In this blog post, you will learn about what AI is, how AI has evolved over the years, and key terms in the AI world. We move to the world of Generative AI, how Gen AI is different than Traditional AI, what’s the fuss about Gen AI, and where is Generative AI used today?
What is AI?
AI is the science of enabling machines to think and learn like humans — but much faster and without fatigue. It’s like teaching a computer to recognise patterns, make decisions, and even create new ideas, just as we do, but using data and algorithms instead of human experience.
How AI Has Evolved Over the Years
- 1950s – AI began as a dream: scientists wanted computers to “think.” Early programs could play chess or solve simple maths problems.
- 1980–1990 – Machine learning came in, where computers could “learn” from examples instead of being told every step.
- 2000 -2010 – Big data and faster computers made AI more powerful. Search engines, spam filters, and recommendation systems became possible.
- 2010–2021 – Deep learning and neural networks gave us voice assistants like Siri and self-driving cars.
- 2021 onwards– Generative AI like ChatGPT that can write, draw, and talk almost like a human. , Agentic AI
Key Terms in the AI World
- Algorithm – A step-by-step set of instructions a computer follows.
- Data – The information AI learns from.
- Machine Learning (ML) – AI that improves its performance as it sees more data.
- Deep Learning – A type of ML inspired by the way our brains work, using “neural networks.”
- Bias – When AI makes unfair or incorrect decisions because of poor or unbalanced training data.
What is Generative AI?
In simple words, Generative AI is a type of Artificial Intelligence that doesn’t just analyse or understand information — it can create new content. That could be text, images, music, videos, designs, or even computer code.
Think of it like a super-creative assistant that has read millions of books, seen billions of images, and heard thousands of hours of music — and can now produce something original for you in seconds.
How is it Different from Traditional AI?
For decades, AI was mainly about recognising patterns and making predictions.
- It could tell you whether an email was spam.
- It could suggest a movie you might like.
- It could detect a tumour in an X-ray image.
But Generative AI goes one step further — it can write the email, design the movie poster, compose the music score, and even generate the video trailer.
AI Has Been Around — So What Changed with Generative AI?
AI has been in use for decades — from simple calculators to complex recommendation engines. But Generative AI is different.
Instead of just recognising patterns or making predictions, it creates — it can write stories, draw pictures, compose music, design products, and even generate software code.
Three things made this possible and exciting:
- Massive Data Availability – AI can now learn from billions of examples, from text to images.
- Advanced Neural Networks – Modern architectures like transformers make it possible to process language and images in ways that feel natural to humans.
- Accessible to Everyone – Tools like ChatGPT, Midjourney, and DALL·E put advanced AI into the hands of everyday people, not just scientists or big tech companies.
That’s why there’s so much buzz — suddenly, AI isn’t just a backend tool, it’s a creative partner you can talk to, brainstorm with, and build with.
Where is Generative AI Used Today?
You might be using it already without realising:
- Content Creation – Blogs, social media captions, product descriptions.
- Art & Design – Creating logos, illustrations, and digital paintings.
- Music & Video – Composing background scores, editing videos, and generating animations.
- Education – Creating personalised learning materials.
- Software Development – Writing and debugging code faster.
