sometimes it's inside the mind of someone whom I need to track down and ask for help.
  4. Create lucky opportunities: I got incredibly lucky several times throughout grad school, culminating in getting to work with Margo at Harvard during my final year. But these fortuitous opportunities wouldn't have arisen if I didn't repeatedly put myself and my work on display—giving talks, chatting with colleagues, asking for and offering help, and expressing gratitude. The vast majority of my efforts didn't result in serendipity, but if I didn't keep trying, then I probably wouldn't have gotten lucky.
  5. Play the game: As a Ph.D. student, I was at the bottom of the pecking order and in no position to change the “academic game.” Specifically, although I dreaded getting my papers repeatedly rejected, I had no choice but to keep learning to play the publication game to the best of my abilities. However, I was happy that I played in my own unique and creative way during the second half of grad school by pursuing more unconventional projects while still conforming to the “rules” well enough to publish and graduate.
  6. Lead from below: By understanding the motivations and personalities of older Ph.D. students, professors, and other senior colleagues, I was able to lead my own initiatives even from the bottom of the pecking order. For example, after I learned Margo's research tastes by reading her papers and grant applications, I came up with a project idea (Burrito) that we were both excited about. If I were oblivious to her interests, then it would have been much harder to generate ideas to her liking.
  7. Professors are human: While this might sound obvious, it's all too easy to forget that professors aren't just relentless research-producing machines. They're human beings with their own tastes, biases, interests, motivations, shortcomings, and fears. Even well-respected science-minded intellectuals have subjective and irrational quirks. From a student's perspective, since professors are the gatekeepers to publication, graduation, and future jobs, it's important to empathize with them both as professionals and also as people.
  8. Be well-liked: I was happier and more productive when working with people who liked me. Of course, it's impossible to be well-liked by all colleagues due to inevitable personality differences. In general, I strived to seek out people with whom I naturally clicked well and then took the time to nurture those relationships.
  9. Pay some dues: It's necessary for junior lab members to pay their dues and be “good soldiers” rather than making presumptuous demands from day one. As an undergraduate and master's student at MIT, I paid my dues by working on an advisor-approved, grant-funded project for two and a half years rather than trying to create my own project; I was well-rewarded with admissions into top-ranked Ph.D. programs and two fellowships, which paid for five years of graduate school. However, once I started at Stanford, I paid my dues for a bit too long on the Klee project before quitting. It took me years to recognize when to defer to authority figures and when to selfishly push forward my own agenda.
  10. Reject bad defaults: Defaults aren't usually in the best interests of those on the bottom (e.g., Ph.D. students), so it's important to know when to reject them and to ask for something different. Of course, there's no nefarious conspiracy against students; the defaults are just naturally set up to benefit those in power. For example, famous tenured professors like Dawson are easily able to get multi-year grants to fund students to work on “default” projects like Klee. As long as some papers get published from time to time, then the professor and project are both viewed as successful, regardless of how many students stumbled and failed along the way. Students must judge for themselves whether their default projects are promising, and if not, figure out how to quit gracefully.
  11. Know when to quit: Quitting Klee at the end of my third year was my most pivotal decision of grad school. If I hadn't quit Klee, then there would be no IncPy, no SlopPy, no CDE, no ProWrangler, and no Burrito; there would just be three or more years of painful incremental progress followed by a possible “pity graduation.”
  12. Recover from failures: Failure is inevitable in grad school. Nothing I did during my first three years made it into my dissertation, and many paths I wandered down in my latter three years were also dead-ends. Grad school was a safe environment to practice recovering from failures, since the stakes were low compared to failing in real jobs. In my early Ph.D. years, I would grow anxious, distraught, and paralyzed over research failures. But as I matured, I learned to channel my anger into purposeful action in what I call a productive rage. Every rejection, doubt, and criticism spurred me to work harder to prove the naysayers wrong. Lessons learned from earlier failures led to successes later in grad school. For example, my failure to shadow professional programmers at the beginning of my second year taught me how and who to approach for these sorts of favors, so I later succeeded at shadowing computational researchers to motivate my dissertation work; and my failure to get lots of real users for IncPy taught me how to better design and advertise my software so that I could get 10,000 users for CDE.
  13. Ally with insiders: I had an easy time publishing papers when allied with expert insiders such as Scott and Joel during my second year, Tom during my MSR internship, and Jeff during my fifth year. They knew all the tricks of the trade required to get papers published in their respective subfields; the five papers that I co-wrote with these insiders were all accepted on their first submission attempts. However, struggling as an outsider—with Dawson on empirical software measurement in my second year and then on my solo dissertation projects—was also enriching, albeit more frustrating due to repeated paper rejections.
  14. Give many talks: I gave over two dozen research presentations throughout my Ph.D. years, ranging from informal talks at university lab group meetings to conference presentations in large hotel ballrooms. The informal talks I gave at the beginning of projects such as IncPy were useful for getting design ideas and feedback; those I gave prior to submitting papers were useful for discovering common criticisms that I needed to address in my papers. Also, every talk was great practice for improving my skills in public speaking and in responding to sometimes-hostile questions. Finally, talks sometimes sparked follow-up discussions that led to serendipity: For example, after watching my first talk on IncPy, a fellow grad student emailed me a link to Fernando's blog post about Python in science; that email encouraged me to reach out to Fernando, who would later inspire me to improve IncPy and then to invent CDE. Over a year later, my Google Tech Talk on CDE directly led to my super-chill summer 2011 internship.
  15. Sell, sell, sell: I spent the majority of my grad school days heads-down grinding on implementing research ideas, but I recognized that convincingly selling my work was the key to publication, recognition, and eventual graduation. Due to the ultra-competitive nature of the paper publication game, what often makes the difference between an accept and a reject decision is how well a paper's “marketing pitch” appeals to reviewers' tastes. Thus, thousands of hours of hard grinding would go to waste if I failed to properly pitch the big-picture significance of my research to my target audience: senior academic colleagues. More generally, many people in a field have good ideas, so the better salespeople are more likely to get their ideas accepted by the establishment. As a low-status grad student, one of the most effective ways for me to “sell” my ideas and projects was to get influential people (e.g., famous professors such as Margo) excited enough to promote them on my behalf.
  16. Generously provide help: One of my favorite characteristics of the Ph.D. experience was that I wasn't in competition with my classmates; it wasn't like if they did better, then I would do worse, or vice versa. Therefore, many of us generously helped one another, most notably by giving feedback on ideas and paper drafts before they were subject to the harsher critiques of external reviewers.
  17. Ask for help: Over the past six years, I became good at determining when, who, and how to ask for help. Specifically, whenever I felt stuck, I sought experts who could help me get unstuck. Finding help can be as simple as asking a friend in my department, or it might require getting referrals or even cold-emailing strangers.
  18. Express true gratitude: I learned to express gratitude for the help that others have given me throughout the years. Even though earning a Ph.D. was a mostly-solitary process, I wouldn't have made it without the generosity of dozens of colleagues. People feel good when they find out that their advice or feedback led to concrete benefits, so I strive to acknowledge everyone's specific contributions whenever possible. Even a quick thank-you email goes a long way.
  19. Ideas beget ideas: As I discovered at the end of my first year, it's nearly impossible to come up with substantive ideas in a vacuum. Ideas are always built upon other ideas, so it's important to find a solid starting point. For instance, the motivations for both IncPy and SlopPy came from my frustrations with programming-related inefficiencies I faced during my 2009 MSR internship. A year later, some of my ideas for extending IncPy, mixed with Fernando's insights on reproducible research and Dawson's mention of Linux dependency hell, led to the creation of CDE. Also, ideas can sometimes take years to blossom, usually after several false starts: I started pondering Burrito-like ideas during my second year and then at the end of my fourth, but it wasn't until my sixth year that I was able to solidify those fuzzy thoughts into a real project.
  20. Grind hard and smart: This book is named The Ph.D. Grind because there would be no Ph.D. without ten thousand hours of unglamorous, hard-nosed grinding. This journey has taught me that creative ideas mean nothing without the extreme effort to bring them to fruition: showing up to the office, getting my butt in the seat, grinding hard to make small but consistent progress, taking breaks to reflect and refresh, then repeating day after day for over two thousand consecutive days. However, grinding smart is just as important as grinding hard. It's sad to see students blindly working themselves to death on tasks that won't get favorable results: approaching a research problem from an unwise angle, using the wrong kinds of tools, or doing useless errands. Grinding smart requires perceptiveness, intuition, and a willingness to ask for help.
I'll end by answering a question involving the F-word: Was it fun?
Some aspects of the Ph.D. experience were very fun: Coming up with new ideas was fun; sketching out software designs on the whiteboard was fun; having coffee with colleagues to chat about ideas was fun; hanging out with interesting people at conferences was fun; giving talks and inciting animated discussions was fun; receiving enthusiastic emails from CDE users around the world was fun. But I probably spent only a few hundred hours on those activities throughout the past six years, which was less than five percent of my total work time.
In contrast, I spent about ten thousand hours grinding alone in front of my computer—programming, debugging, running experiments, wrestling with software tools, finding relevant information, and writing, editing, and rewriting research papers. Anyone who has done creative work knows that the day-to-day grind is rarely fun: It requires intense focus, rigorous discipline, keen attention to detail, high pain tolerance, and an obsessive desire to produce great work.
So, Was it fun?
I'll answer using another F-word: It was fun at times, but more importantly, it was fulfilling. Fun is often frivolous, ephemeral, and easy to obtain, but true fulfillment comes only after overcoming significant and meaningful challenges. Pursuing a Ph.D. has been one of the most fulfilling experiences of my life, and I feel extremely lucky to have been given the opportunity to be creative during this time.

Next - Afterword
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Copyright © 2012 Philip Guo (contact info )

Wednesday, May 30, 2012

The Unimportance of Practically Everything by Greg Mckeown

A friend of mine is the Executive Director for an organization with global reach. He is intelligent and driven, butconstantly distracted. At any given time he will have Twitter, Gmail, Facebook and multiple IM conversations going. The majority of them are useful in some way. Yet, in the back of his mind, he knows there are more important deliverables to get to. But the days slip by and he finds himself working all weekend to catch up. Staying up Sunday night until the early hours of Monday morning has become his modus operandi. He told me, while checking his Blackberry again, that it results in having no social life. It’s so bad that he tried having his Executive Assistant pull all of the internet cables on his computer. But there were still too many ways to get online. When he was struggling to complete a particularly big project, his brother took away his Blackberry and left him at a motel with no internet access. Yet, even there, he still found a workaround within 10 minutes using his ancient Nokia phone to check his email. Eventually, after eight weeks of almost solitary confinement, he was able to get the project done.
Why do otherwise intelligent people find it so easy to be distracted from what really matters?
Social media did not create the problem of distraction, but it is clearly an amplifier. Indeed, a study [PDF] byClifford Nass et al. at Stanford showed that heavy media multitaskers are more susceptible to interference from irrelevant environmental stimuli than light media multitaskers. Heavy multitasking may encourage even heavier multitasking because it leads to a “reduced ability to filter out interference.” Could the part of our brain that is processing deeper cogitative thought actually be atrophying in the process?
None of this would matter if activity and reward were linearly related. But we live in a world where almost everything is worthless and a very few things are exceptionally valuable. This is a counterintuitive idea. After all, the idea that 50% of results come from 50% effort is appealing. It seems fair. Yet, research across many fields paints a very different picture.
As far back as the 1790s, Vilfredo Pareto observed this nonlinear pattern in Italy, where he found that 80% of the land was owned by 20% of the people. Much later, Joseph Moses Juran, one of the fathers of the quality movement, called the insight the “Pareto Principle” and applied it beyond economics. In The Quality Control Handbook, Juran called it “The Law of the Vital Few.” His observation was that you could massively improve the quality of a product by resolving a tiny fraction of the problems. He found a willing audience in Japan, where the country had been producing low-cost, low-quality goods. By adopting the quality processes, the phrase “Made in Japan” gained a totally new meaning. And gradually, the quality revolution led to Japan’s rise as a global economic power.
Distinguishing the “trivial many” from the “vital few” can be applied to every kind of human endeavor and has been done so persuasively by Richard Koch, author of several books on how to apply the Pareto Principle (80/20 rule) to everyday life. Indeed, the examples are everywhere.
Think of Sir Isaac Pitman, the inventor of shorthand, who discovered that just 700 words make up two-thirds of our language (further validated by Zipf’s Law). Or think of Nathan Myhrvold, the former Chief Technology Officer for Microsoft, who said (and then confirmed to me in person for this article), “The top software developers are more productive than average software developers not by a factor of 10x or 100x or even 1,000x, but by 10,000x.” It may be an exaggeration, but it still makes the point that effort and results do not share a linear relationship.
Once we unlearn 50/50 logic, a whole set of behaviors become instinctive. We start scanning our environment for what is really essential. We eagerly eliminate the nonessentials. We say no to 1,000 projects in order to say yes to the one that is exactly what we are looking for.
Just think of Warren Buffett’s philosophy, quoted by Mary Buffett and David Clark in The Tao of Warren Buffett, “You only have to do a few things right in your life, so long as you don’t do too many things wrong.” The authors continue, “Warren decided early in his career it would be impossible for him to make hundreds of right investment decisions, so he decided that he would invest only in the business that he was absolutely sure of, and then bet heavily on them. He owes 90% of his wealth to just ten investments. Sometimes what you don’t do is just as important as what you do.”
First, Do This.
To get started, I recommend a simple action list.
  1. Before you leave the office today, write down your top six priorities for tomorrow on a Post-it note.
  2. Cross off the bottom five.
  3. Write down your top priority on a Post-it note and put it on your computer.
  4. Schedule a 90-minute window to work on your top priority — preferably the first thing of the day.
  5. Every time you are about to check email, Facebook, Twitter etc., write down what you are about to do.
The cumulative impact of this small change can be profound. Indeed, I just received an email from an executive about a member of his team who has a particular tendency to want to do everything. Interestingly, this team member is the most productive member on his team. When he was young, he learned to push past his tendency. (Here’s a funny video with a handy tip for others who are easily distracted.) Most of us just haven’t fully learned how to do that.
But we can.

Tuesday, April 24, 2012

黄昏

兰波- 黄昏
夏日蓝色的傍晚,我将踏上小径,
拨开尖尖的麦芒,穿越青青草地
梦想家,我从鞋底感觉到梦的清新.
我的光头上,凉风习习.

什么也不说,什么也不想,
无尽的爱却涌入我的灵魂,
我将远去,到很远的地方,
就像波希米亚人,
与自然相伴--快乐得如同身边有位女郎。



Monday, April 23, 2012

Monkey Typing

一道题目:一个打字机上有26个字母键,一个猴子每秒钟随意打一个键,问它第一次打出 abc 这个字符串的时间的期望是多少。

@alpha = ('a'..'z');

open (OUT,">monkey_out.txt") or die "could not write to the output file" ;

sub monkey_type
{ @words=();
$sta=1;
while(1)
{
$current=$alpha[rand 26];
push(@words,$current);
if($words[-3] eq "a" && $words[-2] eq "b" && $words[-1] eq "c" )
{
print OUT "$sta\n";
last;
}
$sta++;
}
}


# Set the stimulation cycles here ;
for($i=1;$i<=50;$i++ )
{
&monkey_type;
print "$i\n";
}