Little Bits of Artificial Intelligence

1. Story: The Village Teacher and the Smart Notebook

In a small village, there was a kind teacher named Miss Nira. She wanted to evaluate her students fairly — not just based on test marks, but also on class participation, homework, behavior, and improvement.

At first, she tried assigning weights to each category herself:

• 50% test marks
• 20% homework
• 10% participation
• 10% improvement
• 10% behavior

But it didn’t always feel right. Some students who tried hard didn’t get the grades they deserved, and some high scorers were not improving or helping others.

So, she had an idea — she built a smart notebook that could learn from past grading decisions.

How the Smart Notebook Worked

Miss Nira started by feeding the notebook examples of her past grading:

• For Riya: 85 test, 90 homework, 80 participation → Grade A
• For Ramu: 70 test, 60 homework, 50 participation → Grade C … and so on.

The notebook didn’t understand grades directly. Instead, it guessed, and each time it was wrong, Miss Nira corrected it. Over time, it started learning patterns.

The notebook had multiple layers of tiny decision makers inside — let’s call them neurons.

Each neuron did something simple:

1. Took the numbers (test, homework, etc.).
2. Gave them importance using its own weights.
3. Combined them.
4. Applied a logic function (like “if the total is high enough, pass my signal”).
5. Sent the result to the next layer of neurons.

At the final step, one neuron made a guess — “I think this is a Grade B.”

Miss Nira compared it to the actual grade and said, “No, it’s an A.” The notebook then adjusted its internal weights slightly.

The Training Cycle

This process continued for hundreds of students:

• Guess
• Compare
• Adjust

Over time, the notebook got really good at guessing correctly, even for students it had never seen before.

2. What is Neural Network?

Just like Miss Nira’s notebook:

• A neural network takes inputs (numbers/features).
• It passes them through layers of neurons.
• Each neuron adjusts its behavior during training.
• Finally, it outputs a prediction (like a grade, a yes/no, or a number).

And it keeps learning from feedback until it becomes really smart!

3. Why it’s called a “neural network” ?

The Inspiration: Human Brain

Miss Nira’s smart notebook was actually inspired by how our brain works.Inside our brains, we have billions of tiny nerve cells called neurons.

Each neuron

• Receives signals from other neurons
• Processes them
• Sends a signal forward if it thinks it’s important

It’s like a giant team of messengers passing information, making decisions, and learning over time.

How That Looks in the Smart Notebook

Miss Nira’s notebook had:

• Many small decision-makers (like brain neurons)
• Each connected to many others
• Working together in layers
• Learning by adjusting how strongly they’re connected (just like neurons in the brain form stronger or weaker connections over time)

This web of artificial “neurons” is called a network.

Why “Neural Network”?

Because:

• It mimics neural (brain cell) behavior.
• And it forms a network of many such simple units.

So, just like a brain made of neurons, a neural network is a machine made of artificial neurons.It’s not alive, of course — but it learns, remembers, and adapts — in a simplified version of how a brain does.