MARCHING TOWARDS THE WORLD OF BIONIC TERMINATORS!

Ouch! I dropped a baby. Everyone looks scared! And a robot raises that voice. Oh! No what the hell are you doing with the baby? Sigh, don’t worry! The baby was dropped just a few centimetres from the bed and it’s actually a baby toy.  Ha-ha! Test procedures are on their full swift phase, for your information.

My physics staff told me once that Einstein is the only person who successfully used 1% of brain’s activity. Ooh! Still I’m wondering about that. You might have watched the Hollywood movie named “Lucy”. In that, they pictured us a view of what would probably happen if we used our brain at its full efficiency. How they came up with such concepts? I don’t know whether it’s right or wrong; however I’m sure that it wouldn’t happen that way whatsoever. Here the researchers are in a way to interpret the brain’s activity on neural network based artificial intelligence.

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When it comes to Machining/Automation, we first try to imitate the things by how it’s been done at present, and then modify it; and later on, additional features will be added and we procure lots of versions. Just think about the evolution of grinders from olden days to now, a very good transformation right? Likewise, Artificial Neural Networks (ANNs) are statistical models which has been imitated and inspired from biological neural networks. Modelling and processing of nonlinear relationships between inputs and outputs are done by them in parallel. Machine learning is the key for artificial intelligence.

Human brain is the most complex thing to understand. Its computation is so powerful. Roughly 100 billion neurons are in brain which are networked. Intelligence is gained by connecting/networking neurons. Two kinds of processes will be going on in our brain when we think of a certain aspect. One is activation and next is summation. Domain understanding might be needed to know about this stuff. Anyways, let’s move to ANNs.

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Layers of artificial neurons form the artificial neural networks. To be simple, initially an input layer and an output layer in the end. In between, there lies a hidden layer. Lots of neurons are present in every layer. Hidden layer takes care of iterative learning and problem solving (providing solution). Complexity in providing solutions depends on number of neurons and hidden layers. ANNs are extremely powerful but not as powerful as brain. Its inner working is very difficult to understand; hence the algorithm used in it is called as black-box algorithm. As complexity involves in ANNs, one should be very careful before going to implement it on a system. More likely, it might seem to be as same as digital computing where everything is pre-programmed. Artificial intelligence has the ability to learn from its mistakes and also has the ability to reprogram itself. In other words, it is dynamic until finds an apt solution for a problem.

Undoubtedly, applications of Artificial intelligence are gonna excite us in various ways. Terminator movie could be a reality as well. Arghhh! However, we must be prepared and never lose control.

Evolution is required but not for destruction.

 

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3 Comments

  1. I think your article is interesting, but poorly edited. You were missing many words out of your sentences. I was able to decipher what you meant for most of them. Please, don’t take this criticism negatively. Just before you go to print, make sure you have a separate person read though your article an help you catch your errors.

    Liked by 1 person

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