Alex Ko's Public Library

09 Nov 09

A lot of people are either idealistic or cynical, and they take pride in being one and not the other. I think you need to be both.
You need to be idealistic about your vision.
1 more annotations...
- But for code and process, you need to be cynical

One Amongst a Multitude: Thoughts on Hiring: Why You Shouldn't Judge People Solely On Outcomes

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hiring performance self-improvement psychology

The problem that I see with track records is, most people, especially when desperate for more help, never look beyond it and just take everything people with good track records say at face value, and don't dig any deeper.
A long string of successes often blinds us to luck's effect on those outcomes, and we start feeling an aura of invincibility and treating future ventures with an inevitability of success, which is very dangerous.
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- People who don't take risk into account are dangerous for you to be associated with, especially if they have a history of successes. Those successes have probably made them too confident in the way they do things, and are too arrogant to admit mistakes and change.
- Which person/choice improves my probabilities the most for what I want to do?

One Amongst a Multitude: Take the Jump!

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decision-making philosophy self-improvement

There will always be reasons not to do something risky, new, and unfamiliar. But if it's something you really want, then it's a waste of time doing something else. Just make sure it's not about prestige or money, because in the end, that's not what anyone's life should be about.

One Amongst a Multitude: On Choices, and Making Decisions

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decision-making

a lot of times, the only way to improve is to take a risk. Life is about probabilities, and the only thing you can do is to improve your odds.
All of us face decisions everyday, some of us never learn how to do it.

One Amongst a Multitude: Learning to Find the Right Solution

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education problem-solving creativity

the lecture then test part
As a student, when you are facing a question on a test, you know that the expected answer can be constrained to something that you just learned.
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- the majority of graduates from school are only fit to work in the old factory model, where you are told exactly what to do and to follow the solution blindly
- the solution doesn't solve the problem completely
- I find myself trying to apply what I just learned to all the problems that I face right after.
- There is a definite disjoint in what school teaches us and what we have to face in the real world. School gets half of it right, you do need to know the solutions and formulas and ways of doing things.
  But we also need to know when it is appropriate to apply what we learned, and the current model of learning just does not cut it

Russian Math, the Poincare Conjecture and Perelman - WSJ.com

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American math culture has intellectual rigor but also suffers from allegations of favoritism, small-time competitiveness, occasional plagiarism scandals, as well as the usual tenure battles, funding pressures and administrative chores that characterize American academic life. This culture offers the kinds of opportunities for professional communication that a Soviet mathematician could hardly have dreamed of, but it doesn't foster the sort of luxurious, timeless creative work that was typical of the Soviet math counterculture.
It's all but impossible to imagine an American institution that could have provided Mr. Perelman with this kind of near-solitary existence, free of teaching and publishing obligations.

The returns to entrepreneurship « Startup Boy

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Modern Internet entrepreneurship starts with a few engineers working for nothing and carrying latops and cellphones. They coordinate with Skype and Gtalk and Wikis and Bug Tracking sytems. The company itself is snapped together with outsourced HR, cookie-cutter incorporation and even financing, and outsourced finance / payroll. Marketing is done virally, or through SEO, or SEM. Customer service is handled via the community and forums. PR and outreach through tweets and blogging. Payments come via Paypal. Ads are served up by third-party ad networks. Storage goes on Amazon. Computer goes through Amazon, Softlayer or Rackspace. Code is built upon stacks of open source, SaaS, and $10/month services.

What used to cost $1-$2M to start, now costs $10K. What used to cost $5M to build, now costs $250K. What used to cost $20M to go to market now costs $1M.

But the upside hasn’t gone down. It has gone *up.* The 3 billionth person will be online shortly. They can all use your product. Network effects are stronger than ever, and some businesses become natural monopolies very quickly. Most of the products have no marginal cost of replication, so adding a new customer is pure profit.

Less labor required. Less capital required. Less cost to scale. Larger markets. Cheaper marketing. No cost to ship more product.
The returns to scale for being smart, young, skilled, and high-energy have gone up tremendously, and that has profound implications for society. The smart are getting richer.

08 Nov 09

Teach Yourself Programming in Ten Year

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imported learning programming

Researchers (Bloom
(1985), Bryan & Harter (1899), Hayes
(1989), Simmon & Chase (1973)) have shown it
takes about ten years to develop expertise in any of a wide variety of
areas, including chess playing, music composition, telegraph
operation, painting, piano playing, swimming, tennis, and research in
neuropsychology and topology. The key is deliberative
practice: not just doing it again and again, but challenging yourself
with a task that is just beyond your current ability, trying it,
analyzing your performance while and after doing it, and correcting
any mistakes.
Computer science education cannot make anybody an expert
programmer any more than studying brushes and pigment can make
somebody an expert painter
1 more annotations...
- Fred Brooks, in his essay No Silver Bullet
  identified a three-part plan for finding great
  software designers:
  
  Systematically identify top designers as early as possible.
  
  Assign a career mentor to be responsible for the development of the prospect and carefully keep a career file.
  
  Provide opportunities for growing designers to interact and stimulate each other.

07 Nov 09

Lessons Learned: Marching through quicksand

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social-media publishing collaborative-filtering

Most pundits and the people I ask for advice fall into one of two camps. One is explaining the world as it used to work: the importance of gatekeepers, the scarcity implied by limited distribution, and the resulting quality bar that the industry is so proud of. The other revels in the world as we all know it will be someday: limitless distribution enabled by new technologies, the importance of collaborative filters, and on-demand availability of all content for end-users. The problem with engaging with either camp as an author (or “content creator”) is that neither camp is really addressing the world as it exists today.
Personal brands are displacing organizations brands.
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- Because of the incredible array of information available, we have a desperate need for filtering mechanisms.
- Customers will get to consume the content they want, and support the producers of that content directly, rather than having to rely exclusively on intermediaries. And once you have a relationship with an author, musician, or journalist, it will be quite easy for them to offer new products and services – and for you to give them feedback that helps them shape ever more interesting (and ever more profitable) offerings.
- finding new creators is getting difficult
- Media companies are failing at marketing.
- Mass blasts of information are ineffective, because the broadcast channels are suffering from information overload (even in social media).
  There are too many products clamoring for attention.
- Gatekeepers are overloaded.
- All successful media companies had at their heart a series of editors, producers, and agents tasked with discovering and developing new talent.
- story
- petitioning
- This is the total number of activities that the author has engaged in – other than writing – that causes people to give them attention.
- How many people follow your recommendations?
- very few gatekeepers have a rigorous set of metrics
- the best book reviewers only review books published by the best publishers, which only accept manuscripts from the best agents.
- Even if a self-published book was every bit as good as one published by a top-tier press, how would the reviewers know? They can’t even consider 99% of published books already. And how could they possibly review a blog? The problem is that there are no other metrics they can look at to judge the content of a book to know if it’s worth reviewing.
- getting past it
- It’s time for us to start thinking of every piece of content – books, blogs, albums, TV shows, movies, everything – as a new little startup.

Lessons Learned: Validated learning about customers

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entrepreneurship tips

I don’t think revenue is in and of itself a goal for startups, and neither is profit. What matters is proving the viability of the company’s business model, what investors call “traction.” Demonstrating traction is the true purpose of revenue in an early growth company.
Consider this company (as always, a fictionalized composite): they have a million dollars of revenue, and are showing growth quarter after quarter. And yet, their investors are frustrated. Every board meeting, the metrics of success change. Their product definition fluctuates wildly – one month, it’s a dessert topping, the next it’s a floor wax. Their product development team is hard at work on a next-generation product platform,
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- Diagnosis is easy: they are exceptionally gifted salesmen.
- For a startup, having great sales DNA is a wonderful asset. But in this kind of situation, it can devour the company’s future.
- This approach is fundamentally non-scalable.
- This process cannot be delegated, because it’s impossible to explain to a normal person what’s involved in making the sale. The founders have a lethal combination of insight about what potential customers want and in-depth knowledge about what their current product can really deliver
- Without access to customer data, or even a clear product owner, the product development team keeps building feature after feature based on what they think might be useful. But since nobody in the company can clearly articulate what the product is, their efforts result in incoherence.
- This unit of progress is remarkable in several ways. First of all, it means that most aggregate measures of success, like total revenue, are not very useful. They don’t tell us the key things we need to know about the business: how profitable is it on a per-customer basis? What’s the total available market? What’s the ROI on acquiring new customers? And how do existing customers respond to our product over time?
- Validation comes in the form of data that demonstrates that the key risks in the business have been addressed by the current product.
- Products can find sources of validation with impressive stats along a number of dimensions, such as high engagement, viral coefficient, or long-term retention.

04 Nov 09

Chapter3: Luie

muller.lbl.gov/...Nemesis3.htm - Preview

research philosophy self-improvement collaboration physics

The real problems
to solve are not the ones at the end of each chapter in the textbook. The
real problems come in dealing with the unexpected. The questions are vague
and fuzzy. How do you pick a research topic? How long do you study a subject
before you publish? What do you do when things don't look like you expected
them to look, when your results surprise you? How do you recognize when to
quit a not-completely-hopeless endeavor? Coping with these problems is the
art of physics, and it is very similar to the art of business, or the art
of art.
The real problems
to solve are not the ones at the end of each chapter in the textbook. The
real problems come in dealing with the unexpected. The questions are vague
and fuzzy. How do you pick a research topic? How long do you study a subject
before you publish? What do you do when things don't look like you expected
them to look, when your results surprise you? How do you recognize when to
quit a not-completely-hopeless endeavor?
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- It was a research area
  in which many people could work together, be they great scientists or only
  mediocre. Some people would fit more pieces together than others, and some
  were particularly good at finding that hard piece, the one that everyone else
  had given up on. But everybody was able to find some little way to help.
- He intro duced himself with
  "I'm Luie Alvarez," avoiding the title "professor," which
  many other faculty members obviously favored.
- At the end of the tour, Alvarez
  asked me, "When can you start?" I had not understood much of what
  I had seen, and I didn't think I had asked any intelligent questions. In addition,
  Alvarez hadn't had a chance to check my grades or to look at my record in the Physics Department office, so he had
  no way of knowing whether I was a good student. But it was an offer I couldn't
  refuse.
- Alvarez's
  whole approach to physics was that of an entrepreneur, taking big risks by
  building large new projects in the hope of large rewards, although
  his pay was academic rather than financial. He had drawn around him a group
  of young physicists anxious to try out the exciting ideas he was proposing.
  Many of these people were later to leave basic research and become entrepreneurs
  themselves of one kind or another. The true rewards for this kind of work
  were in the challenge, in the adventure. Alvarez seemed to care less about
  the way the picture in the puzzle would look, when everything fit together,
  than about the fun of looking for pieces that fit. He loved nothing more than
  doing something that everybody else thought impossible. His designs were clever,
  and usually exploited some little-known principle that everyone else had forgotten.
- You can read memos anytime, in the evenings, at home, but you can only learn
  experimental physics by being in the laboratory, by doing it
- Even today, when I visit someone's laboratory and they sit me down in a nearby
  office to hear a lecture on their experiment, I protest. I want to go see
  the hardware, if possible to touch it.
- In the Greek legend, the wrestler Antaeus
  was invincible as long as he touched the ground. Hercules defeated him by
  lifting Antaeus above his head, out of reach of the Earth, where he was able
  to squeeze him to death. This legend may have originated as a reminder to
  farmers to stay in close touch with the land, the source of their sustenance,
  and not to relegate all the manual work to hired laborers. The reminder applies
  equally well to experimental physicists, who must return periodically to their
  apparatus, to get their hands dirty, lest they forget why it often takes an
  hour to put in a screw.
- To become an experimental physicist,
  Alvarez seemed to feel, you had to destroy some expensive equipment. It was
  a rite of passage. "Don't do anything differently," he advised.
  "Keep it up."
- There were more Nobel laureates at Berkeley than in the entire
  Soviet Union. And there was Luie, who had no Nobel Prize then but seemed to
  have more important discoveries to his credit than any of the scientists who
  had won the honor.
- But it wasn't the art of invention, but the art of discovery that
  I most wanted to learn. How did he do it? What secret knowledge enabled him
  to make discovery after discovery? If only I could identify what it was, then
  I could try to learn it.
  
  Skepticism,
  the ability not to be fooled, was clearly important, but it is also cheap.
  It is easy to disbelieve everything, and some scientists seemed to take this
  approach. Sometimes Luie was skeptical, but more often he seemed to embrace
  crazy ideas, at least at first. He rarely dismissed anything out of hand,
  no matter how absurd, until he had examined it closely. But then one tiny
  flaw, solidly established, was enough to kill it. His openness to wild ideas
  was balanced by his firmness in dismissing those that were flawed. He had
  a finely honed skepticism. Perhaps that was part of his secret talent.
- the
  key to discovery was not being "lazy."
- The
  hardest discoveries to take seriously are often your own.
- Walter Alvarez never came that close to a Nobel Prize again,
  but he made sure that his son learned the lesson.
- he hadn't looked long enough
- The
  art of physics consists in knowing what to work on and for how long.
- Luie
  worked out virtually all the details before he even told anybody what he was
  thinking of, and he put these in a memo.
- The gaps in his
  knowledge were surprisingly large, but not detrimental to his work.
- He seemed to have a knack for learning just the right amount about everything,
  and for spending the time he saved inventing and bringing together ideas from
  disparate fields.

01 Nov 09

The Valley of My Dreams: Why Silicon Valley Left Boston’s Route 128 In The Dust

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entrepreneurship innovation social-networks

She noted that Silicon Valley had an amazing dynamism about it. There were extensive professional networks, job hopping was the norm, information was exchanged openly, and the culture encouraged risk taking. The Silicon Valley ecosystem supported entrepreneurial experimentation and collective learning. In other words, Silicon Valley was a very open network—a giant social networking site working in analog before the concept of such a thing even existed.

This organizational mechanism was in sharp contrast to that of Route 128. Dominated by large, vertically integrated, and secretive minicomputer producers such as DEC, Wang, Prime, and Data General. Technology, skill, and know-how were trapped within the boundaries of the large corporations.
the meritocratic openness of Silicon Valley made it a magnet for non-traditional talent and immigrants
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- The Northeast cultural block I think is largely and network that tends toward compartmentalization based on the school you attended. I am generalizing, of course, but it’s my experience. Sitting at dinner in the Northeast inevitably there is a contest of schools, where you went and where your kids are going, often with legacy guarantees. Sitting at dinner in Silicon Valley (well, actually, it’s often breakfast before work) no one cares where you went to school. It’s about the work, the ideas. The chance to get rich or to feed the addiction of creating new stuff that changes the world of technology is the topic.
- My barber in Los Gatos felt equal to us all, and had grand plans for his software project, and could get a hearing. That’s tough in the Northeast Corridor, as Princeton, Harvard, MIT, et al networks are largely closed. An odd thing is there are a lot of those folks in Silicon Valley, but in our meetings it rarely comes up as a ticket of entry.
- I chalked this up to a difference between East coast and West coast. Here your pedigree isn’t important. It is all about how smart and ambitious you are. There it is as you say.

31 Oct 09

Diigo Blog » Highlight, Annotate, Archive, Search, Share ~ Diigo ~ the best online research tool just gets even better: Diigo V4 is live now!

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social-bookmarking diigo

Diigo is not merely just another social bookmarking service or a web markup tool. We are developing Diigo to address our personal pain and to help users to better manage the process of discovering, processing, managing, and sharing online information more productively and effectively, so all the features are carefully thought out and seamlessly integrated with personal and team collaboration productivity in mind.
requested

Journal of Eivind Uggedal: NoSQL East 2009 - Summary of Day 2

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database scalability

The problem with Hadoop is that analysis is typically written in Java.
It’s single-input, two-stage data flow (map, then reduce) is rigid.
Joins (distributed) are also hard to do in Hadoop.
Java is simply to verbose for writing map/reduce jobs.
Lastly, rapid prototyping and exploration is hindered by compilation.
At Twitter they run Cloudera’s free distribution of Hadoop 0.20.1, with
a heavily modified Scribe installation for log collection straight to
HDFS, and heavily modified LZO code for fast and splittable data
compression. Data is then stored as either LZO-compressed flat files
or serialized, LZO-compressed protocol buffers.

Semi structured data at Twitter are: apache logs, search logs, RoR logs,
MySQL logs, rate limiter logs, per-application logs.
Structured data are: tweets, users, block notifications, phones, saved
searches, retweets, authentication, SMS usage, third party clients, followings.
Entangled data: the social graph (doesn’t really lend itself to be map/reduced).
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- counts, min, max, std dev
- Pig makes the easy things really
  easy. Cascading makes the hard stuff possible
- Pros of Cascading:
  
  Great to mix Java between the map/reduce steps.
  You don’t have to worry about when to map and when to reduce.
  You don’t have to think about dependencies.
  The data definitions can change on the fly.
  The level above Hadoop is sometimes like black magic. Hard to debug
  at times.
  Data should be outside of a database to get high concurrency.
- Dynamo paper
- Scales up to one box to several billions of nodes/relationships/props on
  a single JVM. If you hit this limit you’ll have to start
  partitioning your data.
- No O/R impedance mismatch.
  Can easily evolve schemas (organically grow the graph).
  Can represent semi structured info
  Can represent graphs/networks (with performance).
  Lacks in tool and framework support.
  Few other implementations means a potential for lock in.
- Sharding is possible today, but you have to do manual work.
  Working on automatic sharding by using clustering algorithm to
  figure out which parts of the graph could be sharded out.
- The client libraries tends to implement consistent hashing
  which makes horizontal scaling easy.
- asynchronously
  writes to disk which somewhat makes it more like a cache than
  a database
- Redis is good for caches, statistics, work queues, social meta data
  like click tracking—where it’s not to bad if you loose some of
  the data.
- Sherpa is a distributed key/value store which is a bit different
  than the Dynamo style solutions. It does geographical distribution
  with low latency local access.
  It scales to thousands of servers and it’s easy
  to add new servers (elastic).
  It automatically recover from failures and can serve reads and
  writes if servers fail.
  You can access your data as a hash table or ordered table.
- The cloud group
  would really like to open source Sherpa, but unfortunately
  it’s built on other internal Yahoo! architecture. They
  are going to open source it piece by piece.

30 Oct 09

Journal of Eivind Uggedal: NoSQL East 2009 - Summary of Day 1

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CoucbDB is very robust since it never overwrites previously
written data. There are therefore not a repair step after
a server crash, and one can take backups with cp.
A really interesting feature of the views are that they are generated
incrementally. The views are stored in a B-tree and kept up-to-date
when new data is added.
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- One can replicate a subset of documents meeting a certain criteria.
  The replication happens over HTTP, which makes replication across
  datacenters easy and secure.
- One of the first adopters of CouchDB of scale was BBC.
- Meebo chose CoucbDB since it was flexible, easily
  queryable, and could scale to hundred of millions of documents.
  They wrote their own sharding library (sitting on HTTP) called
  Lounge (Nginx and Twisted based).
- Riak supports map/reduce. Therefore most of the work happens where
  the data sits. Map/reduce are more scoped when used in Riak than with
  Hadoop and CouchDB.
- Scalable is not about big and not about fast. It’s about understanding
  and predicting how much it’s going to cost you to get better.
  It tells you how much you have to spend to get more.
  The point is that a statement about scalability has to be prefixed
  for what and how it’s scalable.
- Digg is probably the only large site which have Cassandra in production
- Based on the results of the proof of concept Digg are going to port
  the entire application to Cassandra.
- The new architecture of Digg has a services layer in Python
  between the PHP frontend and Cassandra, Memcached, and MySQL
  at the bottom. Communication from PHP to Python is using Thrift.

25 Oct 09

The Atlantic Online | November 2009 | Does the Vaccine Matter? | Shannon Brownlee and Jeanne Lenzer

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health viruses immunity evolution academic publishing statistics

Nobody knows precisely why we are much more likely to catch the flu in the winter months than at other times of the year. Perhaps it’s because flu viruses flourish in cool temperatures and are killed by exposure to sunlight. Or maybe it’s because in winter, people spend more time indoors, where a sneeze or a cough can more easily spread a virus to others. What is certain is that influenza viruses mutate with amazing speed, so each flu season sees slightly different genetic versions of the viruses that infected people the year before.
t
he healthy-user effect explained the entire benefit that other researchers were attributing to flu vaccine, suggesting that the vaccine itself might not reduce mortality at all
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- The results were also so unexpected that many experts simply refused to believe them. Jackson’s papers were turned down for publication in the top-ranked medical journals. One flu expert who reviewed her studies for the Journal of the American Medical Association wrote, “To accept these results would be to say that the earth is flat!” When the papers were finally published in 2006, in the less prominent International Journal of Epidemiology, they were largely ignored by doctors and public-health officials. “The answer I got,” says Jackson, “was not the right answer.”
- In 2004, for example, vaccine production fell behind, causing a 40 percent drop in immunization rates. Yet mortality did not rise.
- nobody was vaccinated
- flu researchers may not like what Jefferson has to say, they cannot ignore the fact that he knows the flu-vaccine literature better than anyone else on the planet
- The vast majority of the studies were deeply flawed, says Jefferson. “Rubbish is not a scientific term, but I think it’s the term that applies.” Only four studies were properly designed to pin down the effectiveness of flu vaccine, he says, and two of those showed that it might be effective in certain groups of patients, such as school-age children with no underlying health issues like asthma. The other two showed equivocal results or no benefit.
- Studies show that young, healthy people mount a glorious immune response to seasonal flu vaccine, and their response reduces their chances of getting the flu and may lessen the severity of symptoms if they do get it. But they aren’t the people who die from seasonal flu.
- Is vaccine necessary for those in whom it is effective, namely the young and healthy? Conversely, is it effective in those for whom it seems to be necessary, namely the old, the very young, and the infirm?
- They feel strongly that vaccine has been shown to be effective and that a sham vaccine would put test subjects at unnecessary risk of getting a serious case of the flu. In a phone interview, Fauci at first voiced the opinion that a placebo trial in the elderly might be acceptable, but he called back later to retract his comment, saying that such a trial “would be unethical.” Jefferson finds this view almost exactly backward: “What do you do when you have uncertainty? You test,” he says. “We have built huge, population-based policies on the flimsiest of scientific evidence. The most unethical thing to do is to carry on business as usual.”
- whose mere presence in the emergency room has endangered the lives of others
- when patients with even mild flu symptoms show up in the hospital, they vastly increase the spread of the virus, simply because they inevitably sneeze and cough in rooms that are jammed with other people
- Why, then, has the federal government stockpiled millions of doses of antivirals, at a cost of several billion dollars? And why are physicians being encouraged to hand out prescriptions to large numbers of people, without sound evidence that the drugs will help? The short answer may be that public-health officials feel they must offer something, and these drugs are the only possible remedies at hand.
- This is the curious state of debate about the government’s two main weapons in the fight against pandemic flu. At first, government officials declare that both vaccines and drugs are effective. When faced with contrary evidence, the adherents acknowledge that the science is not as crisp as they might wish. Then, in response to calls for placebo-controlled trials, which would provide clear results one way or the other, the proponents say such studies would deprive patients of vaccines and drugs that have already been deemed effective.
- long-recurring theme in American medicine
- The annals of medicine are littered with treatments and tests that became medical doctrine on the slimmest of evidence, and were then declared sacrosanct and beyond scientific investigation.
- Demonstrating the efficacy (or lack thereof) of vaccine and antivirals during flu season would not be hard to do, given the proper resources. Take a group of people who are at risk of getting the flu, and randomly assign half to get vaccine and the other half a dummy shot. Then count the people in each group who come down with flu, suffer serious illness, or die.
- vaccinating healthy people—who can mount an immune response on their own—protects the more vulnerable people around them
- 50 percent of health-care workers say they do not intend to get vaccinated for swine flu and don’t routinely get their shots for seasonal flu, in part because many of them doubt the vaccines’ efficacy
- Launched early enough and continued long enough, social distancing can blunt the impact of a pandemic
- Washing hands diligently, avoiding public places during an outbreak, and having a supply of canned goods and water on hand are sound defenses
- In the United Kingdom,
  the national health department is promoting a “buddy” program, encouraging citizens to find a friend or neighbor willing to deliver food and medicine so people who fall ill can stay home.
- In the U.S., by contrast, our reliance on vaccination may have the opposite effect: breeding feelings of invulnerability, and leading some people to ignore simple measures like better-than-normal hygiene, staying away from those who are sick, and staying home when they feel ill. Likewise, our encouragement of early treatment with antiviral drugs will likely lead many people to show up at the hospital at first sniffle. “There’s no worse place to go than the hospital during flu season,” says Majumdar. Those who don’t have the flu are more likely to catch it there, and those who do will spread it around, he says. “But we don’t tell people this.”

24 Oct 09

Boliao - A New Movement In Digital Marketing | Six Pixels of Separation - Marketing and Communications Blog - By Mitch Joel at Twist Image

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social-media marketing

The Answer Factory: Fast, Disposable, and Profitable as Hell | Magazine

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social-media information-economy knowledge-markets youtube related human-based-computation marketing

To appreciate the impact Demand is poised to have on the Web, imagine a classroom where one kid raises his hand after every question and screams out the answer. He may not be smart or even right, but he makes it difficult to hear anybody else.
The focus on LTV keeps Demand away from any kind of breaking news coverage or investigative work, neither of which tends to hold its value.
4 more annotations...
- a crowdsourced team of freelance “title proofers” turn the algorithm’s often awkward or nonsensical phrases into something people will understand: “How to make a church-pew breakfast nook,” for example, becomes “How to make a breakfast nook out of a church pew.” Approved headlines get fed into a password-protected section of Demand’s Web site called Demand Studios, where any Demand freelancer can see what jobs are available. It’s the online equivalent of day laborers waiting in front of Home Depot. Writers can typically select 10 articles at a time; videographers can hoard 40.
- It turned out that gut instinct and experience were less effective at predicting what readers and viewers wanted — and worse for the company — than a formula.
- You can take something that is thought of as a creative process and turn it into a manufacturing process.
- Online content is not worth very much. This may be a truism, but Rosenblatt has the hard, mathematical proof. It’s right there in black and white, in the Demand Media database — the lifetime value of every story, algorithmically derived, and very, very small. Most media companies are trying hard to increase those numbers, to boost the value of their online content until it matches the amount of money it costs to produce. But Rosenblatt thinks they have it exactly backward. Instead of trying to raise the market value of online content to match the cost of producing it — perhaps an impossible proposition — the secret is to cut costs until they match the market value.

Be lucky - it's an easy skill to learn - Telegraph

www.telegraph.co.uk/...ts-an-easy-skill-to-learn.html - Preview

psychology philosophy luck self-improvement

I gave both lucky and unlucky people a newspaper, and asked them to look through it and tell me how many photographs were inside. On average, the unlucky people took about two minutes to count the photographs, whereas the lucky people took just seconds. Why? Because the second page of the newspaper contained the message: "Stop counting. There are 43 photographs in this newspaper." This message took up half of the page and was written in type that was more than 2in high. It was staring everyone straight in the face, but the unlucky people tended to miss it and the lucky people tended to spot it.
Personality tests revealed that unlucky people are generally much more tense than lucky people, and research has shown that anxiety disrupts people's ability to notice the unexpected.
2 more annotations...
- unlucky people miss chance opportunities because they are too focused on looking for something else
- My research revealed that lucky people generate good fortune via four basic principles. They are skilled at creating and noticing chance opportunities, make lucky decisions by listening to their intuition, create self-fulfilling prophesies via positive expectations, and adopt a resilient attitude that transforms bad luck into good.

Linux: Linus Says, Linux Not Designed; It Never Was | KernelTrap

kerneltrap.org/11 - Preview

linux evolutoin evolutionary-computation human-based-computation

we humans have _never_ been able to replicate
something more complicated than what we ourselves are, yet natural
selection did it without even thinking.
The very architecture of UNIX has very much been an evolution.
7 more annotations...
- When they say that the devil is in the details, they are trying to tell
  you that the details MATTER. In fact, the details matter quite a lot more
  than the design ever does.
- It's "directed mutation" on a microscopic level, but there is very little
  macroscopic direction. There are lots of individuals with some generic
  feeling about where they want to take the system (and I'm obviously one of
  them), but in the end we're all a bunch of people with not very good
  vision.
- I have never _ever_ met a technical person (including me) whom I
  would trust to know what is really the right thing to do in the long run.
- Too strong a strong vision can kill you - you'll walk right over the edge,
  firm in the knowledge of the path in front of you.
  
  I'd much rather have "brownian motion", where a lot of microscopic
  directed improvements end up pushing the system slowly in a direction that
  none of the individual developers really had the vision to see on their
  own.
- And I'm a firm believer that in order for this to work _well_, you have to
  have a development group that is fairly strange and random.
- The scientific paper
  system in computer science is based on publishing things people already
  believe.
- Engineering does not require science. Science helps
  a lot but people built perfectly good brick walls long before they knew why
  cement works.

Alex Ko's Public Library

One Amongst a Multitude: Cynical or Idealistic?

One Amongst a Multitude: Thoughts on Hiring: Why You Shouldn't Judge People Solely On Outcomes

One Amongst a Multitude: Take the Jump!

One Amongst a Multitude: On Choices, and Making Decisions

One Amongst a Multitude: Learning to Find the Right Solution

Russian Math, the Poincare Conjecture and Perelman - WSJ.com

The returns to entrepreneurship « Startup Boy

Teach Yourself Programming in Ten Year

Lessons Learned: Marching through quicksand

Lessons Learned: Validated learning about customers

Chapter3: Luie

The Valley of My Dreams: Why Silicon Valley Left Boston’s Route 128 In The Dust

Diigo Blog » Highlight, Annotate, Archive, Search, Share ~ Diigo ~ the best online research tool just gets even better: Diigo V4 is live now!

Journal of Eivind Uggedal: NoSQL East 2009 - Summary of Day 2

Journal of Eivind Uggedal: NoSQL East 2009 - Summary of Day 1

The Atlantic Online | November 2009 | Does the Vaccine Matter? | Shannon Brownlee and Jeanne Lenzer

Boliao - A New Movement In Digital Marketing | Six Pixels of Separation - Marketing and Communications Blog - By Mitch Joel at Twist Image

The Answer Factory: Fast, Disposable, and Profitable as Hell | Magazine

Be lucky - it's an easy skill to learn - Telegraph

Linux: Linus Says, Linux Not Designed; It Never Was | KernelTrap

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