NEURAL NETWORKS NEURON : STUDENTS A.I. ESSAY

THE HUMAN BRAIN is a massively parallel, self-organising biological system composed of approximately 86 billion neurons, each forming thousands of synaptic connections.

Working in parallel means that each of the 86 billion neurons can be active at the same time communicating with thousands of others through synapses.

Therefore, the human brain processes millions of tasks simultaneously.

WHEN a small angelic student sees a cat, the brain is recognising the shape 3-dimensionally, gauging its volume and weight, processing the motion in 3D environment, associating the image with memories, activating related emotions, etc. - all at the same time.

This parallelism allows the brain to process millions of tasks simultaneously and to be extremely fast and efficient in a complex environment.

At the same time when the brain is processing the presence of a cat, it may also be talking to someone, doing chores, and also receiving synapses from all the organs and systems of the body, wherein it is organising functions at multiple levels.

Artificial Neural Networks are simplified mathematical models with rigid architecture, typically organised in layered sequences.

They learn by optimising numerical weights through backpropagation and gradient descent - abstract statistical processes far removed from the rich, embodied learning of human beings.

While AI systems require vast amount of labeled data to learn specific tasks, human children can grasp abstract concepts, infer meanings and generalise from just a few examples, often guided by curiosity, intitution and social interaction.

These differences are not merely technical ; they point to a deeper divide between AI and organic intelligence shaped by millions of years of evolution and engineered systems bound by human-coded rules and objectives.

This Master Student Essay continues. The World Students Society thanks Anila Shezad, a geopolitical analyst.