Difference between Traditional AI and Generative AI

Traditional AI (Artificial Intelligence):

What it does: Traditional AI is rule-based. It follows specific programmed rules to perform tasks. Think of it like a set of instructions that the computer strictly adheres to.

How it works: It relies on predefined algorithms and requires explicit instructions. It’s good at tasks with clear rules and guidelines.
Example: If you tell a traditional AI to play chess, it follows a set of predefined rules for each chess piece and makes moves based on those rules.

Generative AI:

What it does: Generative AI is more creative. It learns from data and can generate new content or responses. It doesn’t just follow fixed rules; it can come up with original output.

How it works: It uses neural networks to understand patterns in data and generate something new based on what it has learned. It’s often used for tasks like creating art, writing, or generating human-like responses in conversation.

Example: If you show a generative AI a lot of pictures of cats, it can learn from them and then create entirely new pictures of cats, even ones it has never seen before.

In simpler terms, traditional AI is like a really smart robot that follows instructions well, while generative AI is more like a creative assistant that can learn from examples and come up with its own ideas. Traditional AI is great for tasks with clear rules, while generative AI is better suited for tasks that involve creativity and generating new content.