How I Explained AI, Machine Learning and Generative AI to My 5 Year-old Kid
The hype around Artificial intelligence (AI) and Generative AI has reached every corner of our life. Even as a kid you cannot miss noticing these terms. And for curious young minds (like my 5-year-old son) they immediately come with the question — “Papa, what is AI?”
When I encountered this question from my son, at first I didn’t know how to explain. Then I took a day, and come up with a super simple approach to explain:
· What is Artificial intelligence (AI)?
· What is Machine Learning (ML)?
· What is Generative AI?
The same approach can be used if you want to explain these terms to any non-technical person, may be your grandparents 😊
What is Artificial Intelligence (AI)?
Imagine you have lost your dog, and you need to find him. Here are some of the capabilities you need to find your dog:
You should be able to Identify your dog.
Since you were a toddler, you have seen many animals. Since we have helped you identify a dog, you know how does a dog look like.
You can also identify YOUR OWN DOG.
You should be able to make a strategy to find your dog.
You need to be able to make a strategy to find your dog. For example:
· First search in our house.
· If you don’t find him, then search in play area where you usually go with your dog.
· If you don’t find him yet, ask your friends.
· And so on….
You should be able to act according to situation.
For example, if it’s raining, and you know that your dog does not like to get wet, you will focus your search on shaded places.
Now, imagine someone told you — “I have probably seen your dog in garden”.
You (Actually Your Brain) know what to do.
· You know where garden is and how to go there.
· You will not confuse a cat or a tree with a dog.
· The moment you see a dog you will try to identify if it’s your dog or not.
You could search your dog because you have all these intelligences.
What if somehow, we could give all these intelligence to a robot so that next time you lose your dog, your robot could find him.
Imagine the robot can move and capture videos. But that’s not enough. To find your dog, we need to enable this robot to think like you and act like you.
For example:
· We enable the robot to identify your room. But it should be able to recognize the room even if your bed is moved to another wall, or blanket is changed. It needs INTELLIGENCE to identify room even with new changes.
· We enable the robot to identify a dog and distinguish your specific dog.
· We enable the robot to understand human language and instructions.
· We enable the robot to come up with a strategy and act as per new situations. Like search only in shaded places if it’s raining.
In summary, to find your dog, the robot needs HUMAN LIKE INTELLIGENCE.
If we could do that, next time you lose your dog, your robot friend might just find him using its artificial intelligence. It’s like having a little helper with human-like smarts!
This is Artificial Intelligence (AI) — Human like intelligence, created in a robot (or a machine or computer) by human.
The next question I got was — “Papa, let’s enable our robot with AI. How can we actually do that?”
On this, I told him that you are too young to do it. Focus on your study and may be after few years you can do that :D
If you are still not clear on AI, let’s understand using an example of an Super Smart Car
Imagine we have a super smart car which can drive all by itself, just like a grown-up driving a real car.
This car is like a clever buddy. It has a brain, just like how you think and decide when you play. But instead of eyes like yours, it has special cameras to see the road and sensors to feel everything around it.
The car has Intelligence to take Human-like decisions, such as:
· If there’s another car in front, it will stop.
· If it sees someone crossing the road, it will slow down or stop based on situation.
· If the road is clear, it will increase speed.
· If road is clear but road condition is not good, it will slow down.
· If there’s a big red ball rolling across the road, the car will notice it and know to stop so it doesn’t bump into the ball.
The car has intelligence to learn from it’s experience.
This is Artificial Intelligence (AI) — Human like intelligence, created in a car (or a machine or computer) by human.
We stopped our conversation there. But I also prepared myself how to explain Machine Learning and Generative AI in case he asks later.
Machine Learning (ML)
In our previous discussion, we talked about enabling the robot to identify a dog. Let’s explore this further.
Imagine we want to enable the robot not just to identify a dog but other animals as well.
To do so, we will show him pictures of various dogs, cats, bunnies and other animals and label each picture with the name of the animal. We train the robot to identify animals based on size, colour, body shape, sound etc.
Once the training is completed, the robot will be able to identify these animals we trained him for.
Note that all dogs do not look alike. However, once robot has seen many pictures of dogs, it can identify any dog even if it does not exactly look like a specific picture. We need to show lots of pictures of dog to the robot. More pictures it sees, more efficient it will be.
This is Machine Learning - Teaching a robot (or any machine) by giving lots of example pictures (or any other information).
In the computer’s world, information is like the special stuff we call data.
To summarize, Machine Learning is:
· A type of Artificial Intelligence.
· Which enables machines (or computers) to learn from data and make decisions.
Note: If you are a programmer, remember a key point about machine learning, that it’s about learning from data without being explicitly programmed to do so.
Supervised and Unsupervised Learning
Now, let’s take another example. When you went to your class first day, you met lots of classmates. At first all classmates were same to you. But with time, you yourself categorized them in different groups:
· You find some classmates very good and want to be friend with them.
· You find some rude or irritating and want to avoid them.
· You find some very good in sports and want to be in the same team as they are.
· And so on…
Note one important point — When you categorized your classmates, nobody told you how to do that. You yourself did that without anyone’s help.
Similarly, let’s imagine we showed lots of pictures of dogs, cats, bunnies etc. without any label to our robot and told him — “I’m not going to tell you which one is which. Go explore and figure it out”.
The robot starts to look at these animals, noticing things like their fur, size, and how they move. It doesn’t know their names yet, but it’s trying to find patterns and differences on its own.
After exploring, the robot might notice that:
· Some animals have long ears (bunnies)
· Some animals have soft fur and a tail (cats)
· Some animals have wagging tails (dogs)
It figures out these categories without you telling it directly.
In the end, the robot might not know the names of the animals, but it can say that “These animals are similar in some ways, and those are different in other ways.”
Conclusion
If you compare this with our previous example where we enabled the robot to identify an animal, there is a big difference.
When we trained our robot by showing pictures of animals, we labelled each picture with the name of the animal. So, we acted like a teacher to him. We first told him how does a dog or a cat look like and then only he was able to identify them.
In Machine Learning we call this Supervised Learning.
However, when we asked the robot to categorize the animals, we didn’t help him. He categorizes the animals by himself based on patterns and differences.
In Machine Learning we call this Unsupervised Learning.
Generative AI
When we discussed Artificial Intelligence in a robot or a car, there was one thing common — The AI Car or AI Robot, although having human-like intelligence, does not have creativity.
Imagine I asked you to draw an animal you have never seen before. You need to use your imagination and draw a brand-new animal the world has never seen.
Since you have imaginative power and creativity, you will be able to do that. Maybe you will draw an animal that has the body of a lion, face of a cow and the wings of a butterfly.
Now, what if you have a magical robot friend who can create new things all by itself! It can create new things, like artwork, music, or even realistic images, without being explicitly told what to create.
If you show this magical robot lots of pictures of lions, cow and butterflies. Now, with this knowledge, it can draw a completely new animal, like a “lion-cow-butterfly” combination. It doesn’t copy any existing image; instead, it uses its understanding of what makes lion, cow, and butterfly unique to create something entirely new something like below.
This is Generative AI — A robot (or computer) which has imagination and creativity to draw pictures, tell stories, or even make up new games without anyone showing it how.
To summarize, Generative AI is:
· A type of artificial intelligence
· that can create new things, like artwork, music, or even realistic images
· without being explicitly told what to create
Hope you enjoyed reading this blog and got a clear understanding of AI, Machine Learning and Generative AI.
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