‘Bride & prejudice ‘the latest flick from the stable of Gurinder chadha is supposedly an adaptation from the famous classic ‘Pride & Prejudice’. Congrats to Gurinder she has managed to insult Jane Austin in the meanest possible way. To be precise – this film is shit! In fact I would go as far as saying that it is truck loads of shit!! Although there is a so called storyline, the film doesn’t manage to keep the interest of the audience till the end. So far for the storyline, where (as in so many films) aishwarya is confused to the core as to who to marry. Although she was undoubtedly the high point of the movie, se lacked the acting skills to carry it off. The songs being the integral part of any Indian movie, have been messed up to such an extent that I have no words to describe the damage done to the viewers during those painful and agonizing minutes in the theatre. I think due to public safety ‘Anu Malik‘ should stop making songs. Martin Henderson the Hollywood hunk has a taste of Indian cineme what with all the running around the trees. He did a good job nevertheless compared to his previous film ‘Torque’.
In spite of all this the movie carries a hidden meaning and a moral for all its viewer’s. This movie being a bit let down from Gurinder’s last movie ‘Bend it like Beckham’. You might want to watch this movie if you want to increase your ‘tolerance threshold level’...
Monday, October 18, 2004
The Next Breakthrough
The notion that the world around is continuously evolving is obvious; we rarely grasp its full implications. We do not ordinarily think, for example, of an epidemic disease changing its character as the epidemic spreads. Nor do we think of evolution in plants and animals as occurring in a matter of days or weeks, though it does. And we do not ordinarily imagine the green world around us as a scene of constant, sophisticated chemical warfare, with the plants producing pesticides in response to attack, and insects developing resistance. But that is what happens too.
In the past few years, artificial life had replaced artificial intelligence as a long term computing goal. The idea was to write programs that had the attributes of living creatures – the ability to adapt, cooperate, learn and adjust to change. Many of those qualities were especially important in robotics, and they were starting to be realized with distributed processing or DNA computing.
Distributed processing meant that you divided your work among several processors, or among a network of virtual agents that you created in the computer. There were several basic ways this was done –
1) one way was to create a large population of fairly dumb agents that worked together to accomplish a goal – just like a colony of ants worked together to accomplish a goal.
2) Another method was to make a so-called neural network that mimicked the network of neurons in the human brain. It turned out that even simple neural nets had surprising power. These networks could learn. They could build on those past experiences.
3) The third technique was to create virtual genes in the computer, and let them evolve in the virtual world until some goal was attained.
And there were several other procedures, as well. Taken together, these procedures represented a huge change from the older notions of artificial intelligence. In the old days, programmers tried to write rules to cover every situation. For example, they tried to teach computers that if someone purchased something at the store, they had to pay before leaving. But this commonsense knowledge proved extremely difficult to program. The computer would make mistakes. New rules would be added to avoid the mistakes. Then more mistakes, and more rules. Eventually the programs were gigantic, millions of lines of code, and they began to fail out of the sheer complexity. They were too large to debug. You simply could not figure out where the errors were coming from.
So it began to seem as if the rule – based AI was never going to work. Lots of people made dire predictions about the end of artificial intelligence. They started predicting that the computers would never match human intelligence.
But distributed networks of agents offered an entirely new approach. And the programming philosophy was new, too. The old – rules based programming was “ top down “. The system as a whole was given rules of behavior. But the new programming was “ bottom up “. The program defined the behavior of individual agents at the lowest structural level. But the behavior of the system as a whole was not defined. Instead, the behavior of the system emerged, the result of hundreds of small interactions occurring at a lower level. Because the system was not programmed, it could produce surprising results! Results never anticipated by the programmers. That was why they could seem “ lifelike “.
DNA computing involved agent – based programs that modeled biological populations importantly in the real world. Like the programs that mimicked ant forging to control big communications networks. Or programs that mimicked division of labor among termite colonies to control thermostats in a skyscraper. And closely related were the programs that mimicked genetic selection, used a for a wide range of applications. Example of one such application is – witnesses to a crime were shown nine faces and asked to choose which was most like the criminal, even if none really were; the program then showed them nine more faces, and asked them to choose again; and from repeated generations the program slowly evolved a highly accurate composite picture of the face, far more accurate than any police artist could make. Witnesses never had to say what exactly they were responding to in each face, they just chose, and the program evolved.
Most AI systems are very static. Most of them can usually only solve one given specific problem, since their architecture was designed for whatever that specific problem was in the first place. Thus, if the given problem were somehow to be changed, these systems could have a hard time adapting to them, since the algorithm that would originally arrive to the solution may be either incorrect or less efficient. Genetic algorithms (or GA) were created to combat these problems. They are basically algorithms based on natural biological evolution. The architecture of systems that implement genetic algorithms (or GA) are more able to adapt to a wide range of problems. A GA functions by generating a large set of possible solutions to a given problem. It then evaluates each of those solutions, and decides on a "fitness level" (you may recall the phrase: "survival of the fittest") for each solution set. These solutions then breed new solutions. The parent solutions that were more "fit" are more likely to reproduce, while those that were less "fit" are more unlikely to do so. In essence, solutions are evolved over time. This way you evolve your search space scope to a point where you can find the solution.
In the past few years, artificial life had replaced artificial intelligence as a long term computing goal. The idea was to write programs that had the attributes of living creatures – the ability to adapt, cooperate, learn and adjust to change. Many of those qualities were especially important in robotics, and they were starting to be realized with distributed processing or DNA computing.
Distributed processing meant that you divided your work among several processors, or among a network of virtual agents that you created in the computer. There were several basic ways this was done –
1) one way was to create a large population of fairly dumb agents that worked together to accomplish a goal – just like a colony of ants worked together to accomplish a goal.
2) Another method was to make a so-called neural network that mimicked the network of neurons in the human brain. It turned out that even simple neural nets had surprising power. These networks could learn. They could build on those past experiences.
3) The third technique was to create virtual genes in the computer, and let them evolve in the virtual world until some goal was attained.
And there were several other procedures, as well. Taken together, these procedures represented a huge change from the older notions of artificial intelligence. In the old days, programmers tried to write rules to cover every situation. For example, they tried to teach computers that if someone purchased something at the store, they had to pay before leaving. But this commonsense knowledge proved extremely difficult to program. The computer would make mistakes. New rules would be added to avoid the mistakes. Then more mistakes, and more rules. Eventually the programs were gigantic, millions of lines of code, and they began to fail out of the sheer complexity. They were too large to debug. You simply could not figure out where the errors were coming from.
So it began to seem as if the rule – based AI was never going to work. Lots of people made dire predictions about the end of artificial intelligence. They started predicting that the computers would never match human intelligence.
But distributed networks of agents offered an entirely new approach. And the programming philosophy was new, too. The old – rules based programming was “ top down “. The system as a whole was given rules of behavior. But the new programming was “ bottom up “. The program defined the behavior of individual agents at the lowest structural level. But the behavior of the system as a whole was not defined. Instead, the behavior of the system emerged, the result of hundreds of small interactions occurring at a lower level. Because the system was not programmed, it could produce surprising results! Results never anticipated by the programmers. That was why they could seem “ lifelike “.
DNA computing involved agent – based programs that modeled biological populations importantly in the real world. Like the programs that mimicked ant forging to control big communications networks. Or programs that mimicked division of labor among termite colonies to control thermostats in a skyscraper. And closely related were the programs that mimicked genetic selection, used a for a wide range of applications. Example of one such application is – witnesses to a crime were shown nine faces and asked to choose which was most like the criminal, even if none really were; the program then showed them nine more faces, and asked them to choose again; and from repeated generations the program slowly evolved a highly accurate composite picture of the face, far more accurate than any police artist could make. Witnesses never had to say what exactly they were responding to in each face, they just chose, and the program evolved.
Most AI systems are very static. Most of them can usually only solve one given specific problem, since their architecture was designed for whatever that specific problem was in the first place. Thus, if the given problem were somehow to be changed, these systems could have a hard time adapting to them, since the algorithm that would originally arrive to the solution may be either incorrect or less efficient. Genetic algorithms (or GA) were created to combat these problems. They are basically algorithms based on natural biological evolution. The architecture of systems that implement genetic algorithms (or GA) are more able to adapt to a wide range of problems. A GA functions by generating a large set of possible solutions to a given problem. It then evaluates each of those solutions, and decides on a "fitness level" (you may recall the phrase: "survival of the fittest") for each solution set. These solutions then breed new solutions. The parent solutions that were more "fit" are more likely to reproduce, while those that were less "fit" are more unlikely to do so. In essence, solutions are evolved over time. This way you evolve your search space scope to a point where you can find the solution.
Wednesday, October 13, 2004
Confusion leads to Confusion
Ever wonder why ‘confusion’ word is used to denote a confused state? ( Actually a person might be as jobless as I’m to think about such a foolish and preposterous question ). The Chinese philosopher Confucius (who has confusion rhymed in his name itself) was so confused all the time, that his philosophies were also confusing enough to confuse the non-confused in order to ultimately confuse the world which otherwise was non-confused.
Confusion stems out from the fact that a situation when confused leads you into the ever increasing dark tunnel of further confusion. Until you enter this mother of all confusion which like quicksand engulfs you slowly into it and you with the ‘stuffed frog’ expression ( which has been the latest work of a taxidermist) , sense yourself slowly going down deeper and deeper until you see your doom ( not the game! ) clearly in front and decide suicide is far better option than getting confused. The more confused you think you are, the more confusion engulfs you in its confused state. Confused Eah ? Let me make it non-confusing. Ultimately, Confusion leads to confusion which misguides non-confused to fall into the clutches of the confused.
Before this post leads to further confusion, there is a non-confusing challenge to the reader. How many times have I used the word ‘confusing, confusion or confused’ in this post? post the answer as comment. The correct answer will receive a Gift hamper. Finally this post is dedicated to the people who remain confused all their lives. I hope they come out of it…
Confusion stems out from the fact that a situation when confused leads you into the ever increasing dark tunnel of further confusion. Until you enter this mother of all confusion which like quicksand engulfs you slowly into it and you with the ‘stuffed frog’ expression ( which has been the latest work of a taxidermist) , sense yourself slowly going down deeper and deeper until you see your doom ( not the game! ) clearly in front and decide suicide is far better option than getting confused. The more confused you think you are, the more confusion engulfs you in its confused state. Confused Eah ? Let me make it non-confusing. Ultimately, Confusion leads to confusion which misguides non-confused to fall into the clutches of the confused.
Before this post leads to further confusion, there is a non-confusing challenge to the reader. How many times have I used the word ‘confusing, confusion or confused’ in this post? post the answer as comment. The correct answer will receive a Gift hamper. Finally this post is dedicated to the people who remain confused all their lives. I hope they come out of it…
The Limits of the Limitless Mind
Mind is considered to be a very complex organ. It is said to be almost 30 times more powerful than the most powerful computer ever built. With all the massive amount of data the mind can store and all the data it processes from various stimuli, mind is nothing but dependent, a slave ! why in spite of its immense abilities mind cannot master everything? We have engineers who specialize in engineering, they in turn have to depend on the doctors and vice versa. Why do you find people specializing in certain areas only? I guess if we knew everything we would be called the omniscient, omnipotent, the god. But I’m not getting involved with religion or philosophy here and my line of thought is purely logical and scientific.
In spite of all these short comings the mind is the ultimate creator of all man-made things including the puny thing we call as ‘computer’. Why then do we compare ourselves with something of our own creation? Doesn’t it sound stupid? Is it an indication of our insecurity levels? I guess these questions will be unanswered for a long time…
In spite of all these short comings the mind is the ultimate creator of all man-made things including the puny thing we call as ‘computer’. Why then do we compare ourselves with something of our own creation? Doesn’t it sound stupid? Is it an indication of our insecurity levels? I guess these questions will be unanswered for a long time…
A Typical Collegy Day
Getting up in the morning is probably as painful as a ‘root-canal surgery’. But nevertheless, I have to get up. That gives proof to people around you that you are alive. With great difficulty you get up and find the restroom occupied. You wait your turn in a fidget manner and then relieve yourself by flooding the shit holes! Then I drag myself to station to go to college. I wait patiently for the train and when it finally comes, I find it very ‘trainy’. I get in it and find myself amid people struggling to stand. The ratio of amount of free space to the amount of space occupied may be 1:10. Hanging alone the bars I reach college, probably ‘mougli’ would have found it an amusing journey but not me.
I reach class which is as ‘classy’ as it can get. Then I lay down my bed and sleep. Yeah ! that’s right I snore my head off. When the college gets over my ‘friendly friends’ wake me up and I wake up as a zombie would wake up from a grave. Anyway, I come home eat some ‘shit’ popularly called as food and again embrace the ‘brother of death’.
After reading all this, people might think that I have slipped a bit on my mental side, well for all your guesses you might be right!! There is a saying “ A person is what his environment around is”, so can I safely assume that all those around me are also nuts? What say?
I reach class which is as ‘classy’ as it can get. Then I lay down my bed and sleep. Yeah ! that’s right I snore my head off. When the college gets over my ‘friendly friends’ wake me up and I wake up as a zombie would wake up from a grave. Anyway, I come home eat some ‘shit’ popularly called as food and again embrace the ‘brother of death’.
After reading all this, people might think that I have slipped a bit on my mental side, well for all your guesses you might be right!! There is a saying “ A person is what his environment around is”, so can I safely assume that all those around me are also nuts? What say?
Monday, October 04, 2004
" You Look Thin"
there is this general opinion among the upper echelons of the creatures on Earth that I’m thin and all that they spot of me is a fully formed human skeleton and that too without an X-ray machine. other souls might be taken for a toss, but me being among the only few who could get a check-up without an X-ray machine, take it in an optimistic tone. I mean there might be a case where the other person has an ocular defect and I get the comment in turn. Vasuda, a friend of mine who greets me in a manner known to none. here’s a little example –
vasuda : “ Hi , Srikar you are thin “
This has happened so many times that, it sort of became my second name. in fact, if someone calls me just ‘srikar’ ,I sort of start wondering as to what happened to my other part of the name. I mean talk about give and take respect!! This is grossly against Gandhian principles. I would retaliate (just like Albert Einstein did when bitten by an ant)
by saying that maybe they should consult a ‘good ophthalmologist ‘. What Say??
vasuda : “ Hi , Srikar you are thin “
This has happened so many times that, it sort of became my second name. in fact, if someone calls me just ‘srikar’ ,I sort of start wondering as to what happened to my other part of the name. I mean talk about give and take respect!! This is grossly against Gandhian principles. I would retaliate (just like Albert Einstein did when bitten by an ant)
by saying that maybe they should consult a ‘good ophthalmologist ‘. What Say??
The Way of Love
[ Caution ]
People who are expecting something light and funny to read can close this page right
now !! The following content is “ food for thought “ and is alleged to cause severe mental agony to whoever reads it. The views expresses here are entirely mine and are based on my perceptions. and to answer a few – “ No, you needn’t be the intellectual equivalent of 50 Dalai Lama’s to understand this..”
[ Caution Ends ]
Most of you might have heard a saying “ God is Love and Love is God “. This reiterates the fact that there exists one supreme lord and love is common in this world. The Christians, Muslims, Jews, Hindus etc. worship different gods but, truly there is only one god. Why then if we love the same one god, do we quarrel? We quarrel because we do not know and understand what real love is. If we have true love and affection for the one supreme lord we will naturally love each other.
We are all part and parcels of the same supreme lord. Even though we are all individuals, we all depend upon the same sun & we all breath the same air. This is the principle of “ Unity in Diversity “. Unity refers to the fact that we are all part and parcels of the same lord, the father of all; and diversity refers to our eternal individual natures. Because this is the eternal reality, we will only find peace and happiness in this reality. Unity in Diversity will have no meaning if people have no faith in the supreme lord, or love for him & all his living entities. We cause misery due to misunderstanding. We do not know how to love everyone. This can only be achieved by first embracing the supreme love. Some of us think he does not exist at all, some think he is impersonal and some think there are different divinities for those of different religious faiths. For all I can say, they are still not mature enough to embrace the “All Attractive Reservoir of Pleasure “…
People who are expecting something light and funny to read can close this page right
now !! The following content is “ food for thought “ and is alleged to cause severe mental agony to whoever reads it. The views expresses here are entirely mine and are based on my perceptions. and to answer a few – “ No, you needn’t be the intellectual equivalent of 50 Dalai Lama’s to understand this..”
[ Caution Ends ]
Most of you might have heard a saying “ God is Love and Love is God “. This reiterates the fact that there exists one supreme lord and love is common in this world. The Christians, Muslims, Jews, Hindus etc. worship different gods but, truly there is only one god. Why then if we love the same one god, do we quarrel? We quarrel because we do not know and understand what real love is. If we have true love and affection for the one supreme lord we will naturally love each other.
We are all part and parcels of the same supreme lord. Even though we are all individuals, we all depend upon the same sun & we all breath the same air. This is the principle of “ Unity in Diversity “. Unity refers to the fact that we are all part and parcels of the same lord, the father of all; and diversity refers to our eternal individual natures. Because this is the eternal reality, we will only find peace and happiness in this reality. Unity in Diversity will have no meaning if people have no faith in the supreme lord, or love for him & all his living entities. We cause misery due to misunderstanding. We do not know how to love everyone. This can only be achieved by first embracing the supreme love. Some of us think he does not exist at all, some think he is impersonal and some think there are different divinities for those of different religious faiths. For all I can say, they are still not mature enough to embrace the “All Attractive Reservoir of Pleasure “…
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