To be happy with a man you must understand him a lot and love him a little....
To be happy with a woman you must love her a lot and not try to understand her at all....
Tuesday, July 31, 2007
Sunday, July 29, 2007
Thursday, July 12, 2007
10 mistakes to avoid in software development
Forrester Research published this week a report listing 10 mistakes that send software development projects off track.
The 10 mistakes that put projects at risk of failure include:
*** Never committing to project success.
*** Freezing the schedule and budget before a project is sufficiently understood.
*** Overscoping a solution.
*** Circumventing the application development organization altogether.
*** Underestimating the complexity of a problem.
*** Being stingy with subject-matter experts, in which their participation is not sufficient.
*** Choosing the wrong project leadership.
*** Distrusting managers who have had tasks delegated to them.
*** Jumping into development without enough research.
*** Suppressing bad news, in which dialogue is insufficient.
The 10 mistakes that put projects at risk of failure include:
*** Never committing to project success.
*** Freezing the schedule and budget before a project is sufficiently understood.
*** Overscoping a solution.
*** Circumventing the application development organization altogether.
*** Underestimating the complexity of a problem.
*** Being stingy with subject-matter experts, in which their participation is not sufficient.
*** Choosing the wrong project leadership.
*** Distrusting managers who have had tasks delegated to them.
*** Jumping into development without enough research.
*** Suppressing bad news, in which dialogue is insufficient.
Friday, July 06, 2007
Swarm Intelligence
Ants aren't smart. Ant colonies are. A colony can solve problems unthinkable for individual ants, such as finding the shortest path to the best food source, allocating workers to different tasks, or defending a territory from neighbors. As individuals, ants might be tiny dummies, but as colonies they respond quickly and effectively to their environment. They do it with something called swarm intelligence.
One key to an ant colony, for example, is that no one's in charge. No generals command ant warriors. No managers boss ant workers. The queen plays no role except to lay eggs. Even with half a million ants, a colony functions just fine with no management at all—at least none that we would recognize. It relies instead upon countless interactions between individual ants, each of which is following simple rules of thumb. Scientists describe such a system as self-organizing.
Ants communicate by touch and smell. When one ant bumps into another, it sniffs with its antennae to find out if the other belongs to the same nest and where it has been working. (Ants that work outside the nest smell different from those that stay inside.) Before they leave the nest each day, foragers normally wait for early morning patrollers to return. As patrollers enter the nest, they touch antennae briefly with foragers.
"When a forager has contact with a patroller, it's a stimulus for the forager to go out," Gordon says. "But the forager needs several contacts no more than ten seconds apart before it will go out."
That's how swarm intelligence works: simple creatures following simple rules, each one acting on local information. No ant sees the big picture. No ant tells any other ant what to do. Some ant species may go about this with more sophistication than others. (Temnothorax albipennis, for example, can rate the quality of a potential nest site using multiple criteria.) But the bottom line, says Iain Couzin, a biologist at Oxford and Princeton Universities, is that no leadership is required. "Even complex behavior may be coordinated by relatively simple interactions," he says.
Inspired by the elegance of this idea, Marco Dorigo, a computer scientist at the Université Libre in Brussels, used his knowledge of ant behavior in 1991 to create mathematical procedures for solving particularly complex human problems, such as routing trucks, scheduling airlines, or guiding military robots.
One key to an ant colony, for example, is that no one's in charge. No generals command ant warriors. No managers boss ant workers. The queen plays no role except to lay eggs. Even with half a million ants, a colony functions just fine with no management at all—at least none that we would recognize. It relies instead upon countless interactions between individual ants, each of which is following simple rules of thumb. Scientists describe such a system as self-organizing.
Ants communicate by touch and smell. When one ant bumps into another, it sniffs with its antennae to find out if the other belongs to the same nest and where it has been working. (Ants that work outside the nest smell different from those that stay inside.) Before they leave the nest each day, foragers normally wait for early morning patrollers to return. As patrollers enter the nest, they touch antennae briefly with foragers.
"When a forager has contact with a patroller, it's a stimulus for the forager to go out," Gordon says. "But the forager needs several contacts no more than ten seconds apart before it will go out."
That's how swarm intelligence works: simple creatures following simple rules, each one acting on local information. No ant sees the big picture. No ant tells any other ant what to do. Some ant species may go about this with more sophistication than others. (Temnothorax albipennis, for example, can rate the quality of a potential nest site using multiple criteria.) But the bottom line, says Iain Couzin, a biologist at Oxford and Princeton Universities, is that no leadership is required. "Even complex behavior may be coordinated by relatively simple interactions," he says.
Inspired by the elegance of this idea, Marco Dorigo, a computer scientist at the Université Libre in Brussels, used his knowledge of ant behavior in 1991 to create mathematical procedures for solving particularly complex human problems, such as routing trucks, scheduling airlines, or guiding military robots.
Thursday, July 05, 2007
Entrancing concepts - Selfish Gene
The Selfish Gene is a very popular and somewhat controversial book on evolution by Richard Dawkins, published in 1976.
It builds upon the principal theory of George C. Williams's first book Adaptation and Natural Selection. Dawkins coined the term selfish gene as a provocative way of expressing the gene-centered view of evolution, which holds that evolution is best viewed as acting on genes, and that selection at the level of organisms or populations almost never overrides selection based on genes. An organism is expected to evolve to maximise its inclusive fitness – the number of copies of its genes passed on globally (rather than by a particular individual). As a result, populations will tend towards an evolutionarily stable strategy.
Andrew Brown has written:
"Selfish", when applied to genes, doesn't mean "selfish" at all. It means, instead, an extremely important quality for which there is no good word in the English language: "the quality of being copied by a Darwinian selection process." This is a complicated mouthful. There ought to be a better, shorter word – but "selfish" isn't it.
A crude analogy can be found in the old saw about a chicken being just an egg's way of making more eggs. In a similar inversion, Dawkins describes biological organisms as "vehicles" or survival machines, with genes as the "replicators" that create these organisms as a means of acquiring resources and copying themselves. At the level of organisms, we can see genes as being for some feature that might benefit the organism, but at the level of genes, the sole implicit purpose is to benefit themselves.
It builds upon the principal theory of George C. Williams's first book Adaptation and Natural Selection. Dawkins coined the term selfish gene as a provocative way of expressing the gene-centered view of evolution, which holds that evolution is best viewed as acting on genes, and that selection at the level of organisms or populations almost never overrides selection based on genes. An organism is expected to evolve to maximise its inclusive fitness – the number of copies of its genes passed on globally (rather than by a particular individual). As a result, populations will tend towards an evolutionarily stable strategy.
Andrew Brown has written:
"Selfish", when applied to genes, doesn't mean "selfish" at all. It means, instead, an extremely important quality for which there is no good word in the English language: "the quality of being copied by a Darwinian selection process." This is a complicated mouthful. There ought to be a better, shorter word – but "selfish" isn't it.
A crude analogy can be found in the old saw about a chicken being just an egg's way of making more eggs. In a similar inversion, Dawkins describes biological organisms as "vehicles" or survival machines, with genes as the "replicators" that create these organisms as a means of acquiring resources and copying themselves. At the level of organisms, we can see genes as being for some feature that might benefit the organism, but at the level of genes, the sole implicit purpose is to benefit themselves.
Monday, July 02, 2007
Take a break
Took one day leave and visited my house at Aluva. Completed the tasks at home and spend some valuable time with my mother.
My old colleagues at Infopark had arranged a one day trip (Kumarakom boat cruise). Spend one day with them. Had lots of fun. I was black out due to overdose of alcohol - so a part of the entertainment was not accessible for me :(
Had a religous gettogether at my wife's house. After attending the same, we left for Trivandrum.
Three days finished as if it was a dream. Waiting for the next travel.
My old colleagues at Infopark had arranged a one day trip (Kumarakom boat cruise). Spend one day with them. Had lots of fun. I was black out due to overdose of alcohol - so a part of the entertainment was not accessible for me :(
Had a religous gettogether at my wife's house. After attending the same, we left for Trivandrum.
Three days finished as if it was a dream. Waiting for the next travel.
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