From Noise to Art: Exploring Stable Diffusion and Creative AI


Never a day passes when I don’t find myself scrolling through the infinite loop of YouTube Shorts. Has it become my daily routine? Maybe, maybe not. Surely a debatable topic. One day, the YouTube algorithm pushed a short on my feed (they know that I am a Computer Engineer, Shhh🤫!) and it grabbed my attention in no time. Topic? Stable Diffusion. It was a short video of a guy approaching the subway, and it suddenly transforms into animated imaginative stuff.

(Image Courtesy)

After being mesmerised by that video, I decided to dive deeper into the world of Stable Diffusion. As a Computer Engineer, I’m always curious about new technologies, especially those that intersect creativity and technical prowess. I spent hours researching, reading articles, and watching more videos to understand the underlying mechanics of diffusion models.

You must be thinking, “I want that kind of video for my Instagram feed too,” correct? You’re not the only one; I thought that too. Don’t worry, I’ve got your back to help you understand how this works and I will provide the resources you need to get started. I won’t be spoon feeding you but will point out right resources and clear the concepts behind all these.

First, we need to understand what in the world is DIFFUSION.


Imagine you’re in a room with a strong scent of perfume in one corner. Over time, the scent spreads out evenly throughout the room. This spreading out is called diffusion. In simple terms, diffusion is the process of something spreading out to fill a space evenly.

Now, let’s connect this to the world of computers and artificial intelligence. In the realm of AI, diffusion models are used to generate images, but in a reverse way. Instead of spreading out, they start with a lot of noise (like static on a TV) and slowly transform that noise into a clear, meaningful image through a series of steps. 🖥️🌐

Here’s where STABLE DIFFUSION comes into play.

(Image courtesy)


Stable Diffusion is a type of AI model that can create incredibly detailed and imaginative images from random noise. Think of it as a digital artist that starts with a canvas full of random dots and, step by step, turns it into a stunning piece of artwork. This model is “trained” on vast amounts of data, learning the patterns and details needed to create images that look real or fantastical, depending on what you want. 🎨✨

Remember that YouTube Short with the subway transforming into animated imaginative stuff? That’s a perfect example of what Stable Diffusion can do. It takes an initial image or video and, through a process of adding and refining details, it morphs into something entirely new and creative. 🚇🎨

Imagine a serene scene: a couple lying in an open green field, surrounded by the gentle rustle of leaves and the warmth of the sun. As they gaze up at the sky, the man points excitedly towards a fluffy cloud drifting by. ☁️☀️

“Look at that cloud,” the man says. “Doesn’t it look like a rabbit?”

The woman tilts her head slightly and looks at the sky. “Where?” she asks.

“Right there,”he says, pointing at an imaginary outline in the air. “See? It has long ears and a fluffy tail.”

At first, the woman sees nothing but a shapeless mass of white against the blue sky. But as she follows the direction of his finger and lets her imagination take over, suddenly, she sees it too—the outline of a rabbit, clear as day, formed by the contours of the cloud.

This simple interaction between the couple displays the working of Stable Diffusion. In this analogy, the man represents the AI model, while the woman acts as the observer. Just like the man guiding the woman towards the cloud, the AI model starts with a noisy, chaotic image and gradually refines it, pointing out details and patterns until the desired image emerges.

The woman’s ability to recognize the rabbit in the cloud is similar to a trained model in Stable Diffusion. Just as she already knows what a rabbit looks like, the AI model has been trained on vast amounts of data, learning to recognize patterns and generate realistic images.

The above layman explanation was given to me by  – Darsh Shukla

In both cases, the end result is a transformation: from a jumble of noise or shapeless clouds to a clear, recognizable image—the rabbit in the sky, or a stunning piece of digital art. 

So, the next time you find yourself gazing up at the clouds, remember the magic of Stable Diffusion. Just as a simple cloud can become a rabbit with a little imagination, so too can noisy data be transformed into something extraordinary with the power of AI. 


Deforum Colab

Using Deforum Colab is a fun and easy way to get started with Stable Diffusion.  You don’t need to be a tech expert. Whether you want to create stunning visuals for social media or just explore the possibilities of AI, give Deforum Colab a try.  You might be surprised at what you can create! ✨

In conclusion, Stable Diffusion is a fascinating concept that allows AI models to transform noise into stunning images and videos, much like the way our imagination can turn clouds into familiar shapes. 

Here is the link of the video that I generated using Stable Diffusion’s Protogen Model in the Defrorum’s Colab notebook:


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