In recent years, a growing number of leading AI experts have drawn striking parallels between artificial neural networks and the human brain, suggesting that machine intelligence may not only equal but eventually exceed human cognitive abilities. Geoffrey Hinton, often called the Godfather of Deep Learning, remarked, "Our brains are just big neural networks. There's no reason a neural network can't do anything a brain can do."

In the same vein, Yann LeCun, Meta's Chief AI Scientist, stated, "Intelligence — whether biological or artificial — is the ability to predict, plan, reason, and learn. There's no fundamental law that says machines can't surpass us at all of them." These assertions reflect a widespread belief in the AI community, that by mimicking the structure and learning mechanisms of the human brain, machines can become not only equal to but ultimately more efficient, reliable and capable than humans in the matter. From this perspective, the rise of superintelligent AI is seen not as a question of 'if', but of 'when'.

Fact is that machines have always been wonderful aiders for reducing human work, for enhancing human productivity and making human life easier. But it needs not to be forgotten that machines are engineering feats of humans; the human mind comes up with things it wants to do, collects resources and makes machines that would aid him to do the burdensome task in a better, precise and easier way. In this progression, the more science has been done, the more machines have been made, and the more resources collected. This continual process keeps........

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