Generative AI
You have most recently heard of ‘Generative AI’ this is a subset of Machine Learning technology which has become one of the most used buzzwords in tech circle’s and beyond. Generative AI is everywhere right now. But what exactly it is ? How does it works ? The concept of AI itself bring up the fear for humans to get replaced by AI, so how can we make most use of it to make our life’s (Jobs) easier?
What's the difference between AI, Machine Learning and Generative AI?
Generative AI, AI (Artificial Intelligence), and Machine Learning all belongs to same broad field of Study, but represents a different concept or level of specificity.
Artificial Intelligence is the biggest term among the three. It’s about creating machines or software that can think and act like humans. This includes doing tasks that usually require human intelligence and getting better at these tasks with experience. Within AI, there are different areas such as natural language processing (NLP), computer vision, robotics, and machine learning. These are all ways that AI can be used to make machine smarter.
Machine Learning (ML) is a part of AI. It’s a way for computers to learn from data and make choices, instead of being told exactly what to do. ML gets better as it sees more data.
Generative AI is like a special kind of machine learning. Imagine it as a model that learns from some data, and then it can create new things that are similar to that data. It’s not just about making predictions or decisions based on the data; it’s also about being creative and making new, original outputs.
How Does Generative AI Works ?
Generative AI works like a creative person, such as a painter making a new painting or a musician composing a new song. It creates new things based on the patterns it has learned. Imagine learning to draw a cat. You look at many cat pictures and notice things like the body shape, pointy ears, and whiskers. When asked to draw a cat from memory later, you use these patterns to create a new cat picture. It’s not an exact copy of any cat you’ve seen, but a new cat based on the general idea.
Generative AI does something similar. It learns from lots of examples, like images, text, or music. The AI studies these examples to learn the patterns and structures in them. When it learns enough, it can create new examples that are similar.
For example, an AI trained on cat images could make a new cat picture, or one trained on text could write a paragraph about a cat that sounds human. These creations aren’t exact copies but new pieces that follow the patterns it learned. The key thing is that generative AI doesn’t just copy; it creates new things based on what it learned. That’s why it’s called “generative” AI.
