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Man Vs Machine (pg 3 of 3)
Performance, Ability and Adaptability Performance and Ability - So, even though we have proved it to you that the brain is far more superior to today's best computers, many of us out there wouldn't believe it. Why ? Because of the differences in performance. We can obviously see that any low-end computer can beat the fastest human at calculation as well as storing and processing of any information. Here's what we have to say. Although the brain has got more ability, it has got more tasks to perform than that expected of a computer. Did you realize that the brain is has to constantly take charge of maintaining the human body functions for the entire lifetime its host ? Actions like breathing, blinking, coordination of all the body parts are controlled subconsciously by the brain all the time. At the same time, the brain is constantly bombarded by all your senses all at once. In one mere second, the retina sends ten one-million-point images to the brain. At the same time, your ear drums pass sound information real-time at higher-than-CD-quality. And don't forget the information send to the brain by your sense of touch and smell. If a normal higher-end computer was fed with the information from a human's senses constantly and asked to process and react to them, the computer would overload from too much information because it can't react as fast as the brain could. There are many reason why the brain loses out to computers in simple and straightforward jobs (esp. computational and recording jobs). The brain is made for general purposes, not specifically just for computational jobs. In theory, the brain could be as quick as a computer in computational and recording jobs but in real life, it will never be possible because the average human is constantly distracted by his overwhelming senses, his emotions and his own thoughts. There are exceptional people who could read through a 500 page book in less than an hour and remember all the contents as well as people who could perform mathematical calculations at a snap of their fingers but they are only rare examples that prove the hidden potential of the human brain. Adaptability and Learning The brain - Because the human brain receives so much information from all the senses at a constant rate, it is only natural that it would tend to learn and adapt very quickly about its environment and surroundings. In fact, a glance of any of the senses at the surroundings would already provide the brain with enough information about the environment to allow the brain to react immediately with a response. Many of us think that it may seem natural that the human brain is better at non assisted learning and acquiring of new skills when compared to a computer.The human brain is able to learn by trail and error, induce conclusions from past experience and create new methods to deal with the situations it has come across. However, when learning a new skill or quitting a old habit, the human brain requires time to adapt to the behaviours required. When a person does a particular task repeatedly for a number of times, he would realize that the more times he does it, the easier it is for him to do the same task. When continued over longer periods of time, it becomes so easy for the person that he does it sub-consiously, hence, it becomes a habit. Even quitting of habits need adapting to, because the habits are now part of the brain's sub consiousness and the brain performs it even without instruction from the consiousness. Remember that we told you that the memory of a brain seems unabsolute ? That could also be a reason behind the need for adaption during learning. To be given a permanent place in the sub-consious mind, knowledge of the skills are to be translated into relevant instructions for the various parts of the mind so as to perfect the various requirements of the new skill. The hand-eye coordination, finger control or the sense of timing required for the new skill are aquired mostly through trial and error, hence explaining the need for adaption. The computer - Computers are getting smarter by the day. Computer programs at research labs are constantly learning anything that the programmers are feeding them with. Voice reconigtion engines are developed but feeding the program with thousands of different voices from entire towns so that it could pick up patterns in speech, accents and slangs and learn to reconigse them. OCR (optical character recogition) programs are picking up new tips and patterns as it observes the different styles of writings from its ever increasing database. Smarter programs are now able to classify pictures of objects it never saw before into different catogories in real-time by studying their shapes and textures or by observing similair patterns in the picture's coding. The rate of learning computers using smart programs have a big advantage, that is they can share their data between different computers. Data and results achieved first by other computers by trial and error or by observation of patterns can be copied directly to other computers, hence increasing their rate of learning. Since the memory of computers are absolute (either recorded or deleted) , computers need no adapting when they are loaded with traditional programs and are asked to run them. However, some smart programs are capable of learning by trial & error, learning from their mistakes and recording the best solutions to any problems it faces. (an example is the household robot, Cye (created by Henry Thorne) which would memorise the way around a new house without anyhelp simply by trial and error ; banging into walls and barriers and drawing a map of the landmarks it has banged into) Computer learning techniques seem to have taken the right pushes at the right areas, especially the step towards learning to learn by using of the two most important senses, sight and sound. It would not be a overstatement to say that computers would in a decade's time be able to learn simply from observation and examples; In the future, we can expect simplier yet smarter programs.
The brain is still the overall winner in many fields when it comes to numbers. However, because of its other commitments, the brain is less efficient when a person tries to use it for one specific function. The brain is as we can put it, a general purpose processor when compared to the computer. It therefore loses out when it comes to efficiency and performance. We have given the estimate for total human performance at 100 million MIPS, but the level of efficiency for which this can be applied to any task may only be a small fraction of the total. (this fraction depends on the adaptibilty of the brain to the task) Deep Blue, the chess machine that bested world chess champion Garry Kasparov in 1997, used specialized chips to process chess moves at a the speed equivalent to a 3 million MIPS universal computer. This is 1/30 of the estimate for total human performance. Since it is plausible that Kasparov, probably the best human player ever, can apply his brain power to the strange problems of chess with an efficiency of 1/30, Deep Blue's near parity with Kasparov's chess skill supports the theory of the level of efficiency of total performance. ( Garry Kasparov beat Deep Blue with a very close, 2 -1 )
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