You probably by now would have heard of the word AI. You may also have one of two following thoughts when speaking of implementing AI in your business.

I won’t deny this fact I also got overwhelmed by AI and thought it was some rocket science but my curiosity made me learn more about it and I will be helping others understand what is AI, Machine learning, Deep learning, Neural networks, and all these fancy words.

The main idea of AI is to make machines perform tasks and make them work like humans. Thats it.

Now don’t ask me why even do that. Maybe we humans like to sit and relax and do nothing forget it, let’s get back to the topic.

So AI is a theory, similar to the theories in physics like the theory of relativity by Mr Einstein.

The next question which may arise is, if AI is a theory then what is the application of this theory? And here comes the second fancy word Machine learning.

These are a bunch of codes (applying theory using mathematics and coding) that enable machines to find patterns, make decisions, and improve themselves with data.

And did you notice this is exactly what we humans do? I guess now this makes sense to you why I said AI to be a theory.

Theory: Sounds are waves, Application: Radio

Theory: AI, Application: ML.

So to understand how machine learning works, let’s understand what we get when machines learn.

The easiest way to understand it is [x—>y], we give machines something and we expect it to give something in return. For example: I gave my photo and asked who this guy is to the machine (x) and the machine will reply Anupam (y).

So to make machines do that, I first need to give thousands of images (x) of who is anupam(y) and who is not, so that machines find the pattern and the next time I ask if the given image is of Anupam, it takes the decision and replies. This is the process of training the machines.

If the machine fails to give the correct answer then it is trained again with the correct answer and this process is continued until machines gives responses accurately.

Just like humans learn by getting knowledge, similarly machines learn/are trained by a lot of data(x—>y), so that the next time I give it a new x it gives me the correct y for it.

We are creating a machine that does human tasks without humans, how can I make it more human? Give it a human brain. Here comes our third fancy word Deep Learning.

Just like humans have a huge network of neurons, scientists created a huge network of artificial nodes/neurons connected to each other.

These artificial nodes were nothing but some mathematical functions that were capable of learning, performing tasks, and giving an output. Now create a network of all these nodes.

This network (called neural network) was capable of processing more complex patterns and making more complex decisions than any other machine learning model. This was named Deep learning and this gave birth to the new era we are witnessing right now, Generative AI.

I tried to explain all these technical terms in the easiest way possible. My goal is to create an environment where AI can be used by businesses of all sizes and the first step towards that is education. I hope you understood these terms and it will help you with more information I will bring ahead on how to use AI in your business.

That’s all for DAY 1.